Datastream

June 21, 2024 by Nithisha CHALLA

Datastream

In this article, Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management (MiM), 2021-2024) presents information referring to a global financial dataset, which plays a vital role in today’s financial markets for making informed investment decisions.

Introduction

Datastream is a global financial dataset that contains current and historical time series data on stocks, indices, bonds, funds, futures, options, interest rates, commodities, currencies, and economic indicators for 175 countries and 60 markets. It is accessible via two platforms: WRDS and LSEG Workspace.

It is an industry-leading analytical data source that enables detailed exploration of relationships between data series: perform correlation and relationship analysis, test investment and trading ideas, and research countries, regions and industries with time series sometime available from the 1900s onwards.

History

Datastream was developed by Thomson Reuters, now part of Refinitiv, and has been a vital tool for financial professionals for several decades. It has continually evolved to incorporate more data and improve its user interface, reflecting advancements in technology and the increasing demand for comprehensive financial information.

With over 35 million individual instruments or indicators across all major asset classes, including 8.5 million active economic indicators and over 14 million economic time series every day. It features 120 years of data, across 175 countries – the information and tools you need to interpret market trends, economic cycles and the impact of world events.

Its history extends as far back as the 1900s for G7 countries, the 1970s for other major markets and the 1980s for smaller countries.

Uses of Datastream

There are different uses of Datastream such as for investment research, economic analysis, portfolio management, academic research and financial reporting.

Investment Research

Investors and analysts use Datastream to research and evaluate potential investments by analyzing historical performance and financial health. Refinitiv offers in-depth coverage of more than 12,500 global companies across 74 countries, with over 630 metrics and history dating back to 2002.

For example, Refinitiv MarketPsych ESG Analytics (a part of Datastream) are real-time data series which can easily be incorporated into your investment and analysis process, whether quantitative or qualitative. Refinitiv MarketPsych ESG data is available on 100,000+ public and private companies and 252 countries and regions, covering more than 250 strategic ESG data measures, structured into 10 categories underlying the four areas of corporate performance.

Economic Analysis

Economists and policy makers use the database to monitor economic trends, make forecasts, and formulate economic policies.

Economists uses Datastream to access historical GDP data, inflation rates, employment figures, and other relevant economic indicators.

Portfolio Management

Portfolio managers use Datastream to track the performance of assets, optimize asset allocation, and manage risks of their portfolios or funds.

The risk manager uses Datastream to analyze historical price volatility, correlations between assets, and economic indicators that impact market risk. Datastream has had a number of marked firsts within the industry and was a pioneer when it came to calculating indices’ relative data on a daily basis. Thanks to their vast coverage of constituents across the major asset classes, users can construct benchmarks tailored to their respective strategies. This means a fund’s relative performance can be tracked more accurately.

Datastream also offers extensive global coverage of historical end-of-day fund data, with over 30 years of history and a range of measures including net asset value, dividends and performance metrics, plus supporting and operating data such as classifications, identifiers and legal entity all sourced directly from Refinitiv Lipper.

Academic Research

Scholars and students in finance and economics use the extensive data for empirical research, thesis work, and academic publications.

Financial Reporting

Financial institutions use the data for internal reporting, regulatory compliance, and strategic planning.

Finance teams use Datastream to pull data on the company’s stock performance, compare it with industry benchmarks, and include relevant economic indicators.

Advantages of Datastream

To achieve their goals, Datastream is used by various entities and individuals for various reasons: comprehensive coverage, historical depth, user-friendly interface, reliable and timely data, and customization.

Comprehensive Coverage: One of the most extensive databases available, covering a wide range of financial instruments and global markets.
Historical Depth: Offers deep historical data, essential for long-term analyses and trend identification.
User-Friendly Interface: Intuitive tools and interfaces for data extraction, charting, and analysis.
Reliable and Timely Data: Provides accurate and up-to-date information, crucial for making informed financial decisions.
Customization: Users can customize data queries and reports to meet specific research and analysis needs.

Challenges of using Datastream

Given that Datastream deals with real-time or near-real-time data, there are several challenges in processing the streaming data:

Data Overload: The vast amount of financial data available can be overwhelming, making it difficult to filter relevant information.
Data Quality: Ensuring the accuracy and reliability of financial data is crucial, as incorrect data can lead to poor investment decisions.
Cybersecurity: Protecting financial data from cyber threats and unauthorized access is a significant concern for financial institutions and data providers.
Cost: Access to premium financial data services can be expensive, posing a challenge for individual investors and smaller firms.

Conclusion

Datastream plays a critical role in the modern financial ecosystem. By providing real-time access to a wide array of financial data, it empowers investors, analysts, and institutions to make informed decisions, enhance market transparency, and drive economic growth. As technology continues to evolve, the accessibility and quality of financial data will only improve, further transforming the landscape of financial markets.

Why should I be interested in this post?

This article provides a comprehensive overview of Datastream, with clear examples and explanations of key concepts. For management students, understanding and analyzing the corporate world is equally important as being a part of it and making changes in it.

Useful resources

LSEG Refinitiv datastream

Princeton University Library Datastream

Thomson Reuters Thomson Reuters Datastream Economics

NYU libraries Datastream Guide

European University Institute (EUI) Datastream description

About the author

The article was written in June 2024 by Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management (MiM), 2021-2024).

S&P Global Market Intelligence

May 30, 2024 by Nithisha CHALLA

S&P Global Market Intelligence

In this article, Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management (MiM), 2021-2024) presents S&P Global Market Intelligence, which provides financial data, news and analytics for the financial community.

Introduction

S&P company believes that to keep pace with today’s constantly evolving markets, data must be smarter, deeper, and instantly accessible. Their new Market Intelligence platform puts a world of information at the fingertips of market participants, allowing them to make strategic business decisions with conviction, speed, and laser-focused insight.

Logo of S&P Market Intelligence
Logo of S&P Global
Source: S&P Global

History

Standard & Poor’s (S&P) was established in 1860 by Henry Varnum Poor, initially focusing on providing financial data and analysis to investors. The company gained prominence for its pioneering efforts in financial transparency and market insights.

In 1923, Standard & Poor’s introduced the S&P Composite Index, a benchmark index that would later evolve into the iconic S&P 500. This index became a cornerstone of the financial industry, representing the performance of leading U.S. companies.

Throughout the 20th century, Standard & Poor’s expanded its offerings beyond indices, incorporating market intelligence services to provide comprehensive financial data and analytics to institutional investors, analysts, and businesses. In the early 2000s, Standard & Poor’s enhanced its global reach and capabilities through strategic acquisitions and partnerships. This period marked the integration of diverse datasets, analytics, and research services into a unified platform.

In 2016, Standard & Poor’s Financial Services LLC merged with McGraw Hill Financial, forming S&P Global Inc. This merger brought together a diverse portfolio of financial information services under the S&P Global brand. In 2018 they acquired Kensho, whose leading AI and machine learning capabilities drive actionable insights from very complex data.

In 2022, S&P Global and IHS Markit merge, leveraging complementary products to increase customer value and power the markets of the future. Today, S&P Global Market Intelligence remains committed to simplifying financial insights, offering a wide range of products and services that enable users to navigate complex markets with confidence. From earnings estimates to comprehensive coverage of asset classes, S&P Global’s history of innovation and dedication to excellence continues to shape the future of financial technology.

Key Components of S&P Global Market Intelligence

Earnings Estimates

S&P Global Market Intelligence aggregates consensus estimates from financial analysts covering a wide range of industries. Users could easily navigate through the most recent consensus and detailed estimates, revisions, guidance, multiples, surprises, trends, growth rates, and charts for fast and effective estimate tracking.

As of their platform, users seamlessly receive comprehensive global estimates straight into their systems, portals, and business applications through the company’s flexible Data Feed, Cloud, and API Solutions. With S&P Capital IQ Estimates, users can take advantage of historical and real-time consensus estimates, company guidance, analyst coverage, estimate revisions, and more to power their analysis and models.

Direct access and query S&P Capital IQ Estimates via Snowflake eliminates the data ingestion process and improves your productivity and efficiency.

Revenue Projections

S&P Global Market Intelligence delivers revenue projections on both a quarterly and annual basis. This allows investors to track short-term performance and long-term growth trends, offering a complete picture of a company’s revenue trajectory. We can rely on the latest information when we need it. Estimated revisions are updated intraday. Forecasted numbers are presented with point-in-time data.

Revenue projections are available across various sectors and industries, enabling users to conduct sector-specific analyses and comparisons. This helps investors understand industry trends and identify high-growth areas within the market. S&P Global Market Intelligence incorporates macroeconomic indicators into its revenue projections, such as GDP growth, inflation rates, and consumer spending patterns. This holistic approach ensures that revenue forecasts are grounded in broader economic realities.

Forecasts for Key Financial Metrics

Currently S&P Global is working on expanding its industry specific, segment and product level estimates. But its metrics already include general metrics (44), industry specific metrics for oil and gas, banks, insurances and REITs (Real Estate Investment Trust) and Commodity price targets.

Coverage

The S&P Market intelligence platform has a data coverage of over 15,000 banks, 13,257+ global insurance companies, properties across 101 countries with property data going back to 1995, Trucost’s deep environmental performance data on 15,000+ companies around the globe.

S&P Capital IQ Estimates are collected from broker research reports or from estimates feeds provided by the brokers directly. Their estimates data set does not include automated or computer generated estimates. The brokers in their network tend to be institutions and the estimates displayed on S&P Capital IQ Pro are collected from sell-side analyst estimates.

S&P Capital IQ Estimates capture “per share” estimates on the ticker/trading item level. If a user is not seeing all the contributors he/she expect for a company with multiple listings, the company recommends to check under the other listing(s). For example, Sony trades on TSE under 6758 and NYSE under SONY. They reflect the different estimates from analysts for the two trading items respectively. There is more estimates coverage for TSE:6758 compared to NYSE:SONY. The user may be looking at NYSE:SONY but expecting TSE:6758 coverage.

Period

The S&P Market intelligence historical data dates back to 1997 internationally and 1999 specifically for North American companies. The length of history varies based on metric.

Frequency

Their Data Feed Solution, Xpressfeed, paired with their proprietary loader technology, automates the download and management of data packages and enables delivery at any frequency.

The typical turnaround time is 2 hours for estimates (earnings, revenues, etc.), 1 hour for headlines, and 3 hours for guidance. For other vendors, the typical turnaround time is 24 hours, 12 hours and 12 hours (resepectively). This is one of the main qualities that differentiate S&P from other vendors.

Firms and Financial analysts

In a complicated world where one event triggers challenges for seemingly unrelated industries, S&P Global experts can provide market participants in-depth insights into the intersection of topics such as economics, shipping, automotive, commodities trading, oil and gas, financials, sustainability and more. S&P Global Market Intelligence provides high-quality industry data, financial data, news, analysis, and research to its client investors based on the client’s portfolio. Its clients include universities, corporations, government agencies, and investment professionals.

Pricing

Pricing depends on the scope of the usage regarding the following input factors:

Departments to be licensed (accessing the data)

Regions/locations that will have access to the data

Number of users that will have access to the data

Also for API / Datafeed solutions there are separate pricing guidelines, which depend on the amount of data items to be retrieved. This would need to be discussed with the business unit itself.

Use of S&P Global Market Intelligence by the Financial Community

Benchmark for Analysis

S&P Global Market Intelligence provides a vast array of financial metrics, including revenue, earnings, profit margins, and other key financial indicators. The platform offers tailored data for specific industries, enabling precise comparisons within sectors. This helps in understanding industry norms and identifying outliers. For instance, companies can benchmark their financial performance against the top players in their industry to identify strengths and weaknesses.

Market Expectations

S&P Global Market Intelligence plays a pivotal role in shaping and understanding market expectations. By aggregating analysts’ forecasts and market data, the platform helps users gauge investor sentiment and market trends. Key applications include Consensus Estimates, Market Sentiment Analysis and Trend Identification.

Earnings Season Preparation

During earnings season, S&P Global Market Intelligence is indispensable for preparation and analysis. Financial professionals use the platform to access earnings forecasts, historical performance data, and company reports, enabling them to anticipate results, post-earnings analysis and investor communications.

S&P Global Market Intelligence and Tests of Market Efficiency

Academic works

S&P fosters experiential learning with sustainability data and research that offer comprehensive data coverage, robust data linking, and flexible data delivery in the finance lab, student investment fund, research competition, and more. The platform also aids in identifying and analyzing market anomalies, contributing to the academic discourse on market efficiency. Researchers perform event studies to analyze how markets react to new information, such as earnings announcements or economic data releases.

Information Dissemination

S&P Global Market Intelligence excels in the rapid dissemination of financial information, ensuring that market participants have access to timely and accurate data. Real-time data, Custom Alerts and Comprehensive Coverage provided by the platform make it much easier to disseminate the information.

Pros and Cons

S&P Global Market Intelligence platform analysis helps investors evaluate the effectiveness of investment strategies and identify sources of outperformance or underperformance. It provides powerful analytical tools, real-time updates and comprehensive data.

On the other side, S&P Global Market Intelligence platform subscription costs can be high, potentially limiting access for smaller firms or individual investors. And the depth of information and tools available may require a learning curve for new users.

Conclusion

S&P Global Market Intelligence is a vital resource for the financial community, providing essential data, insights, and tools that support a wide range of financial activities. From benchmarking and market analysis to earnings season preparation and academic research, the platform empowers financial professionals to make informed decisions and stay ahead in a dynamic market environment.

Why should I be interested in this post?

Understanding how financial professionals use platforms like S&P Global Market Intelligence can contribute to your professional development, especially if you’re pursuing a career in finance, investment management, or financial advising. It demonstrates your interest in industry trends and best practices.

Useful resources

S&P Global The Market Intelligence Platform

Wikipedia S&P Global

S&P Global Estimates

S&P Global Data into insights

S&P Global Coverage and analytics

About the author

The article was written in May 2024 by Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management (MiM), 2021-2024).

Zacks Investment Research

May 30, 2024May 30, 2024 by Nithisha CHALLA

Zacks Investment Research

In this article, Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management (MiM), 2021-2024) presents Zacks Investment Research, which provides financial data, news and analytics for the financial community.

Introduction

Zacks Investment Research (ZIR) is a prominent financial services company known for its stock research, analysis, and investment tools. Zacks is best known for its proprietary Zacks Rank stock-rating system, which uses earnings estimate revisions to identify stocks that are assured to outperform the market. This system, along with a wide array of financial tools and resources, has made Zacks a trusted name among individual investors, financial advisors, and institutional investors alike.

Logo of Zacks Investment Research

Source: Zacks Investment Research

History

Zacks Investment Research has a rich history that began in 1978 when it was founded by Len Zacks, a Ph.D. in mathematics from MIT. Len Zacks was driven by a pioneering idea that earnings estimate revisions are the most powerful force impacting stock prices. His vision was to develop a research methodology and tools that leverage this insight to help investors make better investment decisions.

In 1978, Len Zacks founded Zacks Investment Research with a focus on earnings revisions. His research suggested that changes in analysts’ earnings estimates had a significant impact on stock prices, and he aimed to harness this insight to create a predictive stock-rating system.

In 1981, Zacks developed the Zacks Rank, a proprietary quantitative model that ranks stocks based on changes in analysts’ earnings estimates. It became the cornerstone of the company’s product offerings, known for its ability to identify stocks likely to outperform the market. In 1986, The Zacks Rank system was made available to institutional investors. It gained credibility and popularity due to its consistent performance in predicting stock price movements.

In 1992, Zacks Investment Research expanded its offerings to individual investors. In 1996, The company launched its website, Zacks.com, making its research and stock ratings accessible to a broader audience.

In 2002, Zacks introduced its mutual fund ranking system, applying its earnings revision methodology to mutual funds. This allowed investors to identify funds with strong earnings potential. In 2004, The company expanded its research offerings to include ETF (Exchange-Traded Fund) ratings and analysis, catering to the growing interest in ETF investing.

In 2015, Zacks Investment Research expanded its institutional services, offering advanced analytics, data feeds, and customized research solutions for hedge funds, asset managers, and financial institutions.

In 2023, Zacks Investment Research still remains a leading provider of financial research, known for its robust stock ranking system, comprehensive research reports, and a wide range of tools that help investors make informed decisions.

Key Components of Zacks Investment Research

Earnings Estimates

Zacks’ early contribution to investment analysis was the discovery that Earnings Per Share (EPS) estimate revisions are the most powerful force affecting stock prices. This discovery gave birth to the Zacks Indicator which, along with being the first to calculate consensus EPS estimates of quarterly earnings and to create the concept of EPS surprises, as well as the first to analyze price response to EPS surprises placed Zacks among the top innovating pioneers in the investment industry.

Zacks gathers earnings estimates from a wide range of sources like Wall Street Analysts, Company Reports, and Economic Indicators. Earnings estimates play a crucial role in the proprietary Zacks Rank system, which ranks stocks from top 5 strong buys to strong sells. The Zacks Rank system leverages these revisions to identify stocks that are likely to outperform or underperform the market.

Earnings estimates are a foundational element of the Zacks Rank system. The Zacks Rank is a proprietary stock rating model that uses changes in earnings estimates to rank stocks.

Model portfolio

The Zacks Investment Committee has maintained a model portfolio since 1996. This portfolio called the Zacks Focus List, is designed for long-term investors and reflects the opinions of Zacks Director of Research Mr. Sheraz Mian. It is published weekly and will list any additions or deletions to the portfolio from the previous week.

Zacks Chief Equity Strategist, John Blank PhD., publishes this monthly report that provides the Zacks forecasts for all major asset classes and the details of Zacks outlook. This report is derived from several resources to come up with individual asset class forecasts.

Forecasts for Key Financial Metrics

In the early 1990s, Zacks developed consensus estimates of other key investment metrics such as brokerage analyst stock ratings, forecasts of future sales, and target prices. More recently, Zacks have expanded again the set of items for which they calculate consensus estimates to include many of the line items and ratios that can be determined from income statements such as ROE, Margins, Net Income, etc.

The Zacks Fundamental database includes 260 operational metric items covering over 900 companies in 32 different industries. The history of the metrics items goes back to 2003. For more details on the operational metrics, download the overview document below.

Coverage

In 1981, Zacks began processing, organizing, and evaluating research produced by US brokerage firms. Today Zacks receives daily electronic data feeds and printed research reports on over 8,500 North American publicly traded companies from over 185 brokerage firms, produced by more than 3,200 analysts amounting to over 500,000 pages of brokerage research. Zacks’s extensive data sets give you access to over 25 years of data history on over 16,000 active and inactive US and Canadian equities.

In addition, ZIR records 25,000 earnings estimate revisions and changes in broker recommendations weekly. This information is made available through institutional and non-institutional product lines and websites such as MSN MoneyCentral, Quicken.com, Bloomberg.com, and FoxBusiness.com, as well as our websites.

On the whole it covers 6,000 US companies, plus 550 non-US companies traded as ADRs on US exchanges from 35 foreign countries, plus 200 Canadian companies trading on US exchanges.

Period

Zacks began in 1978 collecting the individual EPS estimates for over 4,400 US and Canadian companies made by 3,000 analysts employed by 180 US brokerage firms.

Frequency

Zacks maintains a history of annual EPS estimates going back to 1979 and quarterly estimates going back to 1982. Zacks consensus ratings history goes back to 1985. Consensus Sales estimates and Price Targets are maintained back to 2000.

Sales Estimates – 2000 to Present – Monthly, Weekly, Daily Frequency.

Price Targets – 2000 to Present – Monthly, Weekly, Daily Frequency

Zacks data is accessible through raw data feeds for both history files and updates, as hosted web pages that can be framed into finance-oriented websites, as APIs in XML or JSON format, and through partners providing on-demand data-as-a-service (DaaS) platforms.

Firms and Financial analysts

For the 3,800 largest companies Zacks provides over 500 fields of annual standardized data from 2001 forward, and 87 fields from 1979 to 2001. For the 2,800 smaller companies and ADRs, ZIR provide 87 fields of annual standardized data from 1979 to the present.

Zacks employs a rigorous quality control process to make sure all data points are recorded accurately. For each company, a trained analyst enters the data from SEC filings, which is then double-checked by a senior analyst. Once the data is entered, a senior analyst signs off on final completion after reviewing all the data. In addition, the data is subjected to a battery of automated checks to verify balancing relationships and correct errors. All data items are reviewed by multiple sets of trained eyes as well as automated computer checks.

Pricing

There are several types of pricing offered by Zacks Investment Research namely Zacks premium, Zacks Investor Collection, Zacks Ultimate.

Zacks Premium features daily updates of the Zacks Rank, full access to the Zacks #1 Rank List, Equity Research Reports, Focus List portfolio of 50 longer-term stocks, Premium screens and much more. The subscription fee for this per year is $249.

Zacks Investor Collection is a bundle of top subscription services for long-term investors. Customers can access to all of the real-time buy and sell signals from all of Zacks long-term investor portfolios, including the exclusive stocks under the $10 strategy which isn’t available to the general public. Customers can also get full access to all the premium research tools and reports for finding winning stocks, ETFs, and mutual funds. For this program they give access to all the data for $1 in the first 30 days and later prices at $59 per month and $495 per year.

Zacks Ultimate program gives customers access to Zacks’ market insights and the most private picks from Zacks portfolio recommendation services for only $1 in the first 30 days and later they price at $299 per month or $2,995 per year.

Use of Zacks Investment Research by the Financial Community

Benchmark for Analysis

Financial professionals often use Zacks Investment Research as a benchmark for analyzing stocks and making investment decisions. The company’s data and analytical tools provide a reliable foundation for comparative analysis. Investors use the Zacks Rank system to screen for stocks that are expected to outperform the market based on earnings estimate revisions.

According to the company website, it states that “The Zacks Mutual Fund Rank is a rating system that will help you find the best mutual funds to outperform the market. Use the Zacks Mutual Fund Rank to evaluate your current funds, find better funds, and track your funds. In addition, you can follow top-ranked funds featured in daily articles from Zacks’ team of analysts.” which shows how an investor can use their analyses as a benchmark.

Market Expectations

Zacks aggregates earnings estimates from multiple analysts to form a consensus estimate. By monitoring changes in earnings estimates, investors can understand shifts in market sentiment and expectations. Upward revisions typically indicate positive market sentiment, while downward revisions may signal potential concerns.

Zacks tracks earnings surprises, which occur when actual earnings differ significantly from consensus estimates. These surprises can lead to significant market movements and are closely watched by investors.

Earnings Season Preparation

Before earnings announcements, Zacks offers previews that include analysts’ expectations, historical earnings performance, and key factors to watch. After earnings reports are released, Zacks provides detailed analyses comparing actual results to estimates, offering insights into the implications for the company’s stock price and future performance.

Zacks Investment Research and Tests of Market Efficiency

Academic works

Zacks Investment Research is a valuable resource for academic researchers studying market efficiency and other financial theories. Researchers analyze how markets react to earnings announcements and other significant events, using Zacks’ data to test hypotheses about market efficiency.

Information Dissemination

Zacks Investment Research excels in providing up-to-date data and insights to its users. Zacks provides real-time updates on earnings estimates, stock ratings, and market news. Users can set up custom alerts for specific stocks or market events.

Zacks research and data are accessible through various platforms, including its website, mobile apps, and third-party financial services, making it easy for users to stay informed.

Pros and Cons

The Zacks Rank system and earnings estimates are known for their accuracy in predicting stock performance. Zacks offers extensive and detailed financial data, covering a wide range of companies and metrics.

On the other side, Zacks’ premium services can be expensive, potentially limiting access for smaller firms or individual investors. And the depth of information and tools available may require a learning curve for new users.

Conclusion

Zacks offers a wealth of data and analysis that helps in making informed investment decisions. By focusing on earnings estimates and revisions, Zacks helps investors predict stock performance more accurately. The user-friendly tools and real-time updates make it accessible for both beginners and experienced investors.

Why should I be interested in this post?

For management students, understanding and utilizing tools like Zacks Investment Research can provide a significant edge in the financial world. Learning to use such resources effectively can enhance our analytical skills and prepare us for a successful career in finance and investment management.

Useful resources

Zacks Investment Research Zacks Fundamental Data – Company Profile and Financial Statement Data

Zacks Investment Research Our Research. Your Success.

Fidelity Research Firm: Zacks Investment Research

Zacks Investment Research Find the Service That’s Right For You

Zacks Investment Research Zacks Mutual Fund Rank

About the author

The article was written in May 2024 by Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management (MiM), 2021-2024).

Structured Debt in Private Equity: Rated Feeder Funds and Collateral Fund Obligations

April 17, 2025May 22, 2024 by Dante MARRAMIERO

Structured Debt in Private Equity: Rated Feeder Funds and Collateral Fund Obligations

In this article, Dante MARRAMIERO (ESSEC Business School, Master in Strategy and Management of International Business (SMIB), 2022-2023) explains structured debt in Private Equity: Rated Feeder Funds and Collateral Fund Obligations. Such debt products open the market for insurance companies.

Structured Financing for Investment

In the intricate world of finance, innovative structures continually emerge to meet investor demands under the current regulatory framework. Among these structures are Rated Feeder Funds (RNFs) and Collateralized Fund Obligations (CFOs), which facilitate investments for investors with specific investment criteria. This happens particularly with insurance companies and asset managers, to access private equity or alternative strategy funds such as growth funds or private credit funds through rated debt instruments. However, structures like RNFs and CFOs are not without their complexities and regulatory scrutiny, especially in light of historical parallels to Collateralized Debt Obligations (CDOs) and the financial crisis of 2008. CFOs and CDOs have exactly the same structure but have different underlying assets: CDOs are based on debt, specifically mortgages while CFOs are based on Private Equity funds.

The two figures below represent the financial structure of RNFs and CFOs.

Figure 1. Financial structure of an RNF.

Source: the author.

Figure 2. Financial structure of a CFO.

Source: the author.

Rated Feeder Funds (RNFs) and Collateral Fund Obligations (CFOs) thus represent innovative approaches to structured financing, aiming to bridge the gap between investors and private equity or alternative strategy funds.

Why are CFOs and RNFs attracting insurance companies?

CFOs and RNFs are both characterized by a blend of debt and equity components. These vehicles raise capital by issuing debt securities, which are then used to invest in a diversified portfolio of assets across multiple funds. The presence of both debt and equity elements not only provides investors with exposure to various underlying assets (in which the various funds have invested) but also introduces a diversification effect that can attract capital seeking lower risk profiles. The debt issued by CFOs typically undergoes scrutiny by rating agencies to determine their creditworthiness, thereby providing assurance to investors regarding the quality of the investment.

On the other hand, RNFs operate through a structure where investors’ capital is channeled through a special purpose vehicle (SPV) or feeder fund. This feeder fund then invests in a master fund managed by the sponsor. This setup allows investors to gain exposure to the underlying assets of the master fund without directly participating in its operations. RNFs, similar to CFOs, offer rated debt instruments to investors, providing them with a regulated and transparent avenue to access private fund investments.

Regulatory Considerations and Risk Mitigation

One of the key attractions of RNFs and CFOs is the regulatory capital treatment they offer to institutional investors. By investing through rated debt instruments, regulated institutions such as insurance companies can benefit from reduced capital requirements compared to direct equity investments in underlying funds.

However, regulatory scrutiny is a critical aspect of these structures, particularly in jurisdictions like the United States and Europe. In the US, concerns have been raised regarding the applicability of risk retention rules, especially in CFO transactions where repayment primarily depends on limited partnership interests. Similarly, European regulations such as the UK and EU Securitization Regulations impose stringent requirements.

In the US, currently, the NAIC – National Association of Insurance Commissioners has blocked investments from insurance companies in CFOs but is working on possible ways to regulate the market and open the investment again in the future.

Conclusion: Balancing Innovation with Regulatory Compliance

Rated Feeder Funds (RNFs) and Collateral Fund Obligations (CFOs) represent innovative solutions for investors seeking exposure to private funds while optimizing regulatory capital requirements. However, their structural complexities and regulatory scrutiny, particularly in the aftermath of the 2008 financial crisis, underscore the importance of due diligence and compliance.

As financial markets evolve, the challenge lies in striking a balance between innovation and regulatory compliance. While RNFs and CFOs offer opportunities for capital efficiency and investment diversification, they must navigate a complex regulatory landscape to ensure stability and mitigate systemic risks. Only through careful consideration of lessons from history and adherence to regulatory guidelines can these structured financing solutions fulfill their promise in the modern financial ecosystem.

Example of precedent transaction: Tikehau raise a $300 million CFO

Tikehau Capital has raised $300 million collateralized fund obligation backed by cashflows from commitments to its direct lending and private debt secondary strategies. The CFO’s assets consisted of interests in Tikehau’s own debt funds as well as third-party managed private debt funds originated by the firm’s private debt secondaries strategy, according to a statement from Jefferies, which advised on the transaction.

Specifically, the CFO assets were largely Tikehau-managed funds: the direct lending and private debt secondaries which were held on the firm’s balance sheet. This transaction allowed Tikehau to raise capital from the big American insurance companies that otherwise would have considered investing in Tikehau’s funds as out of scope.

Why should I be interested in this post?

This post could be particularly intriguing for business students because it highlights diverse methods of fundraising within the private equity sector. This knowledge could benefit students aiming for careers in finance and those seeking to secure funding for their own ventures. Moreover, it provides valuable insights into the pivotal role that debt plays in financing strategies. Furthermore, it could be a good competitive advantage during Private Equity interviews to know about structured finance as it is an emerging topic in the Private Equity industry and not everyone is up to date with it!

Useful resources

Hanson R. (08/11/2023) Collateralised fund obligations and rated note feeders: options for structuring investment into private funds Morgan Lewis

Cadwalader Brief Primer on CFOs and Rated Feeder Funds

About the author

The article was written in May 2024 by Dante MARRAMIERO (ESSEC Business School, Master in Strategy and Management of International Business (SMIB), 2022-2023).

Private Equity and Italy, is it a nice combination?

May 22, 2024May 19, 2024 by Dante MARRAMIERO

Private Equity and Italy, is it a nice combination?

In this article, Dante MARRAMIERO (ESSEC Business School, Master in Strategy and Management of International Business (SMIB), 2022-2024) explains about the peculiar situation of the Italian Private Equity market.

Italian conservative market is now opening up

Italy’s family-owned enterprises, steeped in tradition yet poised for transformation, stand at a crossroads of opportunity. For decades, these businesses have been the backbone of the country’s economy, rooted in principles of heritage and resilience. Yet, as the global marketplace evolves, so too must they. Enter private equity – once a distant concept, now a beacon of possibility, offering two distinct paths for growth: co-investment and external capital infusion.

As previously mentioned, family businesses dominate the Italian economy, with around 784,000 companies (nearly 85%) being family-owned according to AIDAF, the Italian Association of Family Businesses. These small and medium-sized enterprises are mainly active in sectors like fashion, mechanical engineering, and food, producing high-quality “Made in Italy” products.

One driver for ownership changes in Italian family businesses is succession planning, as many seek external capital to finance growth, international expansion, technology investments or innovations due to being undercapitalized. Private equity funds have stepped in to provide this capital, with Italy being one of Europe’s most mature private equity markets. As a confirmation of this, annual private equity investments in Italy correspond to around 0.36% of GDP, on par with Germany but lower than the UK, Netherlands, and France.

Key target sectors for Italian private equity include IT/communications and industrial goods. Around 14% of Italian family office assets are invested in private equity, with surveys suggesting most intend to increase these allocations. What could make the difference for the future is that younger generations of Italian wealth holders are expected to further drive family office investments into private equity and venture capital, being more interested in backing early-stage businesses, especially in technology. Their international outlook and experience abroad are also influencing asset allocation decisions.

Co-Investment: Fostering Collaboration for Shared Success

Traditionally, family businesses have been hesitant to engage with private equity, wary of relinquishing control and diluting their legacy. However, a paradigm shift is underway as a new wave of private equity firms sets its sights on these familial enterprises, offering tailored solutions to suit their diverse needs.

Co-investment, as mentioned earlier, represents one avenue for growth. Through co-investment, family businesses can partner with private equity firms to pursue inorganic growth opportunities while retaining operational control. This collaborative approach allows for shared risk and rewards, leveraging the strengths of both parties to unlock new synergies and market opportunities.

External Capital Infusion: Embracing Change for Accelerated Growth

Yet, co-investment is not the only path forward. Another emerging trend in Italy’s business landscape is the willingness of family businesses to open their doors to external capital funding, including partial divestment to private equity firms. While this option may involve ceding a degree of ownership and autonomy, it also presents an opportunity to access significant capital infusion and strategic guidance.

The decision between co-investment and external capital infusion is not a one-size-fits-all proposition. Each option carries its own set of benefits and considerations, depending on the unique circumstances and aspirations of the family business in question. Some may find co-investment to be a more palatable approach, allowing them to maintain a greater degree of control over their operations. Others may see external capital infusion as a means to accelerate growth and access new markets.

The Role of Family Offices

Integral to navigating these choices is the role of the family office – a trusted advisor tasked with safeguarding the financial interests of affluent families. Whether pursuing co-investment or external capital infusion, family offices play a crucial role in guiding decision-making and ensuring alignment with long-term goals.

As Italy’s family businesses chart a course toward the future, the convergence of private equity and family offices offers a wealth of opportunities for growth and revitalization. By embracing both co-investment and external capital infusion, these enterprises can leverage the strengths of private equity partnerships while preserving their unique identities and legacies.

Conclusion: Two Paths, One Destination

In conclusion, the dual paths of co-investment and external capital infusion represent two sides of the same coin for Italy’s family businesses. By carefully weighing the options and leveraging the expertise of family offices, these enterprises can navigate the complexities of modern business and chart a course towards sustainable success in an ever-changing world.

Why should I be interested in this post?

This post presents a valuable opportunity to better understand the unique characteristics of the Italian market, predominantly driven by family businesses, and to explore its evolving landscape as it embraces a new business paradigm: Private Equity. Studying this transition offers insights not only for academic enrichment but also for future career prospects in Private Equity. Understanding how Italy’s traditional family business-dominated market is adapting to and integrating Private Equity opens doors for both educational exploration and potential professional paths in this sector.

Useful resources

Bocconi Student Private Equity Club (2024) Overview: The Private Equity Market in Italy over the last 20 years

Deutsche Bateiligungus AG (2023) Private equity in Italy – an undervalued market

FamilyCapital (2020) The big private equity groups backed by families

AltiGlobal (2023) Italy’s next generation of wealth holders step up to grow family wealth while they wait for senior leadership roles

About the author

The article was written in May 2024 by Dante MARRAMIERO (ESSEC Business School, Master in Strategy and Management of International Business (SMIB), 2022-2024)

The selling process of funds

May 11, 2024 by David-Alexandre BLUM

The selling process of funds

In this article, David-Alexandre BLUM (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2019-2023) explains about the selling process of funds.

The process of selling a fund involves several key steps and stakeholders. The fund is built by management teams that develop the strategy, allocation, and follow the macroeconomic scenario of economists. Let’s take the example of Lazard Frères Gestion.

Lazard Frères Gestion is characterized by active management based on fundamental analysis. Financial analysis and knowledge of companies are at the heart of the management process. All institutional management relies on the same macroeconomic scenario. Financial assets are the major source of financing for the real economy. The economy is cyclical. Financial assets are also cyclical. Volatility or bubble effects can cause the market price of an asset to diverge from its fair economic price in the short term, but not in the long term. Over time, it is the ability to capture the different phases of the cycle that creates outperformance.

Lazard Frères Gestion’s investment philosophy is based on both reading the economic cycle and evaluating companies. When products are launched and marketable, the distribution team prospects new clients (through seminars, contacts, or research), responds to tenders, or meets specific client requests.

The client meeting

Once the initial contact has been made, the sales team must prepare a specialized presentation for clients, gathering necessary documents (such as reports, management points, comparative studies, etc.). The preparation of such a presentation is crucial and should not be overlooked. It is important to choose the right arguments to highlight, taking into account the current economic environment and supporting the scenario put forward by the management team.

Selling a fund requires a thorough understanding of the management process, portfolio values, managers’ philosophy, as well as the benchmark performance and various risk and performance indicators of the presented fund.

Once the speech is prepared and the materials finalized, it is up to the seller to showcase the fund’s qualities. If the meeting goes well and negotiations are successful, the transaction can follow quickly or the client may request an entirely different service, such as a dedicated fund (customized fund), if it meets the criteria for accessing the service.

The team then needs to manage the contractual and administrative aspects to finalize the operation. The potential buyer conducts thorough due diligence on the fund, examining financial documents, contracts, internal procedures, and regulatory compliance to ensure there are no hidden issues or unforeseen risks.

Once due diligence is completed and the terms of the transaction are finalized, the parties draft and sign the sales contracts. In addition, they obtain the necessary approvals from the relevant regulatory authorities to transfer the fund’s management to the buyer.

After obtaining regulatory approvals, the client transfers the fund’s assets and liabilities to the buyer. This may include transferring securities, contracts with custodians and fund administrators, as well as communicating with the concerned investors.

Once the transfer is completed, the buyer integrates the fund into their own management structure and takes over the daily management of the fund, ensuring that investment objectives and applicable regulations are met.

Managing the relationship and the customer service

The team’s work does not stop at mere sales. Its role is much more important. It must ensure the proper receipt of financial and legal documents sent to clients periodically. It must also respond to all information requests about the subscribed products and ensure that the services subscribed by the client are performed. It is their duty to do everything possible to justify any underperformance and to nourish the relationship with information and explanations. To do this, they attend various committees and internal meetings to keep abreast of different movements and tactical bets. The sales team can encourage its client to invest more in its product and propose new products that seem to meet the client’s demand. In the event that the client chooses to withdraw from the fund, the relationship does not end there, and it is up to the sales team to work to potentially bring their client back.

From a technical standpoint, the sales team must master the knowledge of its products. The sales team must deeply understand the characteristics of the fund, including investment strategy, objectives, underlying assets, sectoral and geographical allocation, as well as fees and associated costs.

It is essential to know the historical performance of the fund, risk-adjusted returns (such as the Sharpe ratio), and comparisons with benchmark indices or similar funds. The sales team must be able to explain the main risks associated with the fund, such as market, credit, liquidity, and currency risks, as well as the measures taken by the fund manager to mitigate these risks.

Knowledge of regulations applicable to investment funds, such as UCITS or AIFMD directives in Europe, and disclosure and reporting requirements, is crucial to ensure compliance and client trust.

The sales team must be able to identify target investors for the fund, taking into account their risk profile, investment objectives, and liquidity needs.

Team members must master the procedures for subscribing and redeeming fund shares, including deadlines, fees, and specific conditions.

Communication and presentation: Communication and presentation skills are essential for clearly and convincingly explaining the benefits of the fund and addressing potential clients’ questions.

By mastering these technical aspects, the sales team will be able to effectively present the investment fund to potential clients, address their concerns, and assist them in making informed investment decisions.

Why should I be interested in this post?

The sales process of a fund helps to better understand the functioning of the investment fund market and the dynamics between asset management companies, investors, and financial intermediaries.

Investors who understand the sales process of a fund are better equipped to evaluate fund offerings and make informed investment decisions based on their objectives and risk tolerance. Professionals working or considering working in the financial industry, particularly in the areas of asset management, sales, and investment advisory, will benefit from a deep understanding of the fund sales process to enhance their skills and professional performance.

Furthermore, understanding the sales process of a fund can assist investors and financial advisors in comparing different investment products, such as mutual funds, exchange-traded funds (ETFs), and alternative investment funds, to determine the best solution for their specific needs and objectives.

Useful resources

Lazard Frères Gestion

Lazard Frères Gestion Les métiers de la gestion d’actifs (webinaire)

Lazard Frères Gestion Qu’est-ce que la gestion d’actifs ?

Lazard Frères Gestion Quelle allocation d’actifs pour un portefeuille diversifié ?

Hull J., P. Roger (2017) Options futures et autres actifs dérivés Pearson Education.

About the author

The article was written in May 2024 by David-Alexandre BLUM (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2019-2023).

Cardano: Exploring the Future of Blockchain Technology

May 29, 2025May 6, 2024 by Snehasish CHINARA

In this article, Snehasish CHINARA (ESSEC Business School, Grande Ecole Program – Master in Management, 2022-2024) explains the cryptocurrency Cardano.

Historical context and background

Cardano is a blockchain platform that was founded in 2017 by Charles Hoskinson, one of the co-founders of Ethereum. The project was initiated by Input Output Hong Kong (IOHK), a technology company focused on blockchain and cryptocurrency. Cardano’s development was guided by a scientific philosophy and peer-reviewed research, aiming to create a more scalable, sustainable, and interoperable blockchain platform. Cardano is named after Gerolamo Cardano, the Italian mathematician, whereas the cryptocurrency associated with the platform is named after Ada Lovelace, the English mathematician.

Cardano distinguishes itself through its layered architecture, which separates the platform’s settlement layer (Cardano Settlement Layer, CSL) from its computation layer (Cardano Computation Layer, CCL). This separation allows for greater flexibility and scalability, as well as easier implementation of updates and improvements.

Another notable feature of Cardano is its consensus mechanism, called Ouroboros, which is based on a proof-of-stake algorithm. Ouroboros aims to achieve both security and scalability by allowing users to participate in the consensus process based on the amount of cryptocurrency they hold, rather than requiring expensive computational resources like Bitcoin’s proof-of-work mechanism.

Cardano’s development has been divided into phases, each focusing on different aspects of the platform’s functionality and features. These phases include Byron (foundation), Shelley (decentralization), Goguen (smart contracts), Basho (scaling), and Voltaire (governance). As of the time of writing, Cardano has successfully completed the Byron and Shelley phases, with ongoing work on the Goguen phase, which will enable the implementation of smart contracts and decentralized applications (dApps) on the platform.

Cardano Logo

Source: Cardano.

Figure 1. Key Dates in Cardano History

Source: Yahoo! Finance.

Key features

Layered Architecture

Cardano’s architecture is divided into two layers – the Cardano Settlement Layer (CSL) and the Cardano Computation Layer (CCL). This separation allows for greater flexibility, scalability, and easier implementation of updates and improvements.

Ouroboros Consensus Protocol:

Cardano uses the Ouroboros proof-of-stake consensus algorithm, which is designed to be secure, scalable, and energy-efficient. It allows users to participate in the consensus process based on the amount of cryptocurrency they hold, rather than requiring expensive computational resources.

Scalability

Cardano is designed to be highly scalable, capable of handling a large number of transactions per second. Through its layered architecture and consensus mechanism, Cardano aims to achieve scalability without sacrificing security or decentralization.

Interoperability

Cardano aims to enable interoperability between different blockchain networks and protocols. This will allow for seamless transfer of assets and data between different platforms, facilitating greater connectivity and usability of decentralized applications (dApps).

Smart Contracts

Cardano is developing support for smart contracts, which are self-executing contracts with the terms of the agreement directly written into code. Smart contracts will enable the creation of decentralized applications (dApps) on the Cardano platform, opening up a wide range of possibilities for developers and users.

Governance

Cardano has a built-in governance mechanism that allows stakeholders to participate in the decision-making process for the future development of the platform. This includes voting on proposals for protocol upgrades, funding development projects, and other governance-related decisions.

Formal Verification

Cardano emphasizes formal methods and peer-reviewed research in its development process. This includes using formal verification techniques to ensure the correctness and security of its protocols and smart contracts, reducing the risk of bugs and vulnerabilities.

Use cases

Decentralized Finance (DeFi)

Cardano’s smart contract capabilities can facilitate various DeFi applications, including decentralized exchanges (DEXs), lending platforms, stablecoins, and automated market makers (AMMs). Smart contracts on Cardano can enable programmable financial transactions without the need for intermediaries, providing users with greater control over their assets and reducing counterparty risk.

Supply Chain Management

Cardano’s blockchain can be utilized to track and authenticate products throughout the supply chain, ensuring transparency and accountability. By recording every step of a product’s journey on the blockchain, stakeholders can verify its origin, quality, and authenticity, thereby reducing fraud, counterfeiting, and logistical inefficiencies.

Identity Management

Cardano’s blockchain can serve as a secure and decentralized platform for identity management, enabling individuals to control and manage their digital identities without relying on centralized authorities. By leveraging cryptographic techniques, users can securely authenticate themselves and access various services, such as voting, healthcare, and financial transactions, while maintaining privacy and security.

Voting and Governance

Cardano’s blockchain can support transparent and tamper-resistant voting and governance systems, enabling communities to make collective decisions and govern decentralized organizations (DAOs). By using blockchain technology, voting processes can be made more secure, efficient, and auditable, ensuring fair and democratic outcomes.

Tokenization of Assets

Cardano’s blockchain can tokenize various real-world assets, such as real estate, stocks, and commodities, making them easily tradable and transferable on a global scale. By representing assets as digital tokens on the blockchain, ownership rights can be easily verified, fractional ownership can be enabled, and liquidity can be increased, unlocking new opportunities for investment and asset management.

Technology and Underlying Blockchain

Cardano is built on a multi-layered architecture designed to provide scalability, interoperability, and sustainability. At its core, Cardano utilizes a proof-of-stake (PoS) consensus mechanism called Ouroboros, which offers a more energy-efficient and secure alternative to traditional proof-of-work (PoW) systems. Ouroboros divides time into epochs and slots, with slot leaders responsible for creating new blocks and validating transactions within each slot. This approach ensures that the blockchain remains secure and decentralized while enabling high transaction throughput and low latency.

Cardano’s blockchain consists of two main layers: the Cardano Settlement Layer (CSL) and the Cardano Computation Layer (CCL). The CSL serves as the foundation for the platform’s native cryptocurrency, ADA, and facilitates secure and efficient peer-to-peer transactions. It employs a UTXO (Unspent Transaction Output) model similar to Bitcoin, where transactions are represented as inputs and outputs, ensuring transparency and immutability.

On top of the CSL, the CCL enables the execution of smart contracts and decentralized applications (dApps) using Plutus, Cardano’s purpose-built programming language. Plutus is based on Haskell, a functional programming language known for its safety and reliability, and allows developers to write smart contracts with formal verification capabilities, ensuring correctness and security. Additionally, Cardano supports interoperability with other blockchains through sidechains and cross-chain communication protocols, enabling seamless integration with existing infrastructure and networks.

Cardano’s development is guided by a rigorous scientific approach, with ongoing research and peer-reviewed papers driving innovation and advancement. The platform’s roadmap is divided into distinct phases, including Byron (foundation), Shelley (decentralization), Goguen (smart contracts), Basho (scaling), and Voltaire (governance), each focusing on specific features and functionalities. This modular approach allows for continuous improvement and evolution, ensuring that Cardano remains at the forefront of blockchain technology.

Supply of Coins

The supply of coins for Cardano (ADA) is governed by a predetermined protocol established during its initial launch. The total maximum supply of ADA is capped at 45 billion coins. Unlike some cryptocurrencies that have fixed supplies, Cardano’s distribution occurs gradually through a process called “minting.” During the initial phase, ADA tokens were distributed through a public sale and allocated to early supporters, development, and the Cardano treasury. Ongoing minting of ADA occurs through the process of staking, where ADA holders can delegate their coins to stake pools to participate in the network’s consensus and earn rewards. This incentivizes stakeholders to actively participate in the security and governance of the network while also distributing newly minted coins in a decentralized manner. As a result, the circulating supply of ADA gradually increases over time, with new coins being minted and distributed to participants in the Cardano ecosystem.

Historical data for Cardano

How to get the data?

The Cordano is popular cryptocurrency on the market, and historical data for the Cordano such as prices and volume traded can be easily downloaded from the internet sources such as Yahoo! Finance, Blockchain.com & CoinMarketCap. For example, you can download data for Cardano on Yahoo! Finance (the Yahoo! code for Cardano is ADA-USD).

Figure 2. Cordano data

Source: Yahoo! Finance.

Historical data for the Cardano (ADA) market prices

Cardano (ADA) has experienced notable fluctuations in its market price since its inception, reflecting both broader trends in the cryptocurrency market and developments specific to the Cardano project. Following its launch in 2017, ADA initially saw rapid growth, fueled by enthusiasm for its innovative technology and ambitious roadmap. However, like many cryptocurrencies, ADA’s price has been subject to volatility, with periods of sharp appreciation followed by corrections and consolidation. Historical data for Cardano’s market prices reveals a series of peaks and troughs, influenced by factors such as market sentiment, regulatory developments, technological milestones, and macroeconomic trends. Despite this volatility, Cardano has maintained its position as one of the top cryptocurrencies by market capitalization, attracting a dedicated community of supporters and investors. As the project continues to evolve and achieve key milestones, its market price remains closely watched by traders, investors, and stakeholders in the cryptocurrency ecosystem.

Figure 3 below represents the evolution of the price of Cardano (ADA) in US dollar over the period November 2017 – May 2024. The price corresponds to the “closing” price (observed at 10:00 PM CET at the end of the month).

Figure 3. Evolution of Cardano price

Source: Yahoo! Finance.

R program

The R program below written by Shengyu ZHENG allows you to download the data from Yahoo! Finance website and to compute summary statistics and risk measures about the Cardano (ADA).

Data file

The R program that you can download above allows you to download the data for the Cardano (ADA) from the Yahoo! Finance website. The database starts on November, 2017.

Table 1 below represents the top of the data file for the Cardano (ADA) downloaded from the Yahoo! Finance website with the R program.

Table 1. Top of the data file for the Cardano

Source: computation by the author (data: Yahoo! Finance website).

Python code

You can download the Python code used to download the data from Yahoo! Finance.

Python script to download Cardano (ADA) historical data and save it to an Excel sheet::

import yfinance as yf

import pandas as pd

# Define the ticker symbol for Cardano “ADA-USD”

Cardano_ticker = “ADA-USD”

# Define the date range for historical data

start_date = “2020-01-01”

end_date = “2022-01-01”

# Download historical data using yfinance

Cardano_data = yf.download(Cardano_ticker, start=start_date, end=end_date)

# Create a Pandas DataFrame from the downloaded data

Cardano_df = pd.DataFrame(Cardano_data)

# Define the Excel file path

excel_file_path = “Cardano _historical_data.xlsx”

# Save the data to an Excel sheet

Cardano_df.to_excel(excel_file_path, sheet_name=”Cardano Historical Data”)

print(f”Data saved to {excel_file_path}”)

# Make sure you have the required libraries installed and adjust the “start_date” and “end_date” variables to the desired date range for the historical data you want to download.

Evolution of the Cardano (ADA)

Figure 4 below gives the evolution of the Cardano (ADA) on a daily basis.

Figure 4. Evolution of the Cardano (ADA)

Source: computation by the author (data: Yahoo! Finance website).

Figure 5 below gives the evolution of the Cardano (ADA) returns from November, 2017 to May, 2024 on a daily basis.

Figure 5. Evolution of the Cardano returns

Source: computation by the author (data: Yahoo! Finance website).

Summary statistics for the Cardano (ADA)

The R program that you can download above also allows you to compute summary statistics about the returns of the Cardano (ADA).

Table 2 below presents the following summary statistics estimated for the Cardano (ADA):

The mean

The standard deviation (the squared root of the variance)

The skewness

The kurtosis.

The mean, the standard deviation / variance, the skewness, and the kurtosis refer to the first, second, third and fourth moments of statistical distribution of returns respectively.

Table 2. Summary statistics for Cardano.

Source: computation by the author (data: Yahoo! Finance website).

Statistical distribution of the Cardano (ADA) returns

Historical distribution

Figure 6 represents the historical distribution of the Cardano (ADA) daily returns for the period from November, 2017 to May, 2024.

Figure 6. Historical Cardano distribution of the returns.

Source: computation by the author (data: Yahoo! Finance website).

Gaussian distribution

The Gaussian distribution (also called the normal distribution) is a parametric distribution with two parameters: the mean and the standard deviation of returns. We estimated these two parameters over the period from November, 2017 to May, 2024.

Figure 7 below represents the Gaussian distribution of the Ethereum daily returns with parameters estimated over the period from November, 2017 to May, 2024.

Figure 7. Gaussian distribution of the Cardano returns.

Source: computation by the author (data: Yahoo! Finance website).

Risk measures of the Cardano (ADA) returns

The R program that you can download above also allows you to compute risk measures about the returns of the Cardano (ADA).

Table 3 below presents the following risk measures estimated for the Cardano (ADA):

The long-term volatility (the unconditional standard deviation estimated over the entire period)

The short-term volatility (the standard deviation estimated over the last three months)

The Value at Risk (VaR) for the left tail (the 5% quantile of the historical distribution)

The Value at Risk (VaR) for the right tail (the 95% quantile of the historical distribution)

The Expected Shortfall (ES) for the left tail (the average loss over the 5% quantile of the historical distribution)

The Expected Shortfall (ES) for the right tail (the average loss over the 95% quantile of the historical distribution)

The Stress Value (SV) for the left tail (the 1% quantile of the tail distribution estimated with a Generalized Pareto distribution)

The Stress Value (SV) for the right tail (the 99% quantile of the tail distribution estimated with a Generalized Pareto distribution)

Table 3. Risk measures for the Cardano.

Source: computation by the author (data: Yahoo! Finance website).

The volatility is a global measure of risk as it considers all the returns. The Value at Risk (VaR), Expected Shortfall (ES) and Stress Value (SV) are local measures of risk as they focus on the tails of the distribution. The study of the left tail is relevant for an investor holding a long position in the Cardano(ADA) while the study of the right tail is relevant for an investor holding a short position in the Cardano(ADA).

Why should I be interested in this post?

This post provides a compelling exploration of Cardano, catering to both novices and seasoned cryptocurrency enthusiasts alike. It delves into Cardano’s innovative blockchain technology and its role in revolutionizing various sectors, including finance, governance, and social impact initiatives. By understanding Cardano’s layered architecture, consensus mechanism, and ongoing development phases, readers can gain valuable insights into its potential to address scalability, interoperability, and sustainability challenges in the blockchain space. Moreover, the post examines Cardano’s historical performance, market dynamics, and community-driven governance model, offering invaluable perspectives for investors, traders, and stakeholders. Whether you’re intrigued by cutting-edge blockchain solutions or seeking investment opportunities in the cryptocurrency market, this post provides comprehensive insights into the significance and potential of Cardano in shaping the future of decentralized technologies.

Useful resources

Academic research about risk

Longin F. (2000) From VaR to stress testing: the extreme value approach Journal of Banking and Finance, N°24, pp 1097-1130.

Longin F. (2016) Extreme events in finance: a handbook of extreme value theory and its applications Wiley Editions.

Data

Yahoo! Finance

Yahoo! Finance Historical data for Cardano

CoinMarketCap Historical data for Cardano

About the author

The article was written in March 2024 by Snehasish CHINARA (ESSEC Business School, Grande Ecole Program – Master in Management, 2022-2024).

Bloomberg

May 20, 2024May 3, 2024 by Nithisha CHALLA

Bloomberg

In this article, Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management (MiM), 2021-2024) presents Bloomberg, which provides financial data, news and analytics for the financial community.

Bloomberg

Bloomberg is a company that provides financial data, news, and analytics to people in finance and other industries. The company was created to address the need for better financial data and analytics access in the business world. Bloomberg’s flagship product is the Bloomberg Terminal, a computer software system that provides real-time data on financial markets, economic indicators, and news.

Logo of Bloomberg

Source: Bloomberg

History

Bloomberg LP was founded in 1981 by Michael Bloomberg, a former investment banker who recognized the growing demand for reliable financial information and analytics. The company initially focused on developing and selling computer terminals that provided real-time data on stocks, bonds, and other financial instruments.

Bloomberg’s key innovation, Bloomberg Terminal, was introduced in the early 1980s. This groundbreaking platform revolutionized the way financial professionals accessed market data and news, offering a comprehensive toolset for trading, analysis, and research.

Over the years, Bloomberg expanded its offerings beyond terminals to include data analytics, financial software, and media services. Bloomberg News, launched in 1990, became a prominent source of business and financial journalism, providing timely news coverage and insightful analysis to subscribers worldwide.

In the 21st century, Bloomberg continued to innovate and diversify its business, introducing new products and services tailored to the evolving needs of the financial industry. The company expanded its global presence with offices in major financial centers across North America, Europe, Asia, and beyond.

Today, the company’s commitment to innovation, integrity, and excellence has solidified its position as a trusted partner for businesses, governments, and institutions seeking reliable financial information and insights.

Bloomberg has evolved since its introduction in 1981 and has grown the company from a single location to 176 locations and with 20000 employees. Bloomberg with over 40 years of history, facilitates bottom-up and top-down analysis to better assess potential growth and risk as well as future value across industry, sector, index, country, and region.

Bloomberg covers a wide range of firms across different industries, sectors, and regions. According to Chen (2023), Bloomberg grew to a leading financial company with over 325,000 subscriptions to its professional services, almost 1 million global circulations of Bloomberg Businessweek, and over 150 news bureaus internationally. To support this massive network of financial information, data encryption, messaging, and trading, Bloomberg employs over 4,000 computer engineers around the globe.

Key Components of Bloomberg

Earnings Estimates

Bloomberg provides estimates and forecasts about how companies will perform financially. It collects data from many sources and use it to predict things like earnings and revenue for different businesses.

According to Guttmann from Statista (2022), Bloomberg LP, which operates within the business of information services, news services, broadcasting, streaming, and print, generated an estimated 12.2 billion U.S. dollars. A year earlier, the company’s revenue results stood at 10 billion dollars.

Revenue Projections

Alongside earnings estimates, Bloomberg provides forecasts on how much revenue companies are expected to generate. This helps stakeholders analyze and project the growth and performance of businesses over specific periods.

For example, on June 01, 2023, Bloomberg Intelligence released an expected revenue projection on the AI industry for the next ten years stating “Rising demand for generative AI products could add about $280 billion of new software revenue and the Emerging Industry Could Grow at a CAGR of 42% Over the Next 10 Years”. This helps stakeholders of the respective industry to analyze, project, and invest accordingly.

Forecasts for Key Financial Metrics

Bloomberg’s platform includes forecasts for various important financial metrics beyond earnings and revenue, such as cash flow, profit margins, and growth rates. These forecasts assist in assessing the overall financial health and prospects of companies.

In April 2024, Bloomberg launched a point-in-time data solution that gives quants a competitive edge. By pre-ingesting, mapping, and linking many different data sources together, Bloomberg allows customers to significantly reduce the time needed to generate signals or insights. With this launch, Bloomberg is responding to customers’ need for differentiated, value-adding data with standardized company-level fundamentals, estimates, and deep industry-specific metrics, alongside macro information.

Coverage

Bloomberg covers a wide range of companies across different industries, from large corporations to smaller businesses. This extensive coverage ensures that users have access to comprehensive financial data and insights.

Bloomberg Markets maintains coverage of stocks, bonds, commodities, emerging markets, and forex markets from more than 160 countries. Bloomberg Politics holds the largest news agency in the world in US politics and major global events with more than 1000 reporters and staff. Bloomberg News publishes around 5000 stories daily.

Period

Bloomberg usually provides data with the longest available time period. For example, for Bitcoin data starts in 2010.

Frequency

The period and frequency of forecasts on Bloomberg vary based on user needs and market dynamics. Users can access real-time updates and forecasts as frequently as necessary to stay informed about market changes and company performance.

Bloomberg offers the only cloud-native real-time data delivery option suitable for capital markets use. It delivers B-PIPE through an intra-cloud connection to a managed virtual private cloud on Amazon Web Services (AWS) via AWS Private Link. This low-latency option provides speed, reliability, and security via connectivity that remains solely in AWS.

Pricing

The specific pricing for accessing Bloomberg data is mentioned on the Bloomberg website and it states to have categories like all-in access, limited access, and also has special student access for limited data. The cost likely varies based on the package and offerings selected, which can include different data sets, yearly or monthly subscriptions, and access methods. For detailed pricing information, it is recommended to directly go through the Bloomberg website as it includes very precise information that pretty much caters to all the needs based on the functionality.

Bloomberg charges a fee for its services, usually on a subscription basis. The cost can be high, but many financial professionals find it worth it for the valuable information they receive.

Use of Bloomberg by the Financial Community

Benchmark for Analysis

Professionals rely on Bloomberg’s extensive database of financial data, economic indicators, and market news to conduct in-depth analyses of companies, industries, and markets. The platform provides powerful tools and customizable features that enable users to create detailed financial models, perform comparative analysis, and track key performance metrics.

Market Expectations

Financial professionals use Bloomberg to stay informed about market expectations and sentiment. The platform aggregates market forecasts, including earnings estimates, revenue projections, and economic indicators, allowing users to assess consensus expectations and potential market trends. Bloomberg’s real-time updates and customizable alerts enable users to monitor shifts in market sentiment and adjust investment strategies accordingly.

Earnings Season Preparation

During earnings seasons, Bloomberg becomes an essential tool for financial professionals preparing for corporate earnings releases. The platform’s earnings analysis tools help users interpret financial results, identify underlying trends, and make informed decisions based on earnings reports.

Bloomberg and Tests of Market Efficiency

Academic works

Researchers and scholars leverage Bloomberg’s vast dataset and analytics tools to conduct empirical studies on market behavior, information dissemination, and the efficiency of asset pricing models. By analyzing historical market data and real-time information flow, academics assess the degree to which markets reflect all available information and efficiently incorporate new information into asset prices.

Information Dissemination

One key aspect of market efficiency is the speed and accuracy of information dissemination. Bloomberg facilitates the rapid dissemination of market news, economic data, and corporate announcements to a global audience of financial professionals. Researchers use Bloomberg to study how quickly information is incorporated into asset prices and whether markets efficiently reflect public and private information.

Pros and Cons

Given its history and operations in widely known industries and markets, we certainly need to know the pros and cons of Bloomberg.

Bloomberg provides users with access to extensive financial data and analytics, enabling rigorous empirical studies on market efficiency. Bloomberg’s customizable tools and advanced features facilitate complex analyses and modeling for testing various market efficiency hypotheses. The platform offers real-time updates and historical data, allowing researchers to analyze market behavior over different periods and market conditions.

On the other side, Bloomberg’s subscription costs may limit access to users with limited budgets or academic institutions with constrained resources. The complexity of Bloomberg’s interface and data structure may also present a learning curve for users new to the platform.

Conclusion

Bloomberg’s impact extends across the financial community, serving as a trusted resource for investors, traders, analysts, and corporate professionals worldwide.

Why should I be interested in this post?

According to me, mastering Bloomberg can equip management students with valuable skills and knowledge that are directly applicable to careers in finance, business analysis, and strategic management. It offers a practical way to enhance analytical capabilities, stay updated with industry trends, and build a strong foundation for future professional success.

Useful resources

Bloomberg

Wikipedia Bloomberg L.P.

Statista Estimated revenue generated by Bloomberg LP worldwide from 2015 to 2022

Bloomberg Generative AI to Become a $1.3 Trillion Market by 2032, Research Finds

Bloomberg Bloomberg Launches Point-in-Time Data Solution that Gives Quants a Competitive Edge

About the author

The article was written in May 2024 by Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management (MiM), 2021-2024).

Solana: Ascendancy of the High-Speed Blockchain

May 29, 2025April 17, 2024 by Snehasish CHINARA

In this article, Snehasish CHINARA (ESSEC Business School, Grande Ecole Program – Master in Management, 2022-2024) explains the evolution of high performance blockchain powered cryptocurrency, Solana.

Historical context and background

Solana, a relatively new entrant in the cryptocurrency arena, emerged against the backdrop of an increasingly crowded and competitive landscape in the digital currency space. Founded in 2020 by Anatoly Yakovenko, a former engineer at Qualcomm, Solana sought to address some of the inherent scalability and speed limitations plaguing earlier blockchain platforms like Ethereum. The platform is named after the Solana Beach in California, where Yakovenko often surfed, symbolizing the project’s ambition to ride the waves of innovation and technological advancement.

Unlike many other cryptocurrencies that primarily rely on Proof of Work (PoW) or Proof of Stake (PoS) consensus mechanisms, Solana introduced a novel consensus mechanism known as Proof of History (PoH). This mechanism aims to optimize transaction processing speed by organizing transactions into a series of chronological events, enabling parallel transaction processing, and significantly enhancing scalability. Solana’s emphasis on scalability and throughput has positioned it as a promising platform for decentralized applications (dApps) and decentralized finance (DeFi) projects seeking high-performance blockchain infrastructure. Its innovative approach has garnered attention and support from investors and developers alike, propelling Solana into the spotlight as one of the leading contenders in the cryptocurrency space.

Solana Logo

Source: Google.

Figure 1. Key Dates in Solana History.

Source: Yahoo! Finance.

Key features

Scalability

Solana is designed to be highly scalable, capable of processing thousands of transactions per second. Its unique consensus mechanism, Proof of History (PoH), combined with a network of nodes running parallel processing, enables Solana to handle a high throughput of transactions efficiently.

Fast Transaction Speeds

With its focus on scalability, Solana boasts incredibly fast transaction speeds. Transactions can be confirmed in milliseconds, making it suitable for applications requiring rapid transaction processing, such as decentralized finance (DeFi) platforms and high-frequency trading.

Low Transaction Costs

Solana aims to keep transaction costs low, even during periods of high network activity. Its efficient use of resources and high throughput allow for cost-effective transactions, making it accessible to users and developers alike.

Proof of History (PoH)

Solana’s unique consensus mechanism, PoH, serves as a historical record for the ordering and time-stamping of transactions. By leveraging PoH, Solana achieves high throughput without sacrificing decentralization or security.

Support for Smart Contracts

Solana is compatible with smart contracts, allowing developers to build decentralized applications (dApps) and execute programmable transactions on the blockchain. It supports smart contract languages like Rust and Solidity, enabling a wide range of developers to build on the platform.

Ecosystem and Development Tools

Solana boasts a growing ecosystem of projects and development tools to support developers in building decentralized applications. Its developer-friendly environment includes tools such as Solana Studio, a web-based IDE for building and deploying smart contracts, and libraries for interacting with the Solana blockchain.

Interoperability

Solana is designed to be interoperable with other blockchains and protocols, facilitating seamless communication and asset transfer between different networks. This interoperability opens up possibilities for cross-chain decentralized applications and enhances the overall utility of the Solana ecosystem.

Use cases

Non-Fungible Tokens (NFTs)

Solana provides an efficient infrastructure for minting, trading, and storing NFTs. Artists, creators, and collectors are utilizing Solana-based marketplaces like Solanart to buy and sell digital collectibles, artwork, and virtual assets. Solana’s high throughput enables seamless NFT transactions, while its low fees make it appealing for creators seeking an alternative to Ethereum’s congested network.

Gaming and Virtual Worlds

Solana’s high-performance blockchain is well-suited for gaming applications and virtual worlds that require fast transaction processing and scalability. Game developers are leveraging Solana’s infrastructure to create blockchain-based games, in-game assets, and decentralized gaming platforms. Projects like Star Atlas, a space-themed massively multiplayer online game (MMO) built on Solana, demonstrate the platform’s potential to disrupt the gaming industry.

Decentralized Autonomous Organizations (DAOs)

Solana provides a robust framework for building decentralized autonomous organizations (DAOs) that enable community governance and decision-making. DAOs on Solana leverage smart contracts to automate voting mechanisms, distribute governance tokens, and execute proposals transparently and efficiently. These DAOs empower communities to collectively manage and govern decentralized protocols, platforms, and resources.

Tokenization of Real-World Assets

Solana facilitates the tokenization of real-world assets such as real estate, stocks, and commodities, enabling fractional ownership and increased liquidity. Projects are exploring Solana’s blockchain to tokenize and trade various asset classes, unlocking new investment opportunities and reducing barriers to entry for traditional markets.

Technology and underlying blockchain

At the core of Solana’s architecture is the Proof of History (PoH) consensus mechanism, which orders transactions before they are processed into blocks. This deterministic sequencing allows for parallel transaction processing and enhances overall network efficiency. Additionally, Solana utilizes a Byzantine Fault Tolerance (BFT) consensus algorithm called Tower BFT, which further ensures network security and integrity.

Solana’s blockchain implements a novel data structure known as the “Solana Architecture,” which includes a combination of a single global state, a high-speed networking stack, and a high-performance virtual machine (VM). This architecture enables Solana to achieve impressive transaction throughput, with the capability to process thousands of transactions per second (TPS) and sub-second transaction finality. Furthermore, Solana leverages a unique mechanism called “Turbine” to optimize block propagation and reduce network latency, enhancing the overall scalability and performance of the platform.

The Solana ecosystem also features a built-in decentralized exchange (DEX), supporting seamless token swaps and liquidity provision directly on-chain. Smart contracts on Solana are executed using a high-performance VM called Sealevel, which is designed to efficiently process complex computations while maintaining low transaction costs. Overall, Solana’s technology stack, comprising innovative consensus mechanisms, advanced data structures, and optimized networking protocols, positions it as a leading blockchain platform capable of supporting a wide range of decentralized applications (dApps) and use cases at scale.

Supply of coins

Solana (SOL) operates on a fixed supply model, with a maximum supply of 489,026,837 SOL tokens. Unlike traditional fiat currencies, Solana’s tokenomics are governed by the principles of cryptocurrency protocols. The initial distribution of SOL tokens occurred through a combination of token sales, strategic partnerships, ecosystem incentives, and network validators’ rewards. Notably, Solana employs a deflationary economic model, wherein a portion of transaction fees is burned, reducing the overall token supply over time. This deflationary mechanism is designed to counterbalance any potential inflationary pressures as the network expands, ensuring the long-term sustainability and scarcity of SOL tokens. Additionally, SOL tokens are used to facilitate various functions within the Solana ecosystem, including transaction fees, staking rewards, governance participation, and decentralized application interactions. As Solana continues to grow and gain adoption, the controlled and predictable token supply dynamics play a crucial role in maintaining the network’s integrity and value proposition.

Historical data for Solana

How to get the data?

The Solana (SOL) is a popular cryptocurrency on the market, and historical data for the Solana such as prices and volume traded can be easily downloaded from the internet sources such as Yahoo! Finance, Blockchain.com & CoinMarketCap. For example, you can download data for Solana on Yahoo! Finance (the Yahoo! code for Solana is SOL-USD).

Figure 2. Solana data

Source: Yahoo! Finance.

Historical data for the Solana market prices

The historical data for Solana market prices demonstrates a dynamic evolution marked by significant fluctuations and notable trends since its inception. Initially, SOL experienced modest trading activity and price levels, but as Solana gained recognition for its innovative blockchain architecture and scalability features, its market value began to ascend. Early adopters and investors drove demand for SOL tokens, leading to periods of rapid appreciation interspersed with corrections and consolidation phases. Milestones such as protocol upgrades, partnerships, and successful dApp launches often coincided with significant price movements. Moreover, broader market trends and sentiment towards cryptocurrencies influenced SOL’s price dynamics, contributing to both bullish and bearish cycles over time. Overall, SOL’s price trajectory reflects Solana’s journey from its early stages to becoming a prominent player in the blockchain space, highlighting its potential to revolutionize decentralized applications and digital finance despite the inherent volatility of the cryptocurrency market.

Figure 3 below represents the evolution of the price of Solana (SOL) in US dollar over the period April 2020 – December 2023. The price corresponds to the “closing” price (observed at 10:00 PM CET at the end of the month).

Figure 3. Evolution of the Solana (SOL) price

Source: Yahoo! Finance.

R program

The R program below written by Shengyu ZHENG allows you to download the data from Yahoo! Finance website and to compute summary statistics and risk measures about the Solana (SOL).

The R program that you can download above allows you to download the data for the Solana (SOL) from the Yahoo! Finance website. The database starts on April, 2020.

Table 1 below represents the top of the data file for the Solana (SOL) downloaded from the Yahoo! Finance website with the R program.

Table 1. Top of the data file for the Solana (SOL)

Source: computation by the author (data: Yahoo! Finance website).

Python code

You can download the Python code used to download the data from Yahoo! Finance.

Python script to download Solana (SOL) historical data and save it to an Excel sheet::

import yfinance as yf

import pandas as pd

# Define the ticker symbol for Solana Coin

SOL_ticker = “SOL-USD”

# Define the date range for historical data

start_date = “2020-01-01”

end_date = “2022-01-01”

# Download historical data using yfinance

SOL_data = yf.download(SOL_ticker, start=start_date, end=end_date)

# Create a Pandas DataFrame from the downloaded data

doge_df = pd.DataFrame(SOL_data)

# Define the Excel file path

excel_file_path = “SOL_historical_data.xlsx”

# Save the data to an Excel sheet

SOL_df.to_excel(excel_file_path, sheet_name=”SOL_historical_data”)

print(f”Data saved to {excel_file_path}”)

# Make sure you have the required libraries installed and adjust the “start_date” and “end_date” variables to the desired date range for the historical data you want to download.

Evolution of the Solana (SOL)

Figure 4 below gives the evolution of the Solana (SOL) returns from April, 2020 to December 31, 2023 on a daily basis.

Figure 4. Evolution of the Solana (SOL) returns.

Source: computation by the author (data: Yahoo! Finance website).

Summary statistics for the Solana (SOL)

The R program that you can download above also allows you to compute summary statistics about the returns of the Solana (SOL). Table 2 below presents the following summary statistics estimated for the Solana (SOL):

The mean

The standard deviation (the squared root of the variance)

The skewness

The kurtosis.

The mean, the standard deviation / variance, the skewness, and the kurtosis refer to the first, second, third and fourth moments of statistical distribution of returns respectively.

Table 2. Summary statistics for Solana (SOL).

Source: computation by the author (data: Yahoo! Finance website).

Statistical distribution of the Solana (SOL) returns

Historical distribution

Figure 5 represents the historical distribution of the Solana (SOL) daily returns for the period from April, 2020 to December 31, 2023.

Figure 5. Historical Solana (SOL) distribution of the returns.

Source: computation by the author (data: Yahoo! Finance website).

Gaussian distribution

Figure 6 below represents the Gaussian distribution of the Solana (SOL) daily returns with parameters estimated over the period from April, 2020 to December, 2023.

Figure 6. Gaussian distribution of the Solana (SOL) returns.

Source: computation by the author (data: Yahoo! Finance website).

Risk measures of the Solana (SOL) returns

The R program that you can download above also allows you to compute risk measures about the returns of the Solana (SOL).

Table 3 below presents the following risk measures estimated for the Solana (SOL):

The long-term volatility (the unconditional standard deviation estimated over the entire period)

The short-term volatility (the standard deviation estimated over the last three months)

The Value at Risk (VaR) for the left tail (the 5% quantile of the historical distribution)

The Value at Risk (VaR) for the right tail (the 95% quantile of the historical distribution)

The Expected Shortfall (ES) for the left tail (the average loss over the 5% quantile of the historical distribution)

The Expected Shortfall (ES) for the right tail (the average loss over the 95% quantile of the historical distribution)

The Stress Value (SV) for the left tail (the 1% quantile of the tail distribution estimated with a Generalized Pareto distribution)

The Stress Value (SV) for the right tail (the 99% quantile of the tail distribution estimated with a Generalized Pareto distribution)

Table 3. Risk measures for the Solana (SOL).

Source: computation by the author (data: Yahoo! Finance website).

The volatility is a global measure of risk as it considers all the returns. The Value at Risk (VaR), Expected Shortfall (ES) and Stress Value (SV) are local measures of risk as they focus on the tails of the distribution. The study of the left tail is relevant for an investor holding a long position in the Solana (SOL) while the study of the right tail is relevant for an investor holding a short position in the Solana (SOL).

Why should I be interested in this post?

This blog offers an engaging exploration into a cryptocurrency that transcends traditional finance, appealing to a wide audience due to its cultural relevance, investment potential, and vibrant community. Solana’s reputation for high performance in blockchain technology, boasting the capability to process thousands of transactions per second, makes it an appealing option for developers and users seeking efficient transaction processing. Moreover, staying updated on Solana can offer insights into the growth of its ecosystem, including the development of decentralized applications (dApps) and strategic partnerships. For investors, Solana’s increasing popularity and ecosystem growth may signal investment opportunities, making it worthwhile to track news and discussions surrounding the platform. Additionally, Solana’s innovative technical advancements in scalability, consensus mechanisms, and developer tools are of interest to those intrigued by blockchain technology. Engaging with the Solana community provides opportunities for networking and gaining valuable insights into this rapidly expanding ecosystem.

Useful resources

Academic research about risk

Longin F. (2000) From VaR to stress testing: the extreme value approach Journal of Banking and Finance, N°24, pp 1097-1130.

Longin F. (2016) Extreme events in finance: a handbook of extreme value theory and its applications Wiley Editions.

Data

Yahoo! Finance

Yahoo! Finance Historical data for Solana

CoinMarketCap Historical data for Solana

About the author

The article was written in April 2024 by Snehasish CHINARA (ESSEC Business School, Grande Ecole Program – Master in Management, 2022-2024).

Bitcoin est un rêve, un idéal, un espoir

April 15, 2024April 9, 2024 by Jean-Marie CHOFFRAY

Bitcoin est un rêve, un idéal, un espoir

Dans cet article, Jean-Marie CHOFFRAY (Professeur Ordinaire Honoraire d’Informatique Décisionnelle à l’Université de Liège, PhD-77, Management Science, Massachusetts Institute of Technology) introduit son recent article “Mille quatre cent milliards de dollars”.

Personne ne sait précisément ce qu’est Bitcoin (avec « Bvle réseau). Au plan conceptuel, bitcoin (avec « b le jeton) est une chaîne, aussi indestructible que possible, de blocs d’enregistrements, aussi sécurisés que possible. Cette technologie nouvelle est donc un projet en cours dont personne ne peut préjuger l’avenir, quelle que soit la dimension considérée. Bitcoin deviendra ce que la majorité de ses utilisateurs décidera, et surtout aura le courage, d’en faire. Pour Satochi Nakamoto, c’était un rêve. Pour ceux qui travaillent aujourd’hui sur son code, c’est un idéal. Enfin, pour ceux qui l’utiliseront demain, c’est un espoir. L’Histoire de l’Humanité, une autre chaîne de blocs d’enregistrements – à l’évidence, non sécurisés et falsifiables ! – , s’apparente au reflet d’une montée de la Conscience individuelle et collective (cf. « Le phénomène humain » de Pierre Teilhard de Chardin). Bitcoin, c’est L’espoir maintenant (entretien entre Jean-Paul Sartre et Benny Lévy) : « une tension vers la fin, que l’échec, le tragique ne sauraient annuler… La valeur économique de bitcoin serait-elle le prix de la liberté ?

▶ Lire l’article Bitcoin est un rêve, un idéal, un espoir

Autres articles sur le blog

▶ Snehasish CHINARA Bitcoin: the mother of all cryptocurrencies

▶ Jean-Marie CHOFFRAY Mille quatre cent milliards de dollars

A propos de l’auteur

L’article a été rédigé en mars 2024 par Jean-Marie CHOFFRAY (Professeur Ordinaire Honoraire d’Informatique Décisionnelle à l’Université de Liège, PhD-77, Management Science, Massachusetts Institute of Technology).

Types of Market Consensus

April 15, 2024April 9, 2024 by Nithisha CHALLA

Types of Market Consensus

In this article, Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management (MiM), 2021-2024) explains what are the market consensus and different forms of into financial sentiments.

Introduction

Market consensus often talked about in financial circles, goes beyond just a collective opinion; it reflects how investors feel and what’s happening in the financial world. This article looks into different types of market consensus: the agreement on prices between buyers and sellers, the insights provided by financial analysts who study companies’ basics and economic indicators, and the views of technical analysts who analyze stock prices. Several things affect market consensus, like how people generally feel about the market, expectations for market changes, and the actions of important players like central banks.

Understanding the various forms of market consensus is essential for investors and traders navigating the complex world of finance. These collective opinions shape market trends and impact investment decisions.

Price Consensus

One of the most visible forms of market consensus is reflected in asset prices. The principle of supply and demand drives prices, with consensus emerging as traders and investors assess the value of an asset based on various factors such as economic indicators, company performance, and geopolitical events. As these factors change and influence perceptions, they contribute to the evolving consensus reflected in asset prices.

Example: In 2020, Tesla’s stock experienced a tremendous surge as market consensus shifted positively around electric vehicles and renewable energy. Investors believed in the company’s potential for growth, leading to a significant increase in Tesla’s stock price.

Market consensus by financial analysts

Consensus on revenues and earnings

Earnings consensus revolves around the expected future earnings of a company. Analysts and financial experts often provide earnings estimates, and market consensus forms around these forecasts. Deviations from these expectations can lead to significant price movements as investors reassess the company’s performance and prospects. This dynamic interaction between earnings forecasts and market reactions underscores the importance of consensus expectations in shaping investor sentiment and market behavior.

Example: Apple’s quarterly earnings announcements are highly anticipated by the market. If Apple reports earnings that exceed analysts’ consensus estimates, it can lead to a surge in its stock price, reflecting the positive earnings consensus.

Consensus on economic indicators

Economic indicators, such as GDP growth, inflation rates, and unemployment figures, shape the macroeconomic consensus. Governments, central banks, and international organizations routinely release data that analysts and investors leverage to assess the broader economic landscape. Market responses frequently track deviations from consensus forecasts related to these indicators. When actual economic data diverges from expectations, it can trigger significant market movements as investors adjust their outlook on economic conditions and potential policy responses.

Example: During the global financial crisis of 2008, there was a consensus among economists that the world economy was entering a recession. This consensus influenced investor behavior, leading to widespread selling in equity markets and a shift towards safer assets.

Market consensus by technical analysts

Market consensus by technical analysts revolves around interpreting stock price movements and patterns to forecast future market trends. Technical analysts use charts and indicators to identify potential buying or selling opportunities based on historical price data. By analyzing patterns such as support and resistance levels, moving averages, and trading volumes, technical analysts contribute insights into market sentiment and potential price directions. This approach to market consensus complements fundamental analysis and provides a different perspective on investor behavior and sentiment. Breaking through a significant resistance level might lead to a bullish consensus; similarly, breaking through a significant support level might lead to a bearish consensus.

Factors influencing the market consensus

Size of the company and coverage by financial analysts

The size of a company and how many analysts are covering it also influence the stock market consensus. If only a handful of analysts are assigned to the stock, the market consensus estimates are more likely to vary from actual results.

Market sentiment

The sentiment of market participants plays a crucial role in shaping market consensus. Investor sentiment can be bullish or bearish, influenced by factors like news, social media, and market events. Contrarian investors often excel by taking positions opposite to prevailing sentiment, capitalizing on opportunities arising from market overreactions and sentiment shifts. Understanding and analyzing market sentiment is essential for gauging potential market directions and identifying contrarian investment opportunities.

Example: The GameStop saga in early 2021 is a notable example of sentiment consensus. Retail investors on social media forums collectively drove up the stock price of GameStop, challenging traditional market dynamics and catching institutional investors off guard.

Volatility expectations

Volatility expectations, measured by metrics like the VIX (Volatility Index), represent a form of consensus about future market stability. Traders and investors use volatility as an indicator of market risk, and consensus around heightened volatility can lead to defensive strategies, such as increased hedging or reduced risk exposure. Understanding and interpreting volatility consensus is essential for adapting investment strategies to prevailing market conditions and risk perceptions.

Example: The COVID-19 pandemic in 2020 led to a consensus on increased market volatility. The VIX (Volatility Index) surged as investors anticipated heightened uncertainty, prompting shifts in investment strategies to account for the expected market fluctuations.

Policy Consensus

Central bank policies, government regulations, and fiscal measures contribute to policy consensus. Market participants closely monitor statements and decisions made by central banks and governments, forming expectations about interest rates, monetary policy, and regulatory changes. Any surprises in these areas can lead to market volatility.

Example: The announcement of the U.S. Federal Reserve’s quantitative easing policies during the 2008 financial crisis influenced market consensus. The expectation of increased liquidity and lower interest rates contributed to a rally in stock markets.

Technological Consensus

Technological consensus refers to the collective agreement or perception within the technology sector regarding emerging trends, innovations, or the adoption of specific technologies. Industry experts, analysts, and stakeholders contribute to this consensus through assessments of technology developments, market dynamics, and consumer behavior. Consensus within technology influences investment decisions, product development strategies, and market forecasts. Understanding technological consensus is crucial for businesses and investors seeking to navigate the rapidly evolving landscape of technology-driven industries.

Example: The rise of FAANG stocks (Facebook, Apple, Amazon, Netflix, Google) in the last decade reflects a technological consensus. Investors collectively believed in the transformative power of these technology giants, contributing to their substantial market capitalizations.

Conclusion

Market consensus, when explored through the lens of data and statistics, transforms from a theoretical concept to a tangible and actionable tool. Whether you’re an investor, a business leader, or an analyst, integrating statistical insights into your understanding of market consensus adds a layer of precision to decision-making. In the dynamic world of finance, where every percentage point matters, harnessing the power of market consensus with a data-driven approach ensures a more informed and strategic navigation of financial waters.

Why should I be interested in this post?

In essence, this article provides a holistic and data-driven perspective on market consensus, catering to the interests of investors, business professionals, and anyone seeking a nuanced understanding of how collective sentiments shape the financial landscape. Whether you’re actively involved in financial decision-making or simply intrigued by the dynamics of the market, this article offers valuable insights that bridge theory and real-world applications.

Useful resources

CNN Fear & Greed Index: What emotion is driving the market now?

Market consensus What is market consensus?

Faster Capital Navigating Markets: The Power of Market Analysis and Consensus Estimates

About the author

The article was written in April 2024 by Nithisha CHALLA (ESSEC Business School, Grande Ecole – Master in Management (MiM), 2021-2024).

Institutional Brokers’ Estimate System (IBES)

April 9, 2024 by Nithisha CHALLA

Institutional Brokers’ Estimate System (IBES)

In this article, Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management (MiM), 2021-2024) presents Institutional Brokers’ Estimate System (IBES), which provides market consensus for the financial community.

Introduction

In the fast-paced world of finance, the Institutional Brokers’ Estimate System, commonly known as IBES (often written as “I/B/E/S.”), stands as a linchpin in providing investors, analysts, and financial professionals with reliable forecasts and estimates.

IBES, with its roots in comprehensive data aggregation, takes center stage in providing a panoramic view of financial analysts’ estimates and forecasts. IBES acts as a centralized repository of earnings estimates, revenue projections, and other key financial metrics, serving as a vital resource for investors seeking actionable insights.

History

IBES was created in 1976 by the investment research firm, Lynch, Jones & Ryan (LJR). It was developed to address the need for a centralized system to collect and distribute earnings estimates from brokerage analysts. The database offers historical data from its inception and extends internationally from 1987. Over the years, IBES went through several ownership changes. In 1988, LJR was acquired by Primark Corporation. Primark Corporation later merged with Thomson Financial Services in 1990, and IBES became part of Thomson Financial. Thomson Financial subsequently merged with Reuters Group in 2008 to form Thomson Reuters. Thus, IBES became a part of Thomson Reuters. Then Thomson Reuters was acquired by private equity firm Blackstone Group and rebranded as Refinitiv in 2018. Refinitiv was later acquired by the London Stock Exchange Group (LSEG) in 2020. Therefore, IBES is currently owned by the London Stock Exchange Group (LSEG) through its subsidiary, Refinitiv.

Key Components of IBES

Earnings Estimates

IBES compiles earnings estimates from a multitude of financial analysts, providing a consensus view on the expected earnings of a company. As of the latest data, it aggregates forecasts from over 16,000 analysts worldwide, providing a robust consensus on expected earnings for companies across the globe.

Revenue Projections

Beyond earnings, IBES includes revenue projections, offering a comprehensive view of a company’s expected top-line growth. Analysts’ forecasts are aggregated to provide a consensus estimate, aiding investors in gauging revenue expectations.

Forecasts for Key Financial Metrics

IBES extends beyond earnings and revenue, encompassing a spectrum of financial metrics. This includes estimates for operating margins, cash flows, and other key indicators, providing a holistic view of analysts’ expectations. The sheer volume of data—covering over 18,000 companies—ensures a comprehensive snapshot of financial expectations.

Coverage

There are certain types of coverage when we are talking about data coverage such as the Number of Companies Covered, geographic Coverage, Market Capitalization Coverage, Industry Coverage, Depth of Coverage, and Historical Coverage.

According to LSEG data analytics, I/B/E/S Estimates data is displayed at the company level, screened with rigorous quality control methods across more than 23,400 active companies in more than 90 countries, and sourced from over 19,000 analysts.

Estimates Data from over 950 firms contribute data to I/B/E/S, from the largest global houses to regional and local brokers, with U.S. data back to 1976 and international data back to 1987.

Period

IBES has evolved since its introduction in 1976 and includes international data from 1987. I/B/E/S Global Aggregates, with over 30 years of history, facilitates top-down analysis to better assess potential growth and risk as well as future value across industry, sector, index, country, and region.

Frequency

Initially focusing on annual earnings estimates, the database subsequently broadened to encompass quarterly earnings forecasts.

Firms and Financial analysts

IBES covers a wide range of firms across different industries, sectors, and regions. This includes companies listed on major stock exchanges in numerous countries and markets around the world. 950+ contributors, across 90+ in developed and emerging markets, totaling over 19,000 individual analysts – the most in the industry. Unmatchable history across more than 60,000 companies back to 1976 for North America, 1987 for other markets.

Pricing

The specific pricing for accessing I/B/E/S data is not explicitly mentioned on the IBES website and you have to make a request through the LSEG website which manages IBES. The cost likely varies based on the package and offerings selected, which can include different data sets, access methods, and service frequencies. For detailed pricing information, it’s recommended to directly contact LSEG or the respective service providers you’re interested in, as they can provide more precise details based on your specific requirements and the scale of your intended use.

For academic and non-commercial research purposes, access might be available through institutional subscriptions with specific terms of use, as seen with Aalto University’s subscription financed by the Aalto University Data Hub for its users. This indicates that the availability and cost of I/B/E/S data may vary significantly based on the type of use and the access platform. For precise pricing and package options, directly contacting the service providers is the best approach.

Use of IBES by the Financial Community

Benchmark for Analysis

IBES serves as a benchmark for investors and analysts, quantifying market reactions, it dives into the numbers behind market reactions. According to Faster Capital, studies reveal that stocks experiencing positive earnings surprises, surpassing IBES estimates, tend to outperform the market. These numerical insights underscore the practical implications of aligning investment decisions with IBES consensus.

Market Expectations

Analysts and fund managers utilize IBES to gauge market expectations for specific companies. Understanding consensus estimates aids in forming investment strategies aligned with prevailing market sentiments.

Earnings Season Preparation

During earnings seasons, IBES becomes a critical tool for investors preparing for companies’ financial releases. It provides a consolidated view of analysts’ forecasts, helping investors assess potential surprises or disappointments.

IBES and Tests of Market Efficiency

Academic works

The data was subsequently used as the basis for articles in academic finance journals attempting to demonstrate that changes in consensus earnings estimates could identify opportunities to capture excess returns in subsequent periods.

Information Dissemination

IBES plays a pivotal role in disseminating timely information. As estimates are constantly updated based on new information, IBES ensures that market participants have access to the latest insights, contributing to market efficiency.

Pros and Cons

Given its history and operations in huge industries and markets, we certainly need to know the pros and cons of the IBES estimates. In terms of accuracy metrics, IBES relies on the accuracy of analysts’ forecasts. Statistical metrics, such as the mean absolute error (MAE), offer a quantitative evaluation of the system’s precision.

Conclusion

IBES, when viewed through a data-driven lens, transforms into more than a system and becomes a useful tool for decision-makers navigating the intricacies of financial markets.

Why should I be interested in this post?

In essence, this article discovers how the global data powerhouse, backed by impactful statistics, empowers investors, providing a data-driven lens into market expectations and offering actionable insights for informed decision-making in the dynamic world of finance.

Useful resources

London Stock Exchange Group (LSEG) I/B/E/S Estimates

Wikipedia Institutional Brokers’ Estimate System

Market consensus What is market consensus?

Faster Capital Navigating Markets: The Power of Market Analysis and Consensus Estimates

About the author

The article was written in March 2024 by Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management (MiM), 2021-2024).

USD Coin: Deep Dive into the Role of Stablecoins in Modern Finance

January 15, 2025April 2, 2024 by Snehasish CHINARA

In this article, Snehasish CHINARA (ESSEC Business School, Grande Ecole Program – Master in Management, 2022-2024) explains the stable coin USD Coin.

Historical context and background

USD Coin (USDC) is a type of cryptocurrency known as a stablecoin, designed to maintain a stable value relative to the US dollar (USD). It was launched in September 2018 by Centre Consortium, a collaboration between cryptocurrency exchange Coinbase and blockchain technology company Circle. The primary goal of USDC is to provide a digital asset that can be easily transferred between users and used for transactions, while minimizing the volatility typically associated with other cryptocurrencies like Bitcoin or Ethereum.

The need for stablecoins like USDC arose due to the inherent volatility of many cryptocurrencies. While Bitcoin and other digital assets have gained significant attention and adoption, their prices can fluctuate dramatically over short periods, which can make them less practical for everyday transactions and financial contracts. Stablecoins like USDC offer a solution to this problem by pegging their value to a stable asset, such as the US dollar, thereby providing stability and predictability for users.

USDC operates on the Ethereum blockchain as an ERC-20 token, making it compatible with a wide range of decentralized applications (dApps) and enabling seamless integration with the broader cryptocurrency ecosystem. This infrastructure allows users to easily send and receive USDC tokens across various platforms and services, including exchanges, wallets, and payment processors.

Since its launch, USDC has seen significant growth in adoption and usage. It has become one of the most widely used stablecoins in the cryptocurrency market, with billions of dollars worth of USDC tokens in circulation. Its stability and liquidity have made it a popular choice for traders, investors, and businesses looking to transact in digital assets without exposure to the volatility of other cryptocurrencies.

USD Coin Logo

Source: Yahoo! Finance.

Figure 1. Key Dates in USDC History

Source: Yahoo! Finance.

Key features

Stability

USD Coin is a stablecoin, meaning it is pegged to the value of the US dollar on a 1:1 basis. This stability is maintained through regular audits and backing by reserves of US dollars held in custody by regulated financial institutions.

Transparency

USDC operates on blockchain technology, providing transparency and immutability of transactions. Every USDC token is backed by an equivalent number of US dollars held in reserve, which is regularly audited and transparently reported to ensure trust among users.

Speed and Efficiency

Transactions involving USDC can be executed quickly and efficiently on blockchain networks, enabling near-instantaneous settlement compared to traditional banking systems, which may take days for cross-border transactions.

Global Accessibility

USDC enables borderless transactions, allowing users to send and receive payments globally without the need for intermediaries such as banks. This accessibility empowers individuals and businesses, particularly in regions with limited access to traditional financial services.

Interoperability

USDC is compatible with various blockchain platforms and protocols, including Ethereum, Algorand, and Solana, among others. This interoperability facilitates its integration into a wide range of decentralized applications (DApps) and decentralized finance (DeFi) ecosystems.

Use cases

Remittances and Cross-Border Payments:

USDC provides a cost-effective and efficient solution for remittance payments and cross-border transactions, enabling individuals and businesses to transfer value across borders quickly and securely without the need for traditional banking intermediaries.

Stable Value Storage

Due to its stable value pegged to the US dollar, USDC serves as a reliable store of value and a hedge against volatility in the cryptocurrency market. Users can hold USDC as a stable asset to preserve purchasing power and mitigate the risks associated with price fluctuations in other cryptocurrencies.

Decentralized Finance (DeFi) Applications

USDC is widely used as a liquidity provider and collateral asset in various DeFi protocols and applications such as decentralized exchanges (DEXs), lending platforms, yield farming, and liquidity pools. Users can leverage USDC to earn interest, borrow assets, or participate in yield farming strategies within the DeFi ecosystem.

Commerce and Payments

Merchants and businesses can accept USDC as a form of payment for goods and services, leveraging its fast transaction settlement times and low transaction fees compared to traditional payment methods. Integrating USDC payments can streamline cross-border commerce and reduce friction associated with fiat currency conversions.

Financial Inclusion

USDC plays a crucial role in expanding financial inclusion by providing access to digital financial services for individuals and communities underserved by traditional banking infrastructure. By utilizing blockchain technology and stablecoins like USDC, individuals without access to traditional banking services can participate in the global economy and access a wide range of financial products and services.

Technology and underlying blockchain

USD Coin (USDC) operates on a blockchain-based infrastructure, primarily leveraging the Ethereum blockchain as its foundation. Utilizing Ethereum’s smart contract functionality, USDC tokens are issued, transferred, and redeemed in a transparent and trustless manner. The ERC-20 standard, a set of rules and protocols defining interactions between tokens on the Ethereum network, governs the behavior of USDC tokens, ensuring compatibility with a wide range of wallets, exchanges, and decentralized applications (DApps). Moreover, USDC employs a consortium model for governance and operation, with regulated financial institutions serving as members responsible for the issuance, custody, and redemption of USDC tokens. These institutions adhere to strict regulatory compliance measures and conduct regular audits to verify that each USDC token is fully backed by an equivalent reserve of US dollars held in custody. This combination of blockchain technology, smart contracts, and regulatory oversight ensures the integrity, transparency, and stability of USD Coin, making it a trusted and widely adopted stablecoin within the cryptocurrency ecosystem.

ERC-20 Standard of Ethereum for USD Coin

The ERC-20 standard, short for Ethereum Request for Comment 20, is a widely adopted technical specification governing the creation and implementation of fungible tokens on the Ethereum blockchain. Introduced by Fabian Vogelsteller and Vitalik Buterin in 2015, ERC-20 defines a set of rules and functions that enable seamless interoperability between different tokens, ensuring compatibility with various decentralized applications (DApps) and wallets. Tokens adhering to the ERC-20 standard are characterized by a consistent set of methods, including transfer, balance inquiry, and approval mechanisms, facilitating easy integration and widespread adoption across the Ethereum ecosystem. This standardization has played a pivotal role in the proliferation of tokenization, empowering developers to create diverse tokenized assets, conduct crowdfunding campaigns through Initial Coin Offerings (ICOs), and establish decentralized exchanges (DEXs) where ERC-20 tokens are traded autonomously. Additionally, ERC-20 compliance enhances security and interoperability, fostering trust and usability within the Ethereum network.

Supply of coins

The supply dynamics of USD Coin (USDC) are governed by its underlying smart contract protocol and the management of its issuer, Centre Consortium, a collaboration between Circle and Coinbase. USDC operates on a principle of full backing, where each USDC token issued is backed by an equivalent number of US dollars held in reserve. This backing ensures a 1:1 peg to the US dollar, maintaining its stability. The issuance and redemption of USDC are facilitated through regulated financial institutions that hold the corresponding fiat reserves. Moreover, USDC’s supply is transparently audited on a regular basis, with attestations provided by reputable auditing firms to verify the adequacy of reserves. Through these mechanisms, the supply of USDC remains elastic, expanding or contracting based on market demand while preserving its stability and trustworthiness as a stablecoin in the digital asset ecosystem.

Historical data for USDC

How to get the data?

The USDC is popular cryptocurrency on the market, and historical data for the USDC such as prices and volume traded can be easily downloaded from the internet sources such as Yahoo! Finance, Blockchain.com & CoinMarketCap. For example, you can download data for USDC on Yahoo! Finance (the Yahoo! code for USD Coin is USDC-USD).

Figure 2. USD Coin data

Source: Yahoo! Finance.

Historical data for the USD Coin market prices

The historical market price of USD Coin (USDC) has remained relatively stable, as its primary function is to maintain a value pegged to the US dollar at a 1:1 ratio. Since its inception, USDC has consistently traded around the $1 mark, with minor fluctuations typically attributed to market dynamics and liquidity conditions. Investors and traders often utilize USDC as a safe haven asset or a means of temporarily exiting volatile cryptocurrency markets, contributing to its stability. This stability has made USDC a preferred choice for individuals and institutions seeking to hedge against cryptocurrency volatility or facilitate seamless transitions between digital and fiat currencies. Additionally, the transparent backing of USDC by reserves of US dollars held in custody by regulated financial institutions further enhances market confidence and contributes to its stable market price over time.The historical market price of USD Coin (USDC) has remained relatively stable, as its primary function is to maintain a value pegged to the US dollar at a 1:1 ratio. Since its inception, USDC has consistently traded around the $1 mark, with minor fluctuations typically attributed to market dynamics and liquidity conditions. Investors and traders often utilize USDC as a safe haven asset or a means of temporarily exiting volatile cryptocurrency markets, contributing to its stability. This stability has made USDC a preferred choice for individuals and institutions seeking to hedge against cryptocurrency volatility or facilitate seamless transitions between digital and fiat currencies. Additionally, the transparent backing of USDC by reserves of US dollars held in custody by regulated financial institutions further enhances market confidence and contributes to its stable market price over time.

Figure 3 below represents the evolution of the price of USD Coin in US dollar over the period Oct 2018 – Dec 2022. The price corresponds to the “closing” price (observed at 10:00 PM CET at the end of the month).

Figure 3. Evolution of the USD Coin price

Source: Yahoo! Finance.

R program

The R program below written by Shengyu ZHENG allows you to download the data from Yahoo! Finance website and to compute summary statistics and risk measures about the USD Coin.

Data file

The R program that you can download above allows you to download the data for the USD Coin from the Yahoo! Finance website. The database starts on Oct, 2018. Table 1 below represents the top of the data file for the USD Coin downloaded from the Yahoo! Finance website with the R program.

Table 1. Top of the data file for the USD Coin

Source: computation by the author (data: Yahoo! Finance website).

Python code

You can download the Python code used to download the data from Yahoo! Finance.

Python script to download USD Coin historical data and save it to an Excel sheet::

import yfinance as yf

import pandas as pd

# Define the ticker symbol for USD Coin

usdc_ticker = “USDC-USD”

# Define the date range for historical data

start_date = “2020-01-01”

end_date = “2022-01-01”

# Download historical data using yfinance

usdc_data = yf.download(usdc_ticker, start=start_date, end=end_date)

# Create a Pandas DataFrame from the downloaded data

usdc_df = pd.DataFrame(usdc_data)

# Define the Excel file path

excel_file_path = “USDC_historical_data.xlsx”

# Save the data to an Excel sheet

usdc_df.to_excel(excel_file_path, sheet_name=”USDC Historical Data”)

print(f”Data saved to {excel_file_path}”)

# Make sure you have the required libraries installed and adjust the “start_date” and “end_date” variables to the desired date range for the historical data you want to download.

Evolution of the USD Coin

Figure 4 below gives the evolution of the USDC on a daily basis.

Figure 4. Evolution of the USD Coin.

Source: computation by the author (data: Yahoo! Finance website).

Figure 5 below gives the evolution of the USD Coin returns from Oct, 2018 to December 31, 2022 on a daily basis.

Figure 5. Evolution of the USD Coin returns

Source: computation by the author (data: Yahoo! Finance website).

Summary statistics for the USD Coin

The R program that you can download above also allows you to compute summary statistics about the returns of the USD Coin. Table 2 below presents the following summary statistics estimated for the USD Coin:

The mean

The standard deviation (the squared root of the variance)

The skewness

The kurtosis.

The mean, the standard deviation / variance, the skewness, and the kurtosis refer to the first, second, third and fourth moments of statistical distribution of returns respectively.

Table 2. Summary statistics for USDC.

Source: computation by the author (data: Yahoo! Finance website).

Statistical distribution of the USD Coin returns

Historical distribution

Figure 6 represents the historical distribution of the USD Coin daily returns for the period from Oct, 2018 to December 31, 2022.

Figure 6. Historical USDC distribution of the returns.

Source: computation by the author (data: Yahoo! Finance website).

Gaussian distribution

Figure 7 below represents the Gaussian distribution of the USD Coin daily returns with parameters estimated over the period from October, 2018 to December, 2022.

Figure 7. Gaussian distribution of the USDC returns.

Source: computation by the author (data: Yahoo! Finance website).

Risk measures of the USD Coin returns

The R program that you can download above also allows you to compute risk measures about the returns of the USD Coin.

Table 3 below presents the following risk measures estimated for the USD Coin:

The long-term volatility (the unconditional standard deviation estimated over the entire period)

The short-term volatility (the standard deviation estimated over the last three months)

The Value at Risk (VaR) for the left tail (the 5% quantile of the historical distribution)

The Value at Risk (VaR) for the right tail (the 95% quantile of the historical distribution)

The Expected Shortfall (ES) for the left tail (the average loss over the 5% quantile of the historical distribution)

The Expected Shortfall (ES) for the right tail (the average loss over the 95% quantile of the historical distribution)

The Stress Value (SV) for the left tail (the 1% quantile of the tail distribution estimated with a Generalized Pareto distribution)

The Stress Value (SV) for the right tail (the 99% quantile of the tail distribution estimated with a Generalized Pareto distribution)

Table 3. Risk measures for the USDC.

Source: computation by the author (data: Yahoo! Finance website).

The volatility is a global measure of risk as it considers all the returns. The Value at Risk (VaR), Expected Shortfall (ES) and Stress Value (SV) are local measures of risk as they focus on the tails of the distribution. The study of the left tail is relevant for an investor holding a long position in the XRP while the study of the right tail is relevant for an investor holding a short position in the XRP.

Why should I be interested in this post?

The post offers an opportunity for both newcomers and seasoned cryptocurrency enthusiasts to delve into the concept of stablecoins, gaining insights into how digital assets maintain stability amidst market volatility. Furthermore, the post highlights USDC’s role in fostering financial inclusion by enabling borderless transactions, appealing to readers passionate about democratizing finance. Additionally, exploring USDC’s significance in the burgeoning realm of decentralized finance (DeFi) could intrigue those interested in innovative financial technologies and investment opportunities. Examining USDC’s historical performance and market dynamics can offer valuable insights for investors and traders, while shedding light on its compliance measures and regulatory landscape can address concerns regarding legal risks, contributing to readers’ understanding and confidence in this digital asset.

Useful resources

Academic research about risk

Longin F. (2000) From VaR to stress testing: the extreme value approach Journal of Banking and Finance, N°24, pp 1097-1130.

Longin F. (2016) Extreme events in finance: a handbook of extreme value theory and its applications Wiley Editions.

Data

Yahoo! Finance

Yahoo! Finance Historical data for USDC

CoinMarketCap Historical data for USDC

About the author

The article was written in March 2024 by Snehasish CHINARA (ESSEC Business School, Grande Ecole Program – Master in Management, 2022-2024).

Private Banks : Treasuries Departments and proprietary asset allocation

April 1, 2024 by Quentin CHUZET

Private Banks : Treasuries Departments and proprietary asset allocation

In this article, Quentin CHUZET (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2019-2023) explains about Private banks Treasuries Departments and the challenges of proprietary asset allocation.

Introduction

Within the Treasury Department of a Private Bank, the role of its employees is to record incoming and outgoing cash flows, as well as to direct the allocation of assets that comprise its Treasury. Thus, on one hand, we find the amount of cash on the asset side, and on the other hand, on the liability side, the amount of client deposits. In other words, it can be said that the Treasury is primarily constituted by the various deposits made by clients.

These are grouped into 2 categories: sight deposits (money visible in the client’s bank account, available and usable at any time) and term deposits (money placed generally in interest-bearing accounts but only available once the placement has matured).

Private Bank balance sheet

Source: La Finance Pour Tous

To address performance and revenue challenges, the Treasury department manages cash by investing it in interest-bearing products, aiming to generate significant margins. This activity, performed by the Middle and Front Office teams, is referred to as proprietary trading or prop asset allocation.

Before the 2008 financial crisis, the regulatory environment was less stringent, granting banks greater freedom in risk management. However, the crisis highlighted the dangers of this approach, leading to a significant strengthening of regulations.

In 2013, Basel III introduced one of the most important regulatory agreements in banking. It aims to enhance the resilience of banks by increasing their capital and liquidity requirements. Basel III notably introduced a short-term liquidity ratio (LCR) and a long-term liquidity ratio (NSFR).

Regarding liquidity, private banks must now hold sufficient liquid assets to withstand mass deposit withdrawals. They must also comply with a liquidity coverage ratio (LCR), requiring them to have enough high-quality liquid assets to cover their net cash outflows over a 30-day period.

In terms of solvency, private banks must now comply with a capital adequacy ratio (Cooke ratio), requiring them to have sufficient capital to absorb potential losses. Basel III also introduced a leverage ratio, limiting banks’ leverage.

To ensure compliance with these new regulatory frameworks while continuing to maximize revenue, banks have implemented treasury policies and control ratios to define limits and mitigate risks. These treasury policies, spanning multiple pages, guide Front Office teams in asset allocation to maintain the most efficient risk/return ratio possible. It is important to note that each bank has its own risk level, hence treasury policies and their respective limits may vary from one bank to another.

In general, a bank tends to favor a very low-risk level by prioritizing assets that can be quickly liquidated while limiting exposure to interest rate fluctuations or certain sectors. In the risk management process, liquidity and solvency ratios are monitored, as well as ratios related to interest rate risk and non-systematic risk.

Treasury Policy

These Treasury policies, spanning multiple pages, guide Front Office teams in asset allocation to maintain the most efficient risk/return ratio possible. It is important to note that each Bank possesses a risk level unique to itself, which is why Treasury Policies and their constituent limits may vary from one to another.

Thus, this document is divided into several limits and control ratios aimed at protecting against incurred risks. Among the main ratios present in the Treasury Policies, we find:

Liquidity and solvability ratios

Among liquidity and solvability ratios, controls are placed on the recovery time of securities held by the Treasury, with constraints notably regarding recoverable assets within 2 days and those recoverable within 30 days. Through these ratios, the average lifespan of the portfolio is controlled as well as the maximum duration of the securities, as well as the portion of assets placed with the Central Bank, ensuring a high rate of return in periods of high rates and near-immediate liquidity, as it is possible to recover from one day to the next.

These ratios aim to protect against the greatest risk a bank may face: that of illiquidity. This risk is heightened during crises and when clients wish to make massive withdrawals. The bank must thus ensure that all liquidity can be returned.

Security portfolio allocation’s ratios

Through these ratios, the Bank adheres to exposure limits by sector, industry, or company outlined in the Treasury policy: the leverage ratio is a significant indicator. This allows for diversification of allocations and investments and thus frees from specific risk. There are also control ratios based on Moody’s, S&P, and Fitch ratings or ESG ratings.

Finally, there are also ratios aimed at calculating the share represented by each asset class. It should be noted that each asset class represents what is called a “position” in the Treasury Sheet. In other words, each different class represents a different line. Among these lines are placements in the Money Market (Bond Portfolio, NEUCP Portfolio, placements in OPC funds), term interbank loans, currency and rate SWAPs, etc.

Sensitivity ratios

Through these ratios, the Treasury department controls the sensitivity to rates faced by Treasury assets. The Treasury Policy indicates threshold limits that should not be exceeded to ensure optimal rate adjustments, in the event of both increases and decreases.

Risk Management and Asset Allocation

Managing liquidity and solvability risk

To manage liquidity risk as effectively as possible, Private Banks can consider various strategies:

Purchase securities eligible for ECB refinancing
Maintain a high proportion of assets placed at the Central Bank on a daily basis (as they are highly liquid and yield interest at times of high interest rates).
Maintain a short maturity of the security portfolio and short-term deposits.

Interest-rate risk management

Interest-rate risk is a major issue for Private Banks, since a change in interest rates would have a major impact on the yield and price of bond holdings. The sensitivity of an asset represents the length of time during which it cannot be subjected to a variation in its interest rate. Thus, depending on the prevailing trend surrounding interest rate movements, Treasury Traders must invest to maintain a balanced sensitivity ratio. For example, in a scenario where the market strongly expects a future rate decrease, a strategy aimed at maximizing the adjustment period to the rate and thus the sensitivity ratio may be the best option. Conversely, in a scenario where the market anticipates a significant rate hike in the upcoming period, reducing the adjustment period to the rate for the portfolio would allow a quick re-indexing to a higher rate and reduce the time during which those assets would be “under-earning”.

Specific risk and diversification

A specific risk is linked to a particular event, affecting a single company, a sector of activity or a specific financial instrument. It differs from systemic risk, which affects the entire financial system. To reduce this risk, diversification is a key element, which is why a Private Bank can specify limits by sector or asset class in its Treasury Policy.

Therefore, the Treasury department of the Bank and its Front Office teams can allocate their assets to government bonds, as well as to corporate bonds in sectors such as retail, energy, or Real Estate.

Conclusion

In conclusion, the challenges of asset allocation within the Treasury of private banks are manifold. Guided by Treasury Policies, limits, and control ratios, it must adapt to the emergence of a new regulatory environment to define low-risk, high-liquidity investment strategies while addressing performance and revenue maximization objectives. Furthermore, proprietary asset allocation drives private banks to enhance their internal resources and develop tailored management tools.

Why should I be interested in this post?

If you’re interested in proprietary asset management, or in the workings of a treasury department within a private bank, you’ll find a first overview of these topics in this article.

If you have any questions about the position or the sector, please don’t hesitate to contact me on my personal Linkedin page, I’ll be delighted to answer them.

Useful resources

La Trésorerie active d’une entreprise

Banque-Trésorerie

Le Bilan d’une banque

Liquidité, solvabilité et crise bancaire : quelles relations ?

Diversification et gestion des risques

Les placements d’une Trésorerie d’entreprise

Le risque de taux

About the author

The article was written in March 2024 by Quentin CHUZET (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2019-2023).

Venture Capital 101: A Quick Overview

March 31, 2024March 27, 2024 by Alessandro MARRAS

Venture Capital 101: A Quick Overview

In this article, Alessandro MARRAS (ESSEC Business School, Global Bachelor in Business Administration (GBBA), Exchange Semester, September 2023-December 2023) gives a quick overview of Venture Capital.

What is Venture Capital?

Venture capital (VC) is a specialized form of financing where investors provide funds to startup or early-stage companies with high growth potential. This funding is crucial for startups to develop and expand their business operations. Venture capitalists not only provide financial support but also offer expertise and guidance to help these companies succeed. The goal of venture capital is to generate significant returns by investing in innovative businesses that have the potential to disrupt markets and achieve substantial growth.

VCs have five main functions:

They serve as financial intermediaries, channeling capital from investors into promising portfolio companies.
Their investments are directed towards private companies, making them illiquid assets.
VCs actively participate in the management and oversight of their portfolio companies, embodying active investors.
The primary objective of VCs is to maximize financial returns, typically through strategic exits like acquisitions or IPOs.
VCs prioritize investments in entrepreneurial ventures with substantial growth potential, aiming to foster internal growth and increase the likelihood of successful exits. These characteristics highlight the dynamic and strategic nature of venture capital investments, contributing to innovation and economic growth.

VCs vs others:

VCs differ from angel investors as they function as financial intermediaries rather than investing personal funds directly.
Unlike mutual or hedge funds, VCs invest specifically in private companies, placing them within the category of private equity and alternative investments.
While all VCs are private equity funds, the inverse isn’t true; not all private equity funds engage in venture capital.
VCs set themselves apart from crowdfunding platforms by actively participating in the companies they invest in, providing ongoing monitoring and management support.

How are VCs organized?

Venture capital firms are typically organized as limited partnerships, structured to facilitate investment activities while providing a degree of protection and incentive for both investors and managers. For investors this protection comes in the form of limited liability, meaning their risk of losing money is confined to their investment amount and they are not personally liable for the debts of the business. This allows them to invest in high-risk ventures with a capped downside. For managers the incentive is often structured as carried interest, a share of the profits of the investments, which aligns their financial interests with the success of the firm’s investments. This ensures that managers are motivated to select and nurture companies that will yield high returns, thereby directly linking their compensation to their performance in managing the venture capital firm’s portfolio.

Limited partnerships in venture capital consist of two main categories of partners. Firstly, there are limited partners, who contribute capital to the fund and bear limited liability. These investors can include wealthy individuals, banks, mutual funds, and other institutional investors. Secondly, there is the general partner, responsible for managing the fund’s operations and investments, and who assumes unlimited liability. Figures like Don Valentine, Ben Horowitz, and Peter Thiel are examples of notable general partners in the venture capital industry.

The lifespan of a typical limited partnership in venture capital is around ten years, during which investors’ capital is committed and cannot be withdrawn. General partners receive compensation in the form of a management fee and a share of the profits generated by successful investments, known as carried interest.

Limited partnerships offer tax efficiency, as they are not subject to corporate taxes, with partners instead paying taxes on their share of the profits. Additionally, distributions of securities to partners incur no immediate tax implications, with taxes only due upon the eventual sale of the securities.

This organizational structure provides a framework that incentivizes efficient investment management and aligns the interests of both limited and general partners in achieving successful outcomes.

Benefits of VC

Venture capital offers a range of benefits to both entrepreneurs and investors, fostering innovation, driving economic growth, and facilitating wealth creation. Firstly, venture capital provides crucial funding to startups and early-stage companies that may otherwise struggle to secure financing from traditional sources such as banks or public markets. This injection of capital enables entrepreneurs to pursue ambitious ideas and develop groundbreaking technologies, driving innovation across various industries. Moreover, venture capitalists often bring valuable expertise, networks, and mentorship to the table, helping startups navigate challenges, refine their business strategies, and accelerate their growth trajectory.

Secondly, venture capital plays a pivotal role in job creation and economic development. By supporting high-growth startups, venture capital investments fuel job creation, as these companies expand their operations, hire new talent, and contribute to local economies. Additionally, successful startups can spawn entire ecosystems of suppliers, service providers, and complementary businesses, further stimulating economic activity and driving regional prosperity.

Furthermore, venture capital investment offers attractive returns for investors willing to accept the inherent risks associated with early-stage ventures. While venture capital investments carry a higher risk of failure compared to traditional investments, they also offer the potential for substantial returns on successful exits, such as acquisitions or initial public offerings (IPOs). As a result, venture capital serves as a vital asset class for investors seeking diversification and opportunities for outsized returns in their investment portfolios.

VC Financing Cycle

The Venture Capital Financing Cycle delineates the sequential stages of funding that startups typically undergo, from inception to exit. This cycle starts with the Seed Stage, where initial capital is raised to prove concepts and build prototypes. As the startup matures, it may progress through various rounds of funding—Angel, Series A, Series B, and beyond—each designed to fuel growth, product development, market expansion, and operational scaling. The Bridge stage serves as a critical juncture for preparing more mature startups for substantial future rounds or positioning for exit strategies. The cycle culminates in the Pre-IPO and IPO Preparation stages, where companies ready themselves for public offering or seek acquisition opportunities, marking the exit phase. This framework not only structures the investment landscape but also maps the growth trajectory of startups. The VC financing cycle is emblematic of the symbiotic relationship between investors seeking to maximize returns and startups in need of capital to fuel their growth ambitions, fostering innovation and economic development within the broader ecosystem.

VCs financial performance in 2023

In 2023, the venture capital (VC) market experienced significant shifts, reflecting broader economic challenges and evolving investment trends. The year saw a considerable downturn in VC investments, dropping to the lowest levels in four years, with a year-over-year decrease of 35% from the already declining levels of 2022. The total amount raised by VC-backed startups barely surpassed $140 billion, influenced notably by a few mega-deals in the artificial intelligence (AI) sector. The decline was not just in the amount raised but also in deal volume across nearly all fund classes, reaching the lowest point in a decade. Later-stage investments saw the most significant reduction in dollar volume quarter-over-quarter, while Series A investments showed some resilience with a 9% increase.

The backdrop of economic headwinds, valuation concerns, and an overhang of more than 50,000 existing VC-backed startups created a challenging environment for new investments. VC fund formation also experienced a sharp decline, dropping 62% from the record year in 2022, although there was a slight uptick in the last quarter of the year. This situation has led to increased caution among venture capitalists, with a notable reluctance to engage in mega-round financing. Only 50 mega deals were recorded in the last quarter of 2023, marking the lowest total since 2017.

Despite these challenges, AI continued to garner significant attention and investment, driving many of the largest deals in the U.S. during the last quarter of 2023. This trend suggests that while the overall VC investment has declined, specific sectors, particularly those related to technological innovation and AI, continue to attract substantial interest and funding.

Why should I be interested in this post?

As an ESSEC students interested in finance, this post can be a useful resource due to its relevance in the financial sector. Understanding venture capital offers insights into alternative investments, career opportunities in private equity, and the dynamics of financing innovative startups, enriching your knowledge and potential career paths within the finance industry.

Useful resources

Zider B. (1998) How Venture Capital Works Harvard Business Review.

Jeffrey Grabow (29/01/2024) Will venture capital market rebound in 2024 or seek new floor? EY

KPMG Venture Pulse Q4 2023

Deloitte 2024 trends in venture capital

About the author

The article was written in March 2024 by Alessandro MARRAS (ESSEC Business School, Global Bachelor in Business Administration (GBBA), Exchange Semester, September 2023-December 2023).

Multiples valuation method for stocks

March 5, 2024 by Jorge KARAM DIB

Multiples valuation method for stocks

In this article, Jorge KARAM DIB (ESSEC Business School, Master in Strategy and Management of International Business (SMIB), 2024-2025) introduces the method to evaluate stocks called “multiples valuation”.

How much should a stock be worth?

Valuing stocks is a complex yet essential endeavor for investors seeking to make informed decisions in the financial markets. Knowing if you are paying a fair price or if you are over or under paying for a stock is every investors question. Of course, a decision on whether investing or not in a company comes after a long due diligence of valuating the financials of the company, following their reports, and many more actions to ensure you are buying something of value. Some investors call this method “value investing”, when the investor value a stock above the actual price, it is said that the type of investing is “value”, trying to take advantage of the differential between the actual price and the theoretical price. And when they buy a stock for a competitive advantage that is not expected in the near future to concede, it is usually called “growth investing”. Although some famous investors disagree in these definitions, they are used frequently in the financial language.

While there is no one-size-fits-all approach to valuing stocks, investors often turn to a range of methodologies, one of which is multiples analysis. By examining multiples such as price-to-earnings (P/E), price-to-book (P/B), and price-to-sales (P/S), and many more, investors gain insights into how the market values a company relative to its earnings, assets, or revenue. In this article we will try to shine a light on this valuating method and walk through the benefits and limitations the method has.

Multiples valuation method

Multiples valuation method involves analyzing one or more multiples, such as the price-to-earnings (P/E), price-to-book (P/B), and price-to-sales (P/S) ratios, among others. Each multiple provides a unique perspective on how the market values a company relative to its earnings, assets, or revenue.

The price-to-earnings (P/E) ratio, for instance, compares a company’s stock price to its earnings per share (EPS), indicating how much investors are willing to pay for each dollar of earnings generated by the company. A low P/E ratio may suggest that the stock is undervalued, while a high P/E ratio could indicate overvaluation.

One key aspect of this method is that it is usually compared against the ratios of companies within the same industry. It is from the investor’s criteria to decide which filters to apply for deciding against what companies the objective should be compared with, but usually it should be on the same market, region can also be an important factor, and also the size.

There are many sources of information to consult the information from, many of them free. This platform simplifies the valuation by providing not only the information, but in some cases, the ability to connect through an API and do the consulting automatically through a query. In the next image is shown an example from Capital IQ, one of the most prestigious information sources in the financial world, about Walmart and some recommendations from the platform of similar companies in the market to facilitate the calculation.

Walmart’s comparison.
Walmart
Source: Capital IQ.

Calculations

Calculating multiples involves straightforward mathematical formulas that utilize key financial metrics derived from a company’s financial statements. If we use the case for P/E, then we would need to divide the “Market price per share” with the “Earnings per share”. After getting the ratio, let’s say of Walmart, the next step is to get the median P/E for the “similar” companies that the investor decided to compare the company with. With these two values the investor can start seeing a trend on where the company is positioned versus their competitors. The next step is to calculate the price per share of Walmart using the P/E of the similar companies, and see the comparison between the price with the original P/E versus the “mean” of similar companies.

Example: Walmart

This section will be dedicated to illustrate the method explained earlier using Walmart as an example and Capital IQ as the source of information. The first step is to consult the key financials as shown in the next picture.

Walmart’s key financials.
Walmart financials
Source: Capital IQ.

Next, compute the information with the comparable companies suggested by Capital IQ. Important to note that the companies can be added or withdrawn according to everyone’s own criteria.

Comparable analysis.
Comparable companies
Source: Capital IQ.

After retrieving all the information, the next step is to do the calculations explained earlier in the document. The mean EV/EBITDA ratio for the comparable companies and then recalculate the price of Walmart’s stock using the mean EV/EBITDA ratio.

Mean EV/EBITDA ratio.

Source: Capital IQ.

Valuation of Walmart’s stock.

Source: Capital IQ.

In this case, we see an underappreciation of Walmart’s stock, this doesn’t mean that anyone shouldn’t buy stocks of the company, is just the perspective of the valuation method, and also it is not an investing advice.

Conclusions

The multiples valuation method provides investors with a valuable framework for assessing the worth of a stock by comparing it to similar companies within the same industry. By using this method, investors gain insights into how the market values a company relative to its earnings, assets, or revenue.

However, it’s important to recognize the limitations of this approach. Multiples analysis relies heavily on historical financial data and may not fully capture future growth prospects or qualitative factors such as industry dynamics and competitive positioning. Additionally, multiples are subject to fluctuations in market sentiment and may not always reflect the intrinsic value of a company accurately.

Despite these limitations, multiples analysis remains a widely used and valuable tool in the arsenal of investors. When applied judiciously and supplemented with thorough research and analysis, multiples can provide valuable insights into a company’s valuation and help investors identify potential investment opportunities.

Why should I be interested in this post?

This post is with the only intention for educational purposes. Targeting people who are interested in knowing more about valuation methods for stocks. In any way this article pretends to be an investment advice and/or suggestion. Any decision should be taken under personal responsibility and with their respective due diligence previous to the decision.

Useful resources

McKinsey & Company The right role for multiples in valuation

Chastenet E. and A. Marion (2015) Valuation Using Industry Multiples: How to Choose the Most Relevant Multiples, Business Valuation Review, 34(4): 173-183.

Schueler A. (2020) Valuation with Multiples: A Conceptual Analysis, Journal of Business Valuation and Economic Loss Analysis, 15(1) pp. 20190020.

About the author

The article was written in March 2024 by Jorge KARAM DIB (ESSEC Business School, Master in Strategy and Management of International Business (SMIB), 2024-2025).

Contracts for Difference

February 21, 2024 by Isaac ALLIALI

Contracts for Difference

In this article, Isaac ALLIALI (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2019-2023) explains the Contracts for Difference (CFD).

Understanding CFDs

Although banned in the US and for US citizens, the Contract for Difference (CFD) is a relatively new contract, introduced in the 1990s in Great Britain, to allow operators without permission to sell shares short, to speculate on the market’s decline. CFDs were originally based on equity swaps, which allow the exchange of the performance of a stock or stock index for an interest rate. Initially reserved for institutional investors, CFDs were later made available to individual investors and recognized by a directive from the European Union in 2004. Soon after, they gained popularity and rapidly developed in the OTC market. In contrast to centralized exchanges, the “Over The Counter” market facilitates trades directly between participants, offering flexibility for unique financial instruments and fostering niche investment opportunities. While lacking the structure of exchanges, OTC markets play a crucial role in diverse financing needs.

The contract for difference (CFD) is a very popular derivative, which essentially establishes a bilateral agreement between an investor and a broker. This contract does not grant the investor ownership of the underlying asset, but rather the right to receive the difference between the contract’s opening and closing price. Unlike contracts with an expiry date, a CFD is effectively renewed at the closing of each trading day and can be extended forward if desired; you can keep your position open indefinitely as long as there is enough margin in your account to maintain it.

In essence, contracts for differences are very similar to futures with no expiration date. While the contract remains open, your account with the provider will be debited or credited to reflect the interest and dividend alterations. The broker may offer leverage of up to 400 which serves as a powerful tool for amplifying possible financial gains (and losses). Through leveraging, the investor can gain control over a larger position than their initial capital would allow. For instance, if you have ‚Ç¨100 in your account and a leverage of 10, you take a position of ‚Ç¨1,000 (10*100).CFDs offer great flexibility to investors, CFDs provide investors with great flexibility, offering the ability to:

Speculate on a wide range of assets, including stocks, indices, currencies, commodities, etc.
Take advantage of market movements, whether upwards or downwards: enabling both buying and selling positions
Hedge an investment portfolio, using CFDs, which serve as a safeguard against price declines.
Execute advanced trading strategies.

Mechanics of CFD Trading

Opening a CFD position involves several steps. Firstly, traders choose an asset they wish to trade, such as stocks, commodities, or currencies. Secondly, they decide whether to go long (buy) or short (sell) on the asset, basing their decision on their market analysis and expectations for future price movements. Traders also determine the quantity of the asset they want to trade, which can be specified in terms of contracts or units, depending on the CFD provider. CFDs are not standardized products and every CFD broker has their own terms and conditions. Once the initial decisions have been made, the CFD provider calculates the price at which the trade will be executed. This price is typically derived from the market value of the underlying asset, taking into consideration various factors such as supply and demand dynamics, economic data, and market sentiment. The CFD provider may also incorporate a spread into the market price, which represents their profit margin. Margin requirements play a crucial role in opening and maintaining a CFD position. Traders are required to deposit a percentage of the total trade value as collateral, referred to as a margin. This ensures that traders can cover potential losses stemming from adverse price fluctuations. Margin requirements vary depending on factors such as the volatility of the underlying asset and regulatory requirements. Upon opening a position, the value of the CFD fluctuates in accordance to the underlying asset’s price movements. When traders decide to close their position, they execute an opposing trade to offset their initial position. The profit or loss from the trade is calculated based on the price difference between the opening and closing trades, adjusted for any transaction costs.

CFD trading involves various costs and fees that traders should be aware of. Spreads, representing the difference between buy and sell prices, are the primary revenue source for CFD providers and affect trading costs. Narrower spreads typically mean lower costs. Additionally, traders may face overnight financing charges for holding positions, which are influenced by factors such as the asset class and prevailing interest rates. Furthermore, some providers charge commissions on trades, based on elements such as the trading volume. Taking these costs into consideration is crucial for assessing overall profitability and developing effective trading strategies.

Application in the energy industry

NEOEN and BNRG have finalized the financing of three solar power plants in the Republic of Ireland: Hilltown, Hortland, and Millvale, located respectively in the counties of Meath, Kildare, and Wicklow. These plants, with a total capacity of 58 MWc, are among the first large-scale solar projects in the country. As the winners of the first governmental tender for solar power plants in 2020, they benefit from financial support from the Irish government through a Contract for Difference (CFD) mechanism until 2037, ensuring a stable price for the electricity generated. The financing, estimated at 39 million euros excluding financing costs, is provided by NEOEN and BNRG’s equity, alongside non-recourse senior debt from Société Générale. Construction works, awarded to Omexom, are expected to be completed in the first half of 2022,with plant commissioning set/scheduled for the same period. Once operational, these plants will supply the equivalent of 12,700 Irish households with clean electricity, thereby contributing significantly to the country’s energy transition.

Hilltown Solar farm

Source: BNRG

Millwale Solar farm

Source: BNRG

Useful resources

AMF Les CFD (contracts for difference)

BNRG

Neoen

Neoen (12/08/2021) Neoen et BNRG clôturent le financement de trois centrales solaires (58 MWc) en République d’Irlande

Dupuy, P., Fontaine, P. & Hamet, J. (2018). Chapitre 6. Les marchés dérivés et la gestion du risque. Dans : , P. Dupuy, P. Fontaine & J. Hamet (Dir), Les marchés de capitaux français (pp. 153-204). Caen: EMS Editions.

About the author

The article was written in February 2024 by Isaac ALLIALI (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2019-2023).

CumEx files

February 18, 2024 by Matthieu MENAGER

CumEx files

In this article, Matthieu MENAGER (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2017-2021) we take a look at the CumEx files scandal. The total amount of the fraud, according to the 19 media that revealed the affair (including Le Monde, Die Zeit and La Repubblica) amounts €140 billion.

CumCum & CumEx : What is the difference

CumEx and CumCum are two tax avoidance schemes that came to public attention in 2018. CumCum is considered a legal form of tax optimization, while CumEx is illegal. CumCum involves artificially transferring ownership of dividend-paying shares or securities, when dividends are paid out, to avoid tax. Foreign investors sell their shares back to domestic banks for what is often a very short time before receiving their dividends. These investors thus escape any levy and then recover their dividends, in return for a commission paid to the bank that temporarily housed their financial securities. The operation is so quick that the tax authorities are unable to identify the true owner of the securities. CumEx, on the other hand, consists of obtaining a tax refund on dividends that have never been paid. This practice is illegal and has cost European countries billions of euros.

The damage done by CumEx Files

Dividend fraud, known as “CumEx”, is a form of tax plunder estimated at €140 billion, last amount dating from 2022 (€33.3 billion for France; €28.5 billion for Germany; €27 billion for the Netherlands; €18.8 billion for Spain), as reported by FranceInfo (2021). Revealed in Germany, this fraud affected 11 countries (Germany, France, Spain, Italy, the Netherlands, Denmark, Belgium, Austria, Finland, Norway and Switzerland). Hanno Berger, a renowned lawyer, has devised a manipulation that involves buying and selling shares around the time of the dividend payment, so quickly that the tax authorities can no longer identify the true owner. The manipulation, which requires the agreement of several investors, enables the same dividend tax refund to be claimed several times over, thereby prejudicing the tax authorities.

The scam can be illustrated as follows:

CumCum

Tim from Frankfurt transfers his shares in a French company to Hugo, who lives in Dubai, where dividends are taxed at 0% under an agreement between Paris and Dubai, a few days before the dividend payment (Figure 1). The dividends are then paid by the French company to Hugo (Figure 2) and therefore has no dividend taxes to pay to the French state (Figure 3). The shares are then returned to Tim, who didn’t have to pay any taxes (a tax saving of 15 to 30%). The tax system in France for dividends is a flat tax of 30% and consists of a single flat tax of 12.8% and 17.2% social tax. Tim and Hugo may agree to share the tax saving between them (Figure 4).

Figure1. CumCum mechanism – First step:
CumCum mechanism - First step:
Source: The author.

Figure 2. CumCum mechanism – Second step:
CumCum mechanism - Second step:
Source: The author.

Figure 3. CumCum mechanism – Third step:

Source: The author.

Figure 4. CumCum mechanism – Fourth step:

Source: The author.

CumEx

Tim, Lea and Hugo will trade hundreds of thousands of shares over a very short period around the dividend payment date. The tax authorities will have no way of knowing who the real owner of the shares is and they’ll pay back taxes they haven’t even collected.

Figure 5. CumEx mechanism

Source: The author.

Who is implicated?

BNP Paribas, Société Générale, Natixis and Crédit Agricole (Cacib) are suspected of helping their customers to avoid paying tax on dividends. The resale and repurchase of shares, even for a short period, is in fact legal. On the other hand, the industrialisation of this practice to evade tax can be punished. In 2018, BNP Paribas, Crédit Agricole and Société Générale were among the French banks singled out by the “CumEx Files” investigation group for this type of practice.

In Germany, dozens of people have been charged (traders, bankers, lawyers, advisers). The Warburg bank in Hamburg is one of the banks accused and should have reimbursed 47 million euros to the German port city. The municipality waived this obligation in 2016. The investigators are therefore looking into whether political leaders – including Olaf Scholz, the city’s mayor at the time – put pressure on the municipal tax authorities to waive recovery of these taxes. The decision to waive repayment of the sums owed by the Warburg bank was apparently taken shortly after a conversation between Olaf Scholz and Christian Olearius, then head of the bank. Investigators discovered more than €200,000 in cash in a safe at the home of another SPD member of parliament, who may have played a role in the bank’s repayment, fuelling suspicions of possible secret financial arrangements.

At the end of March 2023, the French Parquet national financier (PNF – a national prosecutor’s office specializing in major economic and financial crime) launched a wave of searches. On May 2, before the French Senate, Gabriel Attal, Minister Delegate for Public Accounts, made public the total amount of reassessments notified to date by the tax authorities: €2.5 billion, according to L’Express. This bill, which includes penalties in addition to the amounts reassessed, concerns in particular the five banks targeted by the PNF searches (Société Générale, BNP Paribas and its subsidiary Exane, Natixis and HSBC), but also Crédit Agricole (which managed to avoid the search).

Financial concepts

Shares are part of a company’s equity when it is incorporated as a public limited company. It is therefore a source of financing for the company, in the same way as debt securities, from which, however, it differs clearly. It has an unlimited lifespan (it can only be disposed of by selling the share, and there is no contractual repayment), and its holder bears the full risk of the company (he or she receives no income if the company goes badly, and in the event of liquidation the shareholder takes second place to the creditor in the distribution of the proceeds from the sale of assets – in other words, most of the time he or she can recover nothing). In return, the share gives the holder the right to share in the company’s profits and management via voting rights.

Dividends

By definition, the dividend is defined as the shareholder’s income. This is the amount that a shareholder (owner of shares in a company) receives as a result of the profits generated by the company over a given period. The choice of dividend payment is made at the general meeting. At that time, distributable profits and available reserves are recorded.

Shareholders receive a dividend in two cases:

When there is a distributable net profit
But also when the company does not make a profit but wishes to draw on its reserves of cash to remunerate its shareholders.

Why should I be interested in this post?

CumEx Files is also a very recent scandal. What I find most shocking is that some very well-known banking institutions are also implicated in the scandal. Politicians (including the German Chancellor) are even suspected of involvement. So it’s worth taking a closer look at these affairs to understand how they worked.

Useful resources

Press articles

Le Parisien (21/10/2021) CumEx Files : la France a perdu 33 milliards d’euros de recettes fiscales en vingt ans

Le Monde (18/10/2018) « CumCum », « CumEx » : le scandale des dividendes expliqué simplement

Le Monde (15/05/2023) Scandale « CumCum » : le fisc réclame plus de 2,5 milliards d’arriérés fiscaux aux banques

L’Express (19/08/2022) Allemagne : tout comprendre au scandale “Cum-ex Files” qui éclabousse Olaf Scholz

France Info (21/10/2021) “CumEx Files” : ce que l’on sait du “pillage fiscal à 140 milliards d’euros” révélé par plusieurs médias

France 24 (21/10/2021) “CumEx Files” : Hanno Berger, le cerveau présumé du scandale aux 140 milliards d’euros

Le Monde (21/10/2021) « CumEx Files » : un pillage fiscal à 140 milliards d’euros, quatre banques françaises dans le viseur du fisc

Videos

Le Monde (18/10/2018) CumEx Files : comment arnaquer le fisc avec la Bourse

Zonebourse (31/03/2023) Comment les banques fraudent le fisc grâce aux dividendes (CumCum, CumEx)

The Dark Side of Money (15/02/2022) CumEx Files: Biggest TAX FRAUD in Europe

Explainitychannel (04/03/2020) Cum-ex deals explained

About the author

The article was written in February 2024 by Matthieu MENAGER (ESSEC Business School, Bachelor in Business Administration (BBA), 2017-2021).

Creating a portfolio of Conviction

June 4, 2024February 12, 2024 by Chloé ANIFRANI

Creating a portfolio of Conviction

In this article, Chloé ANIFRANI (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2019-2024) explains what it means to create a portfolio of conviction.

Conviction as a filter for your investment universe

In their article on Asset Allocation, Akshit GUPTA, an ESSEC student, defines the basics criteria considered by investors when building a portfolio. He defines them as the profile of the investor (risk profile, objective, time horizon), characteristics of the chosen assets (expected returns, risk, correlation), and chosen strategy of investing (strategic or tactical allocation).

Although those characteristics are what any good investor should consider in the first place, some other criteria might come into account. This is the case for portfolio used in thematic and conviction funds, which use particular quality filters to reduce their investment universe before taking a closer look at other characteristics in the highlighted assets.

In this article, we will only talk about equity assets (no bonds, structured products…).

For example, these filters might be geographic (global, European, American…), by capitalization (small, mid and large caps) or sector (technology, luxury, energy…).

Another type of filter seen in stock picking might be a conviction: after analyzing a company, the investor strongly believes that it shows a particular quality that makes it eligible for their portfolio.

The filter we will talk about today is one of those: Pricing Power.

Pricing Power is defined as the ability of a company to raise their prices without affecting the demand for their products, mostly thanks to specific technological invocation or patent, brand image and/or high barriers to entry for competitors.

This quality is often observed in sectors like luxury (LVMH, Hermès, Ferrari, Mercedes-Benz…), health (Cooper, Zoetis, medication for rare disease…) or aeronautics (Airbus Dassault…), for example. On the contrary, it is harder to find in sectors like energy, insurance or telecom, where many actors offer the same type of products and services.

Pricing Power in asset allocation: how can an analyst recognize Pricing Power in companies

Although Pricing Power is greatly influenced by sectors, as explained above, it also is company specific. Firms might possess technologies and innovations that allow them to showcase Pricing Power in a sector that isn’t known for it, while others may not be able to utilize their sector’s strength in a way that would lead to gaining Pricing Power.

Therefore, here are some characteristics that help recognize Pricing Power in companies (Louis Vuitton, Ferrari, Hermès, Atoss Software, Capgemini, Airbus, ASML, Safran, EssilorLuxottica, Disney, Netflix, L’oréal):

Brand strength

Companies with strong and well-established brands often have better Pricing Power. Consumers may be willing to pay a premium for products associated with a trusted and recognized brand.

Examples: Louis Vuitton, Ferrari, Hermès

Unique products or services, technological innovation

If a company offers unique or differentiated products or services that are not easily replicated by competitors, it may have greater control over pricing. This uniqueness can create a competitive advantage.

Examples: Atoss Software, Capgemini

High barriers to entry

If a company is established in a sector with high barriers to entry, like high cost of development or strict regulatory environment, it may showcase Pricing Power, as switching from this company to competitors might be difficult for customers in case of price increase.

Examples: Airbus, ASML, Safran

Market position

A leading market position or a dominant market share can provide Pricing Power. Market leaders often have more control over pricing, since customers may view their products as industry standards.

Examples: LVMH, EssilorLuxottica

Customer loyalty

High customer loyalty can enable a company to maintain Pricing Power. However, since customer loyalty derives from a feeling of trust between the client and brand, it shouldn’t be considered as a primary element to examine for investors, as too many raises in prices might negatively impact the relationship.

Examples: Disney, Netflix

Track record of price increases

Examining a company’s historical ability to implement price increases successfully can provide insights into its Pricing Power. Consistent or periodic price increases without significant negative effects on sales would be a positive indicator.

Examples: L’oréal, Louis Vuitton, Hermès

It is important to note that elements like cost advantages (economies of scale, economies of scope, relationship with manufacturers…) do not lead to pricing power, but to margin control, which would be another type of filter.

The case of luxury: intangibles in Pricing Power

To better understand how Pricing Power evolves for brands, let’s talk about the case of luxury today.

In 2022 and 2023, the market has been shaken by the new hawkish monetary policy declared by central banks, with interest rates raising at a rapid pace and to a level that had not been seen for many years.

This new reality led to difficulties for firms which relied heavily on debt to finance their activities.

In the case of the luxury sector, our new situation of “Higher for longer” rates lead to a strengthening of the already existing barriers to entries. Firms that have been major actors in this field for decades (LVMH, Kering, Hemes, Richemont…) should see fewer young brands emerging to their levels for the years to come.

It is interesting to note that those actors’ Pricing Power comes primarily from their brand image. This component helps them to sustain an “asset light” growth, which doesn’t require much investment in new technologies or patents on their parts.

However, an investor might worry that the current inflation and reduction of houses’ purchasing power might affect demand on luxury products, that are often not primary necessities.

Indeed, if 2022 was a particularly good year for the sector (9-11% annual growth), its trajectory has slowed down in 2023, coming back to average historical levels (7-8%). The major actors, who raised their prices significantly in 2022 and 2023, already plan more moderate raises for the years to come.

Those elements should be considered by an investor interested in Pricing Power. However, they do not invalidate it for the sector. We notice two elements that are in its favor for the upcoming years: the consumption of luxury goods is becoming more and more concentrated on the most “iconic” brands (Hermès, Chanel, Louis Vuitton…) and the number of clients is increasing steadily every year. In 2023, there were 400 million of luxury consumers. 50 million of them where millionaires, which is interesting to note, knowing how polarized this sector consumption is: 1% of the customers equals 20% of the total sales. This means that the main luxury consumers are the least affected by the current drop in purchasing power.

With this information and the previously stated higher barriers to entry, we can consider that the current state of the market might actually be beneficial to the luxury sector’s main actors’ Pricing Power.

Funds and ETFs with Pricing Power at their core

To conclude this article, we will cite some funds that have been basing their investment strategies around Pricing Power.

We selected three of these funds, all primarily invested in Eurozone. The funds are Delubac Pricing Power I (FR0011304229), Pictet Premium brands I (LU0217138485, also invested in the US) and Amplegest Pricing Power (FR0010889857).

Top 10 Delubac Pricing Power.
Delubac PP top 10
Source: Morningstar.

Top 10 Pictet Premium Brands.
Pictet PB top 10
Source: Morningstar.

Top 10 Amplegest Pricing Power.
Amplegest PP top 10
Source: Morningstar.

While examining their top 10 stocks, it is interesting to note that some brands, well-established as having Pricing Power, can be found in all three allocations (LVMH, L’Oréal, Linde).

For your information, here are the funds’ performances over the last five years, compared to their zone of investment’s.

Performances over 5 years
PP funds 5y track
Source: Quantalys.

Performances in 2023
PP funds 2023
Source: Quantalys.

Annual Performances from 2017
PP funds perf from 2017
Source: Quantalys.

And yes, investing with conviction can be rewarding and a great way to differentiate your product, but it doesn’t always beat the market!

Why should I be interested in this post?

If you wish to work in Asset Management, as an analyst or funds manager, or as a customer, this post will help you understand what kind of criteria might be used to do so. Asset Managers sell a product, not just a track record, and it is important to know how to build a portfolio around a concept in order to differentiate yourself on a very saturated market!

Useful resources

Pricing Power is the magic ingredient for equity investors

JP Moorgan Combating inflation with pricing power

Morgan Stanley Combating inflation with pricing power

About the author

The article was written in February 2024 by Chloé ANIFRANI (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2019-2024).

Discovering Private Equity: Behind the Scenes of Fund Strategies

March 25, 2025February 10, 2024 by Lilian BALLOIS

Discovering Private Equity: Behind the Scenes of Fund Strategies

In this article, Lilian BALLOIS (ESSEC Business School, Bachelor in Business Administration (BBA), 2019-2023) explains about Private Equity fund strategies.

Reminder: What is Private Equity?

Private Equity entails investors directing capital into privately held enterprises that are not publicly traded on stock exchanges. Private Equity firms manage investors’ funds, which are utilized to secure ownership stakes in these companies, fostering their growth, innovation, or resolution of financial challenges. In exchange, investors anticipate yielding profits upon exiting the investment, typically within a span of 5 to 8 years.

Private equity thus offers a way for companies to receive strategic financing and for investors to earn returns on their investments, in an alternative way to traditional investments.

But how do you know which funds to invest in?

Decoding Success: How to choose the perfect Private Equity Investment Strategy

Aligning Investments with the Company Lifecycle

Private equity investments are aligned with various stages of a company’s lifecycle (Cf. chart below). In the early stages, venture capital provides funding for startups to assist in innovation and growth. As companies mature, growth equity offers expansion capital to fuel further development and market penetration. In the maturity stage, private equity often engages in leveraged buyouts (LBOs) to acquire established companies, implementing operational enhancements and strategic changes to boost efficiency and profitability. Finally, distressed capital may be deployed to support struggling businesses, offering resources and expertise to facilitate turnaround efforts.

Company life cycle.

Source: The author

Venture Capital: at the Introduction Phase

Venture Capital is a private equity and financing approach focused on supporting early-stage startups and high-potential businesses. Investors, including affluent individuals, investment banks, and angel investors, contribute funds to fuel the growth of these companies. Apart from monetary contributions, investors may also offer technical or managerial expertise. An illustrative example of Venture Capital at work is Uber, which in 2010 received its initial major funding of $1.3 million led by First Round Capital. Shortly after, in early 2011, it raised $11 million in a Series A funding round led by Benchmark. With these funds, Uber expanded its operations to various cities in the United States and abroad, including Paris, where the concept originated. By December of 2011, Uber secured $37 million in Series B financing from Menlo Ventures, Jeff Bezos, and Goldman Sachs, further fuelling its global expansion and technological advancements.

Growth Equity: at the Growth Phase

Growth equity is a less speculative form of financing, aids companies in their expansion phase. Unlike venture capital, growth equity is directed at already profitable and mature businesses with minimal debt. This type of funding, commonly involving minority ownership through preferred shares, facilitates strategic business growth, such as entering new markets or acquiring other companies, with a balanced risk-return profile. Adyen, a prime example, initially self-funded, but experienced exponential growth after securing $250M in Series B funding led by General Atlantic in 2014. This injection of capital significantly accelerated Adyen’s trajectory, leading to its successful IPO on Euronext in June 2018, with a market capitalization of €7.1B. Adyen’s subsequent revenue surge to €721.7 million in 2022 further underscores the potency of growth equity in fuelling sustained business growth.

Leveraged Buyouts & Management Buyouts: during the Maturity Phase

Leveraged Buyouts

Leveraged Buyouts (LBOs) funds combine investment funds with borrowed capital to acquire companies, aiming to enhance profitability. By leveraging creditors’ and investors’ money, the fund manager has more capital to purchase larger companies, either outright or by securing a majority stake for strategic control. The term “leveraged buyout” reflects the use of borrowed funds to afford larger acquisitions, potentially resulting in substantial returns if the strategies pay off. An instance of an LBO is Elon Musk’s acquisition of Twitter, Inc. Despite initial resistance from Twitter’s board, who employed a “poison pill” strategy to deter hostile takeovers, Musk’s persistent pursuit led to the acceptance of his buyout offer of $44 billion on April 25.

Management Buyouts

Management Buyouts (MBOs) are transactions in which the existing management team of a company acquires a significant ownership stake or complete ownership of a business. In a MBO, the current managers collaborate with a private equity firm to purchase the business from its existing owners. This transaction is common when a company’s management team believes they can run the business more effectively or exploit growth opportunities better than the current ownership structure allows. The MBO of Dell Inc. in 2013 stands out as one of the largest and most significant in history. With a valuation reaching approximately $24.9 billion. The company’s founder, Michael Dell, partnered with Silver Lake Partners to reclaim control of the company he had founded. The move allowed Dell to implement long-term strategies and make pivotal decisions without the immediate pressures of quarterly earnings reports, facilitating a more nimble and adaptable approach to the rapidly evolving tech landscape.

Distressed Capital: at the Decline Phase

Distressed capital consists in lending to companies facing financial crises and to take control of businesses during bankruptcy or restructuring processes. The strategy involves purchasing distressed companies at a lower price, turn them around, and eventually sell them. Distressed capital carries inherent risk due to investing in financially challenged companies. For example, in May 2020, Hertz Global Holdings, filed for Chapter 11 bankruptcy due to the impact of the COVID-19 pandemic on its business, which saw a significant decline in travel demand. During its bankruptcy proceedings, Hertz secured funding from distressed debt investors to support their operations and restructuring efforts. This financing came from a consortium of lenders and institutional investors, providing Hertz with the liquidity needed to continue operations, pay essential expenses, and navigate the bankruptcy process.

Timeless Investing: Optimizing Portfolios through Vintage Year Diversity

What are “Vintage Years”?

“Vintage years” refer to specific time periods during which a fund was raised or initiated. Each vintage year represents a cohort of funds that were raised and deployed within a similar timeframe. These vintage years are often used by investors and analysts to track the performance of funds over time, as funds raised in the same vintage year may encounter similar market conditions and economic environments, which can affect their overall performance and returns.

Mitigating market cycles

Private equity has demonstrated superior performance compared to public equity throughout market cycles. However, returns are subject to fluctuations based on the phase of the business cycle. For instance, if a fund initiates investments during a downturn, it is likely to encounter a broader array of distressed and undervalued assets, with the potential for profitable exits when the market peaks. Conversely, a fund entering the market at its highpoint may face challenges as assets are likely to be expensive and may risk undervaluation upon entering public markets during the exit phase.

Given the unpredictability of market timing, diversification across vintages serves as a strategic approach to dampen this cyclical risk. This approach aims to create a more stable return profile that mirrors the overall characteristics of the asset class.

Establishing a self-sustaining portfolio

Company life cycle.
Self-funding Portfolio
Source: The author

As written above, funds can diversify through various vintages. This strategy allows to generate returns from an earlier vintage, which are reinvested as commitments for a subsequent vintage. In doing so, a self-funding portfolio is cultivated, steadily appreciating in value over time.

Exploring Sectors of Private Equity Investments

In 2023, technology continued to lead private equity investments, capturing a significant 31% share of total investments. Cloud-related ventures, especially enterprise Software as a Service (SaaS), remained appealing, fueled by expectations of sustained growth. Additionally, the rapid adoption of machine learning, driven by global enterprises integrating generative Artificial Intelligence (GenAI) into operations, signaled a broader trend towards innovation.

Consumer-focused investments, accounting for 14% of total investments, saw a focus on low-risk ventures in the food and agribusiness sector. Sustainable farming, combined agriculture, and timber ventures stood out, driven by increasing emphasis on environmental sustainability and responsible resource management.

In addition, financial services (11%) and health sectors (9%) saw significant private equity activity. In finance, investments spanned various subsectors, reflecting a pursuit of diverse opportunities. Meanwhile, health sector niches like enterprise imaging solutions and voice-based diagnostics attracted attention, driven by innovation in medical technology platforms, highlighting the sector’s transformative potential.

PE deals by sector.
Sectoral Share in Private Equity Deal Values
Source: Moonfare

The private equity landscape in 2023 featured a diverse range of investment opportunities, with technology dominating while consumer, financial services, and health sectors also drew significant interest, providing distinct pathways for growth and value generation.

Why should I be interested in this post?

This post offers a comprehensive overview of private equity investing. It defines private equity and explores various investment strategies such as venture capital, growth equity, leveraged buyouts, management buyouts, and distressed capital, providing practical insights into their roles at different stages of a company’s lifecycle. Additionally, the post discusses the concept of vintage years and their significance in tracking fund performance over time, highlighting the importance of portfolio diversification and risk management.

▶ Louis DETALLE A quick presentation of the Private Equity field…

▶ Louis DETALLE A quick review of the Growth Capital…

▶ Louis DETALLE A quick review of the Venture Capitalist’s job…

▶ Matisse FOY Key participants in the Private Equity ecosystem

▶ Marie POFF Film analysis: The Wolf of Wall Street

Useful resources

Academic References

Martin, J. and R. Manac (2022) Varieties of funds and performance: the case of private equity, The European Journal of Finance, 28(18) 1819–1866.

EVCA (2007) Guide on Private Equity and Venture Capital for Entrepreneurs

Caselli, S. and M. Zava (2022) Private Equity and Venture Capital Markets in Europe

Specialized Press

Investment Strategies in private equity

Barber F. and M. Goold (2023) The strategic secret of private equity Harvard Business Review

Private Equity Pulse: key takeaways from Q4 2023

Financial Times Private Equity

Wall Street Journal Private Equity

About the author

The article was written in February 2024 by Lilian BALLOIS (ESSEC Business School, Bachelor in Business Administration (BBA), 2019-2023).

Datastream

Introduction

History

Uses of Datastream

Investment Research

Economic Analysis

Portfolio Management

Academic Research

Financial Reporting

Advantages of Datastream

Challenges of using Datastream

Conclusion

Why should I be interested in this post?

Related posts on the SimTrade blog

Other financial data

Useful resources

About the author

S&P Global Market Intelligence

Introduction

History

Key Components of S&P Global Market Intelligence

Earnings Estimates

Revenue Projections

Forecasts for Key Financial Metrics

Coverage

Period

Frequency

Firms and Financial analysts

Pricing

Use of S&P Global Market Intelligence by the Financial Community

Benchmark for Analysis

Market Expectations

Earnings Season Preparation

S&P Global Market Intelligence and Tests of Market Efficiency

Academic works

Information Dissemination

Pros and Cons

Conclusion

Why should I be interested in this post?

Related posts on the SimTrade blog

Useful resources

About the author

Zacks Investment Research

Introduction

History

Key Components of Zacks Investment Research

Earnings Estimates

Model portfolio

Forecasts for Key Financial Metrics

Coverage

Period

Frequency

Firms and Financial analysts

Pricing

Use of Zacks Investment Research by the Financial Community

Benchmark for Analysis

Market Expectations

Earnings Season Preparation

Zacks Investment Research and Tests of Market Efficiency

Academic works

Information Dissemination

Pros and Cons

Conclusion

Why should I be interested in this post?

Related posts on the SimTrade blog

Useful resources

About the author

Structured Debt in Private Equity: Rated Feeder Funds and Collateral Fund Obligations

Structured Financing for Investment

Why are CFOs and RNFs attracting insurance companies?

Regulatory Considerations and Risk Mitigation

Conclusion: Balancing Innovation with Regulatory Compliance

Example of precedent transaction: Tikehau raise a $300 million CFO

Why should I be interested in this post?

Related posts on the SimTrade blog

Useful resources

About the author

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