Top 5 companies by market capitalization in the US

March 26, 2024June 28, 2023 by Nithisha CHALLA

Top 5 companies by market capitalization in the US

In this article, Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management, 2021-2023) presents the top 5 companies by market capitalization in the US.

Introduction to market capitalization

Market capitalization, often referred to as “market cap,” is a key metric used in the financial world to assess the size and value of a publicly traded company. Market capitalization provides insights into a company’s position in the market and its relative size compared to other companies. It is a measure of a company’s total market value, calculated by multiplying its current stock price by the total number of outstanding shares.

Market capitalization is an important indicator for investors, analysts, and market participants as it reflects the perceived worth of a company by the investing public. Note that market capitalization assesses the size of the company in the equity market, but the total value of the company measured by its assets or the sum of its liabilities and shareholders’ equity may larger if the company uses debt (financial leverage).

The top 5 corporations in the US market according to market capitalization by 2023 are as follows:

1) Apple Inc.
2) Microsoft Corporation
3) Amazon.com, Inc.
4) Alphabet Inc. (formerly Google)
5) Meta Platforms Inc. (formerly Facebook Inc.)

By looking at these top 5 companies, we observe that these companies mainly belong to the technology sector.

We detail below the characteristics of each company: statistics, analysis of revenues, and stock market data.

#1 Apple Inc.

Logo of Apple Inc.

Source: the company.

Statistics (2023)

Market capitalization: $2,514 billion
Inclusion in stock market indexes: NASDAQ-100, S&P 500
Listing on stock exchanges: NASDAQ
Industry: Technology (Consumer Electronics)
Location of headquarters: Cupertino, California, United States
Year founded: 1976
Number of employees: 164,000

Revenues

Apple is a multinational technology company that designs, manufactures, and sells consumer electronics, software, and online services. It is best known for its iconic products such as the iPhone, iPad, Mac, and Apple Watch. The company has a strong ecosystem of hardware, software, and services, including the App Store, Apple Music, iCloud, and Apple Pay. Apple has a reputation for innovation and user-friendly designs, and it has a loyal customer base worldwide.

Stock chart

Stock chart for Apple Inc.

Source: Yahoo! Finance.

The historical data for Apple stock prices can be downloaded from Yahoo! Finance website: Download the data for Apple

#2 Microsoft Corporation

Logo of Microsoft Corporation

Source: the company.

Statistics (2023)

Market capitalization: $2,066 billion
Inclusion in stock market indexes: NASDAQ-100, S&P 500
Listing on stock exchanges: NASDAQ
Industry: Technology (Software)
Location of headquarters: Redmond, Washington, United States
Year founded: 1975
Number of employees: 221,000

Revenues

Microsoft is a multinational technology corporation that develops, manufactures, licenses, supports, and sells computer software, consumer electronics, personal computers, and related services. It is widely known for its flagship products such as the Windows operating system and Microsoft Office suite. The company has expanded into various other technology sectors, including cloud computing (Azure), gaming (Xbox), and enterprise software (Microsoft Dynamics). Microsoft has a strong presence in both consumer and enterprise markets.

Stock chart

Stock chart for Microsoft Corporation.

Source: Yahoo! Finance.

The historical data for Microsoft stock prices can be downloaded from Yahoo! Finance website: Download the data for Microsoft Corporation

#3 Amazon Inc.

Logo of Amazon

Source: the company.

Statistics (2023)

Market Capitalization: $1,011 billion
Inclusion in stock market indexes: NASDAQ-100, S&P 500
Listing on stock exchanges: NASDAQ
Industry: Retail (E-Commerce), Cloud Computing
Location of headquarters: Seattle, Washington, United States
Year founded: 1994
Number of employees: 1,465,000

Revenues

Amazon.com, Inc. is an American multinational conglomerate that focuses on e-commerce, cloud computing, digital streaming, and artificial intelligence. It is the world’s largest online marketplace and offers a wide range of products and services through its websites and platforms. Amazon’s services include Amazon Prime, Amazon Web Services (AWS), Kindle e-readers, and Amazon Echo devices. The company has also ventured into other areas, such as entertainment production and grocery retail. Amazon has experienced significant growth and expansion since its inception.

Stock chart

Stock chart for Amazon Inc.

Source: Yahoo! Finance.

The historical data for Amazon stock prices can be downloaded from Yahoo! Finance website: Download the data for Amazon

#4 Alphabet Inc. (formerly Google Inc.)

Logo of Alphabet

Source: the company.

Statistics (2023)

Market Capitalization: $1,356 billion
Inclusion in stock market indexes: NASDAQ-100, S&P 500
Listing on stock exchanges: NASDAQ
Industry: Technology (Internet Services)
Location of headquarters: Mountain View, California, United States
Year founded: 1998
Number of employees: 190,711

Revenues

Alphabet Inc. is a multinational conglomerate that serves as the parent company of Google and several other subsidiaries. Google, as a subsidiary of Alphabet Inc., is a technology company that generates a significant portion of Alphabet’s overall revenues. While specific revenue figures for Google are not provided separately in Alphabet’s financial reports, Google’s advertising business constitutes the majority of Alphabet’s revenue stream. Google primarily generates revenue through its advertising platforms, including Google Search, YouTube, Google Display Network, and Google Ads.

Stock chart

Stock chart for Alphabet Inc.

Source: Yahoo! Finance.

The historical data for Amazon stock prices can be downloaded from Yahoo! Finance website: Download the data for Alphabet

#5 Meta Platforms Inc. (formerly Facebook Inc.)

Logo of Meta

Source: the company.

Statistics (2023)

Market capitalization: $529 billion
Inclusion in stock market indexes: NASDAQ-100, S&P 500
Listing on stock exchanges: NASDAQ
Industry: Technology (Social Media)
Location of headquarters: Menlo Park, California, United States
Year founded: 2004
Number of employees: 86,482

Revenues

Meta Platforms Inc., previously known as Facebook Inc., is a social media and technology company that focuses on connecting people and enabling social interactions. The company operates various social networking platforms, including Facebook, Instagram, WhatsApp, and Messenger. These platforms offer users the ability to share content, communicate with others, and engage in online communities. Meta Platforms Inc. also provides advertising and marketing solutions to businesses, leveraging the vast user base of its platforms. The company has expanded into areas such as virtual reality (Oculus) and artificial intelligence research. It plays a significant role in shaping the digital landscape and has a global user reach.

Stock chart

Stock chart for Meta Platforms

Source: the company.

The historical data for Meta Platforms stock prices can be downloaded from Yahoo! Finance website: Download the data for Meta Platforms

Why should I be interested in this post?

As a management student, understanding the top companies in different markets and their market capitalization holds significant value. It provides you with industry insights, allowing you to comprehend the competitive landscape and trends within specific sectors.

Analyzing market capitalization aids in investment analysis, enabling you to assess the size, growth potential, and financial health of companies. Moreover, studying successful companies (success being measured by their market capitalization) provides valuable lessons in competitive strategy, organizational management, and leadership practices.

Useful resources

Companies Market Cap Largest American companies by market capitalization

Yahoo! The 30 Largest Companies on the Stock Market

About the author

The article was written in June 2023 by Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management, 2021-2023).

Market Capitalization

June 28, 2023 by Nithisha CHALLA

Market Capitalization

In this article, Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management, 2021-2023) explains Market Capitalization and its specificities.

What is Market Capitalization?

Market capitalization is a key metric used to assess the size and value of publicly traded companies. It represents the company’s value for the owners of the company (the shareholders or stockholders). This metric allows companies to be classified as large-cap, mid-cap, or small-cap based on their respective market-capitalization sizes.

Large-cap companies are typically more established, with market capitalizations exceeding several billion dollars. They are more stable and frequently represent industry leaders. In the US stock market, Apple, Microsoft, and Amazon are examples of large-cap companies.

Mid-cap companies fall between large-cap and small-cap companies. They are typically businesses that have seen moderate growth and may still have room for expansion. Mid-cap companies are frequently regarded as having a good balance of growth potential and stability. For example, Etsy Inc., DocuSign Inc., Spotify Technology S.A. etc.

Small-cap companies have lower market capitalizations than large-cap and mid-cap firms. They are generally thought to have greater growth potential, but also greater risk due to their smaller size and possibly limited resources. NeoGenomics, Inc., Clean Energy Fuels Corp., Axon Enterprise Inc. etc.

Mathematical formula?

The general formula for calculating market capitalization:

Market Capitalization = Current Share Price x Number of Outstanding Shares

In this formula:
“Current Share Price” refers to the price of a single share of the company’s stock. It is the latest transaction price. As Market Capitalization is usually computed every day, the current share price corresponds to the closing price of the trading session.

“Number of Outstanding Shares” represents the total number of shares of the company’s stock that are publicly available and held by investors.

The Significance of Stock Price

When considering market capitalization, the stock price is an important factor to consider. It represents the current market price at which a company’s shares are bought and sold. Stock prices, which are influenced by factors such as supply and demand, market sentiment, and company-specific news, play a critical role in determining a company’s market capitalization.

On the short term, as the number of shares issued by the company is stable, the stock price is the main factor which influences market capitalization.

How is the Number of Shares Computed?

The total number of outstanding shares of a company’s stock is used to calculate market capitalization. The outstanding shares are those that the company has issued and are held by shareholders, which include individual investors, institutional investors, and insiders.

The number of outstanding shares can be found in the company’s financial statements, specifically the balance sheet and the notes to the financial statements.

Which Shares are Included?

The outstanding shares generally include common shares or ordinary shares, which are the most common types of shares issued by companies. Preferred shares or other types of securities that may have different rights or characteristics are typically excluded from the calculation of market capitalization.

When we compute market capitalization, we take into consideration all outstanding shares of stock, which include publicly traded shares plus restricted shares held by the top management team and the founders of the company. Note that market capitalization is different from the float which takes into consideration only the shares available for trading in the secondary market.

If a company has different classes of shares with different voting rights or other characteristics, each class of shares may have its own market capitalization calculation based on the respective share price and the number of outstanding shares for that class.

Market capitalization provides an estimate of the overall value of the publicly traded portion of a company and is commonly used as a measure to compare companies or track changes in a company’s value over time.

Why should I be interested in this post?

Understanding market capitalization allows management students to analyze the financial health and performance of companies. By considering market capitalization along with other financial indicators, students can assess the relative size and value of companies in the market. Management students need to evaluate investment opportunities and determine the attractiveness of different stocks or companies based on their market capitalization and growth potential. Large-cap companies often offer stability and lower risk, while small-cap companies tend to be riskier but may have higher growth potential. Management students need to understand the risk-return tradeoff associated with different market capitalization segments.

Useful resources

Fidelity Investments Market capitalization

Wikipedia Market capitalization

Motley Fool An Example of Market Capitalization

About the author

The article was written in June 2023 by Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management, 2021-2023).

My experience as a trading floor intern at CIC Market Solutions

June 22, 2023 by Tanguy TONEL

My experience as a trading floor intern at CIC Market Solutions

In this article, Tanguy TONEL (ESSEC Business School, Global BBA, 2019-2023) shares his professional experience as an intern at the Bordeaux trading floor of CIC.

About CIC Market Solutions

Logo of the CIC Market Solutions.
Logo of CIC Market Solutions
Source: CIC Market Solutions

My internship

I joined the trading floor of CIC Sud-Ouest (the South-West branch of CIC) which is divided in two desks (FICC – Fixed Income, Currencies and Commodities, and asset management) to provide personalized advice to local corporate clients for their investments and risk management. There, I assisted sales and asset managers in their daily duties.

My missions

As an intern, my tasks were very diverse as I have been assisting both FICC and asset management desks. In a day, I would operate the trades reconciliation, monitor the limit orders execution for the sales traders, research and analyze data for the asset managers in preparation of client meetings and do reporting to track the performance of investments. Finally, I helped with management control and middle office tasks such as new clients’ registration.

Required skills and knowledge

While some technical skills such as Excel/VBA are welcomed, the most important skill to have is curiosity. Indeed, as financial markets are constantly evolving it is important to look for anything that can help explain any change, whether in the products’ performances, in the regulatory environment or in clients’ demand to react proactively.

What I learned

During the internship, I learned about the financial solutions provided by a trading floor. On the FICC desk, I was exposed to derivatives and other complex products. On the asset management desk, I discovered the world of EMTNs (Euro Medium Term Notes) which are structured products.

Overall, the internship allowed me to get a broader understanding of the financial markets as I could see the impacts of the markets and the broader economy on clients’ needs, and the impact of client’s needs on the type of products offered by the bank.

Financial concepts related my internship

EMTNs

Euro Medium Term Notes (EMTNs) are a type of debt security that is issued by large corporations, financial institutions, and sovereign governments to raise funds for financing purposes (so the bank can loan money). EMTNs are similar to traditional bonds in that they pay a fixed or floating rate of interest and have a maturity date. One of the key advantages of EMTNs is their flexibility. They can indeed be tailored to meet the specific needs of investors. In practice, the structurers can work on guaranteeing the capital, on the yield… They usually obey rules (such as “The EMTN pays 7% per year for 3 years, then the spread between a rate and another. When the EMTN has paid 22% or at the end of the seventh year, the product ends, and the investor gets his or her capital back.”).

Derivatives

Financial derivatives are financial instruments used to manage risk. They derive their value from an underlying asset or group of assets. Derivatives can be sold for a wide range of assets such as interest rates, currencies and commodities, which are traded by the FICC desk.

There are several types of financial derivatives. The best-known include futures contracts, options contracts, swaps, and forwards.

Futures contracts are agreements to buy or sell an asset at a predetermined price and date in the future.
Options contracts give the holder the right, but not the obligation, to buy or sell an asset at a predetermined price and date in the future.
Swaps are agreements to exchange cash flows based on different financial instruments, such as interest rates or currencies.
Forwards are similar to futures contracts, but they are customized agreements between two parties rather than standardized contracts traded on an exchange.

Structured products

Structured products are financial instruments that are created by combining multiple financial assets, such as stocks, bonds, and derivatives, into a single investment product. These products are designed to meet specific investment objectives, such as providing income, capital protection, or exposure to a particular market or asset class.

Structured products are typically created by financial institutions, such as banks or investment firms, and are sold to investors. They can be customized to meet the specific needs of individual investors and can be structured to provide a range of risk and return profiles.

Some common types of structured products include:

Principal-protected notes: These products provide investors with a guaranteed return of their initial investment, while also offering exposure to the performance of an underlying asset or index.
Autocallable notes: These products provide investors with a fixed income stream, while also offering the potential for higher returns if an underlying asset or index meets certain performance criteria.
Reverse convertibles: These products provide investors with a fixed income stream, while also exposing them to the risk of a decline in the value of an underlying asset or index.

Why should I be interested in this post?

The trading floor is the link between the financial markets and the rest of the business world. Understanding the products offered allows one to get a better grasp on both sides of the economy.

Useful resources

Academic resources

Hull J.C. (2021) Options, Futures, and Other Derivatives Pearson, 11^th Edition.

Business resources

CIC Market Solutions

About the author

The article was written in June 2023 by Tanguy TONEL (ESSEC Business School, Global BBA, 2019-2023).

My experience as an Investment Specialist at Amundi Asset Management

June 22, 2023 by Tanguy TONEL

My experience as an Investment Specialist at Amundi Asset Management

In this article, Tanguy TONEL (ESSEC Business School, Global BBA, 2019-2023) shares his professional experience as an investment specialist in the ETF, Smart Beta & Indexing division of Amundi Asset Management.

About Amundi Asset Management

Amundi Asset Management is a leading global asset manager with over €1.7 trillion in assets under management as of December 31, 2022. The company was founded in 2010 as a joint venture between Crédit Agricole and Société Générale and has since grown to become one of the largest asset managers in Europe.

Amundi offers a wide range of investment solutions across all major asset classes, including equities, fixed income, multi-asset, and alternative investments. The company serves a diverse client base, including institutional investors, corporations, and individual investors.

Logo of Amundi.

Source: Amundi

My internship

I joined the Investment Specialist team of the ETF, Smart Beta & Indexing division which works as a facilitator for the asset management and the sales teams. The team answers clients on the most technical questions and their due diligence inquiries, applies to calls for tenders, monitors the market and does the reporting of the funds.

My missions

During my internship, I shadowed the team, helping them on a broad variety of their tasks.
Among those, I worked on the reporting of the funds, researching data to answer clients’ questions and on drafting sales offers for calls for bids. Additionally, I documented the tools used by the team in their daily activity which allowed me to get involved in nearly all the team’s duties.

Required skills and knowledge

While some technical skills such as Excel/VBA are welcomed, the most important skill to have is curiosity. Indeed, as financial markets are constantly evolving it is important to look for anything that can help explain any change, whether in fund performance, in the regulatory environment or in clients’ demand to react proactively. The ability to adapt is crucial, tools change.

What I learned

During the internship, I have been able to learn a lot about passive management. Indeed, the funds offered by Amundi are very diverse and allowed me to discover the concept of Smart Beta, how indices are built and replicated by asset managers, how ESG rules are incorporated into funds…

Financial concepts related my internship

Passive asset management

Passive asset management is an investment strategy that seeks to replicate the performance of a market index or benchmark. It involves investing in a diversified portfolio of securities that closely mirrors the composition of a particular index.

Usually replicated by index funds or ETFs, the indices follow different kind of rules in their composition while the asset managers work to replicate them without getting involved in the composition.

Physical and Synthetic ETFs

There are two main ways that an ETF can replicate an index: physically and synthetically.

A physically replicated ETF holds all or a representative sample of the securities in the index it tracks. For example, if an ETF tracks the S&P 500 index, it will hold all 500 stocks in the index or a representative sample of those stocks. The ETF’s performance would then closely track the performance of the index.

A synthetically replicated ETF, on the other hand, does not hold the underlying securities in the index. Instead, it uses derivatives, such as swaps, to replicate the index performance. The ETF enters into an agreement with a counterparty, such as a bank, to receive the returns of the index in exchange for paying the counterparty a fee. The counterparty holds the underlying securities and takes on the risk of holding them.

Physical replication tends to be more straightforward and transparent, as investors can see exactly what securities the ETF holds. However, it can also be more expensive, as the ETF incurs costs associated with buying and selling the underlying securities.

Synthetic replication can be cheaper, as the ETF does not need to buy and sell the underlying securities. However, it also introduces counterparty risk, as the ETF is reliant on the counterparty to fulfill its obligations. Additionally, synthetic ETFs may be less transparent, as investors may not know exactly what securities the counterparty is holding.

Smart Beta

Smart Beta is a strategy used in asset management that seeks to outperform traditional market-cap weighted indices by selecting stocks based on factors other than their market capitalization. These factors can include value, momentum, quality, and low volatility, among others.

Using Smart Beta, investors will seek to lower the variance of their portfolio, reducing risk or try to improve returns.

Indeed, one of the flaws of passive funds such as ETFs is that by following the indices, they might bear unrewarded risk or miss rewarded risk. This is due to the fact that for market-cap weighted funds, when a company’s market cap rises as a share of the index, it will also rise as a share of the fund, even if it yields less returns to the holder than another stock.

This has lately been seen with tech companies that grew exponentially as money flowed into those funds.

Why should I be interested in this post?

As passive management is taking a larger share of the asset management industry, understanding this growing trend can provide a valuable edge whether to work inside it or deal with it. Nonetheless, the concepts detailed in this article can also be useful for personal finance decisions.

Useful resources

Amundi ETF, Gestion indicielle et Smart Beta

Amundi ETF

About the author

The article was written in June 2023 by Tanguy TONEL (ESSEC Business School, Global BBA, 2019-2023).

Can technical analysis actually help to make better trading decisions?

June 14, 2023 by Theo SCHWERTLE

Can technical analysis actually help to make better trading decisions?

In this article, Theo SCHWERTLE (Maastricht University, School of Business and Economics, Bachelor in International Business, 2023) explains how technical analysis can actually help to make better trading decisions (or not).

Market efficiency

Let’s take a look at the different levels of market efficiency and their implications for a trader.

The efficient market hypothesis (EMH) posits that market prices fully incorporate all available information. If this hypothesis is verified, it is infeasible to consistently achieve higher returns than the market on a risk-adjusted basis. According to the EMH, stocks are believed to consistently trade at their fair value on exchanges, precluding the possibility of purchasing undervalued stocks or selling overvalued ones, thus implicitly dismissing the efficiency of technical analysis (TA) and fundamental analysis. As such, the EMH suggests that outperforming the overall market through security selection or market timing is infeasible, and the only way for investors to attain higher returns is by taking on increased risk in their investments.

Definitions

The EMH has three forms: the weak form, the semi-strong form and the strong form. The weak form of the EMH asserts that historical market data (transaction prices and volumes) cannot be used to predict future price movements. The semi-strong form of the EMH asserts that publicly available information (historical market data, financial account published by firms, reports written by financial analysts, etc.) cannot be used to predict future price movements. The strong form of the EMH asserts that both public and private information cannot be used to predict future movements.

Tests of the EMH

Though the strong form of the EMH is generally rejected, scholars are less consistent with evidence for or against the weak or semi-strong form of the EMH. Focusing on technical analysis, a significant body of literature has examined the relationship between EMH and technical analysis (TA), with many scholars rejecting the weak form (Leigh et al., 2002; Eugster and Uhl, 2022). The results of the tests seem to depend on the length of the investment period, the EMH being less rejected for a longer investment period.

Technical analysis

In the world of finance, Technical Analysis serves as an essential tool for investors and traders alike. The methodology involves forecasting future price movements based on the historical data of financial instruments. This strategy pivots on two core principles: the market discounts everything, and prices move in trends (Kirkpatrick & Dahlquist, 2010).

Chartism is one of the oldest techniques in technical analysis. It rests on the identification and analysis of chart patterns and price formations, with chartists meticulously studying these patterns to anticipate future market trends (Lo, Mamaysky, & Wang, 2000). This form of analysis operates on the principle that certain patterns are recurring and that understanding these patterns can provide insights into future price movements.

Another time-tested tool is Moving Averages, a technique that seeks to smooth out price data by creating a consistently updated average price. This approach comes in several variants, with the Simple Moving Average (SMA) and the Exponential Moving Average (EMA) being the most prevalent. These techniques help to clear out the ‘noise’ from random short-term price fluctuations and allow analysts to focus on the overall trend direction.

In stark contrast to these conventional methods stands the modern, technology-driven approach of High Frequency Trading (HFT). This innovative form of trading capitalizes on the power of advanced algorithms and high-speed data processing to execute trades at astonishing speeds. Unlike traditional technical analysis, which primarily focuses on transaction prices and volumes, HFT leverages real-time data from the order-flow and the order-book, exploring minute market discrepancies that might otherwise go unnoticed (Aldridge, 2010).

All we need is short-term market inefficiencies

Hirshleifer and Shumway (2003) gave meaningful insight into the relationship between the weather and daily market index return, demonstrating that sunshine is strongly and significantly correlated with stock returns. In line with that argumentation, Edmans et al. (2007) investigate the stock market reaction to sudden changes in investor mood, using international soccer results as the primary mood variable. The results show a significant market decline after soccer losses in equity markets of the losing teams, with a loss in the World Cup elimination stage leading to a next-day abnormal stock return of −49 basis points. This effect is more substantial in small stocks and more meaningful games and is robust to methodological changes. The same loss effect could also be documented for other international tournaments.

So what does that mean? There are human biases that make humans so different from the rational being many financial theories suggest we are.

Discussion about the feasibility of technical analysis for hedge funds

Hedge funds are also using technical analysis in their decision-making process; however, the degree of utilization varies significantly. The main area where TA is used by hedge funds is to find areas of liquidity to full big positions.

Kavajecz und Odders-White (2004) explored the relationship between TA and liquidity by testing the hypotheses that support and resistance levels coincide with peaks in depth on the limit order book and that moving-average forecasts reveal information about the relative position of depth on the book. They found that technical support/resistance levels, as well as moving average indicators, are significantly related to the state of liquidity on the limit order book and concluded that it is tied to the strategic behavior of limit order traders. This provides a reliable method for practitioners to locate liquidity in the book and reduce transaction costs.

The main advantage of TA is the low cost to construct a market perspective as it requires only market data. The implementation of TA is lower than acquiring and analyzing public or private information. So, if used adequately it is in face the cheaper and more accessible investment approach compared to traditional financial analysis tools.

Sounds good! Where is the catch?

According to Timmermann and Granger (2004), using new financial prediction methods may lead to short-term gains as the information is rapidly incorporated into market prices making the market the more efficient. As these new financial prediction methods become more widely used by other market participants, their effectiveness decreases over time. This idea is supported by studies showing that many stock market anomalies diminish, vanish, or even reverse after they are documented in academic literature (publication on the Social Science Research Network (SSRN) for example).

A broad study by Yamamoto (2012) investigated the profitability of exploiting short-term market inefficiencies and concluded that one could not generate consistent positive results that outperform a buy-and-hold strategy. Yamamoto (2012) analyzes technical strategies for 207 individual stocks in the Nikkei 225 over a one-year period and use two statistical procedures to reduce data-snooping bias (the data-snooping bias refers to the tendency to make false discoveries or draw incorrect conclusions when repeatedly testing and analyzing a dataset, often due to the increased likelihood of finding seemingly significant patterns or relationships by chance). The results indicate that all 9 technical trading strategies underperform the buy-and-hold strategy, suggesting that information on past prices and demand/supply imbalances are not sufficient for superior technical trading profits.

Conclusion

Short-term market inefficiencies can be exploited to generate positive returns. However, many of the found profitability diminish after introducing real market conditions, transaction fees or adjusting the returns for the increased risk. Generally, TA offers increased benefits over fundamental analysis in the short-term but loses ground with increased time as the market returns to efficiency. The difference in information costs motivates its popularity, but even if a profitable trading strategy is found, its benefits may only be enjoyed for a short time.

Why should I be interested in this post?

Technical analysis offers a different perspective on the market that is rarely touched on by university curriculums. This alternative approach is used by individual traders as well as institutional traders like hedge funds to find good entries and exits in the market. According to a survey by Menkhoff (2010), 77% of all hedge fund managers in their sample rate TA as really important to their decision-making, attributing a value of at least 10% to it in their decision-making process. About 20% of fund managers even indicate to prefer TA over fundamental analysis. So, it seems to offer some value, despite the academic criticism in line the efficiency of the market.

Useful resources

Academic articles

Edmans, A., García, D. & Norli, Y. (2007). Sports Sentiment and Stock Returns The Journal of Finance 62(4), 1967–1998.

Eugster, P. & Uhl, M. W. (2022). Technical analysis: Novel insights on contrarian trading. European Financial Management .

Fama, E. F. (1970). Efficient capital markets: A review of theory and empirical work. The Journal of Finance 25(2), 383-417.

Hirshleifer, D. & Shumway, T. (2003). Good Day Sunshine: Stock Returns and the Weather The Journal of Finance 58(3), 1009–1032.

Kavajecz, K. A. & Odders-White, E. R. (2004). Technical Analysis and Liquidity Provision Review of Financial Studies 17(4), 1043–1071.

Leigh, W., Purvis, R. & Ragusa, J. M. (2002). Forecasting the NYSE composite index with technical analysis, pattern recogniser, neural network, and genetic algorithm: a case study in romantic decision support Decision Support Systems 32(4), 361–377.

Lo, A. W., Mamaysky, H., & Wang, J. (2000). Foundations of technical analysis: Computational algorithms, statistical inference, and empirical implementation. The Journal of Finance 55(4), 1705-1770.

Menkhoff, L. (2010). The use of technical analysis by fund managers: International evidence. Journal of Banking & Finance 34(11), 2573–2586.

Timmermann, A. & Granger, C. W. (2004). Efficient market hypothesis and forecasting International Journal of Forecasting, 20(1), 15–27.

Yamamoto, R. (2012). Intraday technical analysis of individual stocks on the Tokyo Stock Exchange Journal of Banking & Finance, 36(11), 3033–3047.

Books

Aldridge, I. (2010). High-frequency trading: a practical guide to algorithmic strategies and trading systems. John Wiley & Sons.

Kirkpatrick II, C. D., & Dahlquist, J. R. (2010). Technical Analysis: The Complete Resource for Financial Market Technicians. FT press.

Lewis, M. (2014). Flash Boys: A Wall Street Revolt. W. W. Norton & Company.

About the author

The article was written in June 2023 by Theo SCHWERTLE (Maastricht University, School of Business and Economics, Bachelor in International Business, 2018-2023).

The KOSPI 50 index

June 6, 2023 by Nithisha CHALLA

The KOSPI 50 index

In this article, Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management, 2021-2023) presents the KOSPI 50 index representing the South Korean equity market and details its characteristics.

The KOSPI 50 index

A well-known stock market index in South Korea, the KOSPI 50 index serves as a crucial benchmark for the South Korean equity market. It represents the performance of the 50 biggest and busiest companies traded on the main South Korean stock exchange, the Korea Exchange (KRX), listed on the market.

The KOSPI 50 index, which was created on April 1, 2002, is managed by the Korea Exchange and is widely regarded as an accurate indicator of the Korean economy and its key sectors. Market capitalization, trading volume, and liquidity are used in the index selection process to make sure that only the most significant and representative companies from the Korean market are included.

The KOSPI 50, a market capitalization-weighted index, takes into account the market value of each constituent stock to reflect the relative importance of each stock. The KOSPI 50 is prominently displayed on trading platforms and financial websites, similar to other significant stock market indices, making it simple for investors and analysts worldwide to access. It is a crucial indicator of the state and trends of the Korean economy and is important for making investment decisions.

The ticker symbol commonly used in the financial industry to represent the KOSPI 50 index is “KOSPI50”.

Table 1 below gives the Top 10 stocks in the KOSPI 50 index in terms of market capitalization as of January 31, 2023.

Table 1. Top 10 stocks in the KOSPI 50 index.

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

Table 2 below gives the sector representation of the KOSPI 50 index in terms of number of stocks and market capitalization as of January 31, 2023.

Table 2. Sector representation in the KOSPI 50 index.

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

Calculation of the KOSPI 50 index value

The KOSPI 50 index is a float-adjusted market-capitalization-weighted index. It is adjusted for the proportion of shares that are available for trading in the market as well as the market value of each constituent stock. With the help of this weighting methodology, investors can get a complete picture of the Korean market by ensuring that larger companies have a greater influence on the index’s movements than smaller ones.

The formula to compute the KOSPI 50 index is given by

Float Adjusted Market Capitalization Index value

where I is the index value, k a given asset, K the number of assets in the index, P^k the market price of asset k, N^k the number of issued shares for asset k, F^k the float factor of asset k, and t the time of calculation of the index.

In a float-adjusted market-capitalization-weighted index, the weight of asset k is given by

Float Adjusted Market Capitalization Weighted Index Weight

Use of the KOSPI 50 index in asset management

The analysis of the companies that make up the KOSPI 50 index offers important new perspectives on the Korean economy, its key industries, and the elements that influence business success there. The index also acts as a crucial tool for investors, allowing them to assess the performance of their portfolios in comparison to the larger Korean market and make well-informed investment choices. It supports various asset management tasks, such as passive investments, evaluating corporate risk, asset allocation, and portfolio management, and offers investors insightful information.

Benchmark for equity funds

Investors can gain a thorough understanding of the South Korean market and make wise investment decisions by following the KOSPI 50 index. It is significant to remember that the KOSPI 50 index, which includes the 50 largest and most actively traded companies in South Korea, represents a particular market segment. While it offers an accurate indicator of the performance of these well-known businesses, it might not accurately reflect the performance of all markets and industry sectors nationwide. Investors should think about incorporating other indices, such as the KOSPI 200, which covers a wider range of companies listed on the Korea Exchange, or the MSCI Korea Index, which includes a more diverse set of companies, to obtain a more thorough evaluation of the South Korean market.

Financial products around the KOSPI 50 index

Different financial products linked to the KOSPI 50 index are available for investors looking to diversify their portfolios and increase their exposure to the South Korean stock market. These products offer chances to possibly profit from changes in the market and take part in the performance of the 50 biggest and most actively traded South Korean companies.

Here are some of the main financial products associated with the KOSPI 50 index:

Exchange-Traded Funds (ETFs): similar to stocks, investors can trade and invest in ETFs that track the KOSPI 50 index. These ETFs offer a practical way to get exposure to the KOSPI 50 companies’ performance. The KODEX KOSPI 200 ETF and the Samsung KODEX Leverage ETF are two examples of KOSPI 50 ETFs.
Options and Futures Contracts: Investors can use options and futures contracts based on the KOSPI 50 index to manage risk, make predictions about market trends, or put trading strategies into practice. Investors can purchase or sell the index through these derivative contracts at predetermined future prices and dates.
Mutual Funds and Index Funds: A number of mutual funds and index funds concentrate their investments in the businesses represented by the KOSPI 50 index. These funds seek to match the performance of the index or build portfolios that closely resemble the index’s components. Through these funds, investors can gain exposure to the KOSPI 50, allowing for investment diversification and expert management.

Historical data for the KOSPI 50 index

How to get the data?

The KOSPI 50 index is the most common index used in finance, and historical data for the KOSPI 50 index can be easily downloaded from the internet.

For example, you can download data for the KOSPI 50 index from December 11, 1996 on Yahoo! Finance (the Yahoo! code for KOSPI 50 index is ^KS11).

Source: Yahoo! Finance.

You can also download the same data from a Bloomberg terminal.

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 KOSPI 50 index.

Data file

The R program that you can download above allows you to download the data for the KOSPI 50 index from the Yahoo! Finance website. The database starts on December 11, 1996. It also computes the returns (logarithmic returns) from closing prices.

Table 3 below represents the top of the data file for the KOSPI 50 index downloaded from the Yahoo! Finance website with the R program.

Table 3. Top of the data file for the KOSPI 50 index.
Top of the file for the KOSPI 50 index data
Source: computation by the author (data: Yahoo! Finance website).

Evolution of the KOSPI 50 index

Figure 1 below gives the evolution of the KOSPI 50 index from December 11, 1996 to December 30, 2022 on a daily basis.

Figure 1. Evolution of the KOSPI 50 index.

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

Figure 2 below gives the evolution of the KOSPI 50 index returns from December 11, 1996 to December 30, 2022 on a daily basis.

Figure 2. Evolution of the KOSPI 50 index returns.

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

Summary statistics for the KOSPI 50 index

The R program that you can download above also allows you to compute summary statistics about the returns of the KOSPI 50 index.

Table 4 below presents the following summary statistics estimated for the KOSPI 50 index:

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 4. Summary statistics for the KOSPI 50 index.

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

Statistical distribution of the KOSPI 50 index returns

Historical distribution

Figure 3 represents the historical distribution of the KOSPI 50 index daily returns for the period from December 11, 1996 to December 30, 2022.

Figure 3. Historical distribution of the KOSPI 50 index 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 December 11, 1996 to December 30, 2022. The mean of daily returns is equal to 0.02% and the standard deviation of daily returns is equal to 1.37% (or equivalently 3.94% for the annual mean and 28.02% for the annual standard deviation as shown in Table 3 above).

Figure 4 below represents the Gaussian distribution of the KOSPI 50 index daily returns with parameters estimated over the period from December 11, 1996 to December 30, 2022.

Figure 4. Gaussian distribution of the KOSPI 50 index returns.
Gaussian distribution of the daily KOSPI 50 index returns
Source: computation by the author (data: Yahoo! Finance website).

Risk measures of the KOSPI 50 index returns

The R program that you can download above also allows you to compute risk measures about the returns of the KOSPI 50 index.

Table 5 below presents the following risk measures estimated for the KOSPI 50 index:

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 5. Risk measures for the KOSPI 50 index.

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 KOSPI 50 index while the study of the right tail is relevant for an investor holding a short position in the KOSPI 50 index.

Why should I be interested in this post?

For a number of reasons, management students (as future managers and individual investors) should learn about the KOSPI 50 index. The index includes wide range of industries, including energy, finance, telecommunications, and consumer goods, and it covers the biggest and most liquid German companies. Understanding how the index is constructed, how it performs, and the companies that make up the index is important for anyone studying finance or business in Russia or interested in investing in German equities.

Individual investors can assess the performance of their own investments in the German equity market with the KOSPI 50 index. Last but not least, a lot of asset management firms base their mutual funds and exchange-traded funds (ETFs) on the KOSPI 50 index which can considered as interesting assets to diversify a portfolio. Learning about these products and their portfolio and risk management applications can be valuable for management students.

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.

Business

Wikipedia What is the KOSPI 50 index

PWC A guide to listing on the Korean exchange

Data

Yahoo! Finance

Yahoo! Finance Historical data for the KOSPI 50 index

About the author

The article was written in June 2023 by Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management, 2021-2023).

The OMX Copenhagen 25 (OMXC 25) index

June 6, 2023 by Nithisha CHALLA

The OMX Copenhagen 25 (OMXC 25) index

In this article, Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management, 2021-2023) presents the OMX Copenhagen 25 (OMXC25 or OMXC 25) index representing the Danish equity market and details its characteristics.

The OMX Copenhagen 25 index

The 25 biggest and busiest companies listed on Nasdaq Copenhagen, the main stock exchange in Denmark, make up the OMX Copenhagen 25 (OMXC 25) index, which is a market-capitalization-weighted index. With 1,000 points as the base point, the index was introduced on December 4th, 1996.

Nasdaq Copenhagen chooses the stocks for the OMXC 25 index, taking into account elements like market capitalization, liquidity, and free float. To maintain its representation of the Danish stock market, the index is reviewed twice a year, in June and December, and rebalanced as necessary.

The OMXC 25 is a market-capitalization-weighted index, which means that the index’s weight is based on the market capitalization of each company. This increases the OMXC 25’s comparability to the Danish market as a whole.

Investors and analysts pay close attention to the performance of the OMXC 25 index, which is widely used as a benchmark for the Danish stock market. Through financial products like exchange-traded funds (ETFs) and index funds that follow the OMXC 25 index, investors can gain exposure to the Danish market. The ticker symbol “OMXC25” is frequently used in trading platforms and financial websites to denote the OMXC 25 index.

Table 1 below gives the Top 10 stocks in the OMXC 25 index in terms of market capitalization as of January 31, 2023.

Table 1. Top 10 stocks in the OMXC 25 index.

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

Table 2 below gives the sector representation of the OMXC 25 index in terms of number of stocks and market capitalization as of January 31, 2023.

Table 2. Sector representation in the OMXC 25 index.

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

Calculation of the OMXC 25 index value

The performance of the 25 most actively traded and highly capitalized companies listed on the Danish Nasdaq Copenhagen stock exchange is reflected in the OMX Copenhagen 25 (OMXC 25) index, which is a float-adjusted market-capitalization-weighted index. The index is evaluated twice a year by Nasdaq Copenhagen and includes businesses from a variety of industries, including technology, healthcare, and finance. Each year, the index is rebalanced in June and December, and the companies that make up the index are chosen using criteria like market capitalization, trading volume, and free float.

The formula to compute the OMXC 25 index is given by

Float Adjusted Market Capitalization Index value

In a float-adjusted market-capitalization-weighted index, the weight of asset k is given by

Float Adjusted Market Capitalization Weighted Index Weight

Use of the OMXC 25 index in asset management

A common benchmark used by investors to evaluate the performance of their investment portfolios in relation to the Danish stock market is the OMXC 25 index. Investors and analysts can learn a lot about the state of the Danish economy overall and the performance of important industries like technology, healthcare, and industrials by closely following the changes in the OMXC 25 index. Through ticker symbols like “OMXC25” or “OMXC25.CO,” the index is frequently mentioned in financial news outlets and is readily available to investors and traders worldwide.

Benchmark for equity funds

The performance of the top 25 companies listed on the Copenhagen Stock Exchange (Nasdaq Copenhagen) is represented by the OMXC 25 index, but it does not fully represent the size of the Danish equity market. Because of this, investors seeking a more thorough representation of the Danish market may want to think about other, wider market indices, like the OMXC 25 or the OMXC All-Share.

The 25 most active and liquid companies listed on Nasdaq Copenhagen are included in the OMXC 25 index, which offers a more comprehensive view of the Danish market. The OMXC All-Share index, on the other hand, provides a more thorough overview of the Danish equity market as a whole and covers a wider range of companies, including both large and small caps. In order to accurately track their performance and align it with their investment goals in the Danish market, investors should carefully assess their investment objectives and strategies to determine the most appropriate benchmark index.

Financial products around the OMXC 25 index

With the help of the OMXC 25 index, these financial products give investors the chance to diversify their portfolios, get exposure to the Danish stock market, and perhaps even profit from market fluctuations.

Some of the main financial products associated with the OMXC 25 index are:

Exchange-Traded Funds (ETFs): ETFs, which are traded on stock exchanges like individual stocks, allow investors access to the OMXX 25 index. ETFs that track the performance of the OMXC 25 index, like the iShares OMXC 25 UCITS ETF and the Xact OMXC 25 ETF, give investors a broad view of the Danish market.
Options and Futures Contracts: Investors can purchase or sell the OMXC 25 index through options and futures contracts that are linked to the index at a specified price and future date. These derivative contracts can be used for hedging, speculation, and portfolio management, among other things.
Mutual Funds and Index Funds: A few mutual funds and index funds concentrate their investments in businesses that are part of the OMXX 25 index or seek to match its performance. With the help of these funds, investors now have an easy way to expose themselves to a diverse portfolio of Danish stocks.

Historical data for the OMXC 25 index

How to get the data?

The OMXC 25 index is the most common index used in finance, and historical data for the OMXC 25 index can be easily downloaded from the internet.

For example, you can download data for the OMXC 25 index from December 19, 2016 on Yahoo! Finance (the Yahoo! code for OMXC 25 index is ^OMXC25).

Source: Yahoo! Finance.

You can also download the same data from a Bloomberg terminal.

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 OMXC 25 index.

Data file

The R program that you can download above allows you to download the data for the OMXC 25 index from the Yahoo! Finance website. The database starts on December 19, 2016. It also computes the returns (logarithmic returns) from closing prices.

Table 3 below represents the top of the data file for the OMXC 25 index downloaded from the Yahoo! Finance website with the R program.

Table 3. Top of the data file for the OMXC 25 index.
Top of the file for the OMXC 25 index data
Source: computation by the author (data: Yahoo! Finance website).

Evolution of the OMXC 25 index

Figure 1 below gives the evolution of the OMXC 25 index from December 19, 2016 to December 30, 2022 on a daily basis.

Figure 1. Evolution of the OMXC 25 index.

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

Figure 2 below gives the evolution of the OMXC 25 index returns from December 19, 2016 to December 30, 2022 on a daily basis.

Figure 2. Evolution of the OMXC 25 index returns.

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

Summary statistics for the OMXC 25 index

The R program that you can download above also allows you to compute summary statistics about the returns of the OMXC 25 index.

Table 4 below presents the following summary statistics estimated for the OMXC 25 index:

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 4. Summary statistics for the OMXC 25 index.

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

Statistical distribution of the OMXC 25 index returns

Historical distribution

Figure 3 represents the historical distribution of the OMXC 25 index daily returns for the period from December 19, 2016 to December 30, 2022.

Figure 3. Historical distribution of the OMXC 25 index 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 December 19, 2016 to December 30, 2022. The mean of daily returns is equal to 0.02% and the standard deviation of daily returns is equal to 1.37% (or equivalently 3.94% for the annual mean and 28.02% for the annual standard deviation as shown in Table 3 above).

Figure 4 below represents the Gaussian distribution of the OMXC 25 index daily returns with parameters estimated over the period from December 19, 2016 to December 30, 2022.

Figure 4. Gaussian distribution of the OMXC 25 index returns.
Gaussian distribution of the daily OMXC 25 index returns
Source: computation by the author (data: Yahoo! Finance website).

Risk measures of the OMXC 25 index returns

The R program that you can download above also allows you to compute risk measures about the returns of the OMXC 25 index.

Table 5 below presents the following risk measures estimated for the OMXC 25 index:

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 5. Risk measures for the OMXC 25 index.

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 OMXC 25 index while the study of the right tail is relevant for an investor holding a short position in the OMXC 25 index.

Why should I be interested in this post?

Students can gain a thorough understanding of industry dynamics, market competition, and the interplay of various factors that affect business success in Denmark by studying the OMXC 25 index. Investors can compare the performance of their portfolios to that of the larger Danish stock market using the OMXC 25 index as a benchmark. In addition to reflecting investor sentiment toward Denmark’s biggest and most actively traded companies, it offers a snapshot of the market’s health.

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.

About the OMXC 25 index

Nasdaq Index Description

Capital.com What is the OMXC20 index?

Data

Yahoo! Finance

Yahoo! Finance Data for the OMXC 25 index

About the author

The article was written in June 2023 by Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management, 2021-2023).

The BEL 20 index

June 6, 2023 by Nithisha CHALLA

The BEL 20 index

In this article, Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management, 2021-2023) presents the BEL 20 index representing the Belgian equity market and details its characteristics.

The BEL 20 index

The top 20 companies listed on Euronext Brussels, Belgium’s main stock exchange, make up the BEL 20 index, a stock market index that measures performance. The BEL 20 index was created in 1991, and Euronext oversees its operation. The market capitalization, liquidity, and sector representation of the companies chosen for the index are taken into consideration.

The market capitalization of each stock determines its weight in the BEL 20 index, which is a capitalization-weighted index. To guarantee that the index continues to be a trustworthy representation of the Belgian equity market, it is rebalanced four times per year.

With the widely used ticker symbol “BEL20” in the financial sector, investors and traders can access the BEL 20 index through various financial news sources and trading platforms. The BEL 20 index is a useful tool for investors and financial professionals because it can give important insights into the performance of the Belgian economy and its best-performing companies.

Table 1 below gives the Top 10 stocks in the BEL 20 index in terms of market capitalization as of January 31, 2023.

Table 1. Top 10 stocks in the BEL 20 index.

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

Table 2 below gives the sector representation of the BEL 20 index in terms of number of stocks and market capitalization as of January 31, 2023.

Table 2. Sector representation in the BEL 20 index.

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

Calculation of the BEL 20 index value

The performance of the 20 largest and most actively traded companies listed on the Brussels Stock Exchange (Euronext Brussels) in Belgium is reflected in the BEL 20 index, which is a float-adjusted market-capitalization-weighted index. The Belgian Association of Financial Analysts (ABAF-BVFA), which chooses the companies to be included in the index based on their liquidity, market capitalization, and free float, reviews the index on a quarterly basis.

The BEL 20 is rebalanced quarterly, taking into account any changes in the market capitalization of the constituent companies, to make sure the index accurately reflects the performance of the Belgian stock market.

The formula to compute the BEL 20 index is given by

Float Adjusted Market Capitalization Index value

In a float-adjusted market-capitalization-weighted index, the weight of asset k is given by formula

Float Adjusted Market Capitalization Weighted Index Weight

Use of the BEL 20 index in asset management

Investors frequently use the BEL 20 index as a benchmark to assess the performance of their investment portfolios in relation to the larger Belgian stock market.

Investors and analysts can learn more about the performance of the Belgian economy and its major sectors—such as financial services, consumer goods, and energy—by examining the changes in the BEL 20 index. Investors and traders can access the index using ticker symbols like “BEL20” or “BEL20.BR” and it is frequently covered in financial news outlets. Investors should take into account other indexes and benchmarks for a more thorough evaluation of the Belgian market, however, as the BEL 20 index does not cover all industries and sectors in Belgium.

Benchmark for equity funds

For equity funds investing across the board in the Belgian market, the BEL 20 index may not always be the best benchmark. This is due to the fact that the BEL 20 index does not account for the entire Belgian equity market; rather, it only tracks the performance of the top 20 companies listed on Euronext Brussels. Investors may need to take into account other broader market indices, such as the BEL Mid, which includes the 60 next most significant listed companies after the BEL 20, or the BEL Small, which includes the smallest companies listed on Euronext Brussels, in order to obtain a more complete representation of the Belgian market. Investors should therefore assess their investment goals and plans before choosing the appropriate benchmark indices.

Financial products around the BEL 20 index

The performance of the businesses that make up the BEL 20 index is the main objective of these products. Several financial products follow the BEL 20 index, including:

Exchange-Traded Funds: ETFs that track the BEL 20 index include the Lyxor UCITS Bel 20 ETF and the iShares Bel 20 UCITS ETF
Index funds: The Candriam Equities Belgium Index and the BNP Paribas B Fund Belgium Index are examples of index funds that track the performance of the Bel 20 index

These financial products allow investors to follow the performance of the top 20 companies listed on the Euronext Brussels exchange as well as gain exposure to the Belgian equity market. These financial products could produce returns based on the performance of the Belgian equity market and assist investors in diversifying their portfolios.

Historical data for the BEL 20 index

How to get the data?

The BEL 20 index is the most common index used in finance, and historical data for the BEL 20 index can be easily downloaded from the internet.

For example, you can download data for the BEL 20 index from January 3, 1984 on Yahoo! Finance (the Yahoo! code for BEL 20 index is ^BFX).

Source: Yahoo! Finance.

You can also download the same data from a Bloomberg terminal.

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 BEL 20 index.

Data file

The R program that you can download above allows you to download the data for the BEL 20 index from the Yahoo! Finance website. The database starts on January 3, 1984. It also computes the returns (logarithmic returns) from closing prices.

Table 3 below represents the top of the data file for the BEL 20 index downloaded from the Yahoo! Finance website with the R program.

Table 3. Top of the data file for the BEL 20 index.
Top of the file for the BEL 20 index data
Source: computation by the author (data: Yahoo! Finance website).

Evolution of the BEL 20 index

Figure 1 below gives the evolution of the BEL 20 index from January 3, 1984 to December 30, 2022 on a daily basis.

Figure 1. Evolution of the BEL 20 index.

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

Figure 2 below gives the evolution of the BEL 20 index returns from January 3, 1984 to December 30, 2022 on a daily basis.

Figure 2. Evolution of the BEL 20 index returns.

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

Summary statistics for the BEL 20 index

The R program that you can download above also allows you to compute summary statistics about the returns of the BEL 20 index.

Table 4 below presents the following summary statistics estimated for the BEL 20 index:

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 4. Summary statistics for the BEL 20 index.

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

Statistical distribution of the BEL 20 index returns

Historical distribution

Figure 3 represents the historical distribution of the BEL 20 index daily returns for the period from January 3, 1984 to December 30, 2022.

Figure 3. Historical distribution of the BEL 20 index 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 January 3, 1984 to December 30, 2022. The mean of daily returns is equal to 0.02% and the standard deviation of daily returns is equal to 1.37% (or equivalently 3.94% for the annual mean and 28.02% for the annual standard deviation as shown in Table 3 above).

Figure 4 below represents the Gaussian distribution of the BEL 20 index daily returns with parameters estimated over the period from January 3, 1984 to December 30, 2022.

Figure 4. Gaussian distribution of the BEL 20 index returns.
Gaussian distribution of the daily BEL 20 index returns
Source: computation by the author (data: Yahoo! Finance website).

Risk measures of the BEL 20 index returns

The R program that you can download above also allows you to compute risk measures about the returns of the BEL 20 index.

Table 5 below presents the following risk measures estimated for the BEL 20 index:

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 5. Risk measures for the BEL 20 index.

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 BEL 20 index while the study of the right tail is relevant for an investor holding a short position in the BEL 20 index.

Why should I be interested in this post?

By analyzing the companies in the BEL 20 index, students can gain an understanding of how these industries operate and the factors that influence their success. For example, students can explore how regulations affect the financial services industry, how innovation drives growth in the pharmaceutical sector, and how geopolitical events impact energy markets. This knowledge can be particularly useful for those pursuing careers in finance, economics, or business.

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.

About the BEL 20 index

Wikipedia What is the BEL 20 index

Currency BEL 20 index explained

Trading economics About Belgium Stock Market Index BEL20

Data

Yahoo! Finance

Yahoo! Finance Data for the BEL 20 index

About the author

The article was written in June 2023 by Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management, 2021-2023).

The IBEX 35 index

June 6, 2023 by Nithisha CHALLA

The IBEX 35 index

In this article, Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management, 2021-2023) presents the IBEX 35 index representing the Spanish equity market and details its characteristics.

The IBEX 35 index

The Bolsa de Madrid’s benchmark stock market index, the IBEX 35 index, is regarded as Spain’s primary stock exchange. The company that runs the Spanish stock exchanges, Bolsas y Mercados Espaoles (BME), which was founded on January 14, 1992, is in charge of managing it.

The 35 most liquid and well-capitalized companies traded on the Bolsa de Madrid make up the index. Based on trading volume, liquidity, and free-float market capitalization, the companies listed are chosen. The index includes businesses from a wide range of industries, including consumer goods, energy, finance, and telecommunications.

The IBEX 35 index is a free-float market capitalization-weighted index, which means that the index’s weights are based on market capitalization and are float-adjusted for each stock. This makes sure that the movements of the index are more influenced by larger companies than by smaller ones.

The IBEX 35 index is widely represented on trading platforms and financial websites, like other significant stock market indices. The performance of the Spanish economy and the overall health of the European Union are closely watched by investors and analysts around the world.

The ticker symbol used in the financial industry for the IBEX 35 index is “IBEX”.

Table 1 below gives the Top 10 stocks in the IBEX 35 index in terms of market capitalization as of January 31, 2023.

Table 1. Top 10 stocks in the IBEX 35 index.

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

Table 2 below gives the sector representation of the IBEX 35 index in terms of number of stocks and market capitalization as of January 31, 2023.

Table 2. Sector representation in the IBEX 35 index.

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

Calculation of the IBEX 35 index value

As a free-float market-capitalization-weighted index that is float-adjusted, the IBEX 35 index is calculated by taking into account the market capitalization of each of the companies that make up the index. To ensure that the index accurately captures the performance of the Spanish stock market, Bolsas y Mercados Espaoles (BME), the Spanish stock exchange, reviews and rebalances the index twice a year. The stocks that will be included in the index are chosen by the Technical Advisory Committee of the BME, which takes into account elements like liquidity, market capitalization, and trading volume.

The formula to compute the IBEX 35 index is given by

Float Adjusted Market Capitalization Index value

In a float-adjusted market-capitalization-weighted index, the weight of asset k is given by

Float Adjusted Market Capitalization Weighted Index Weight

Use of the IBEX 35 index in asset management

The IBEX 35 index serves as a benchmark for assessing the performance of the Spanish stock market. Because it is a widely used indicator of the performance of the Spanish stock market, it can help investors with important asset management tasks like passive investments, evaluating corporate risk, asset allocation, portfolio management, and so forth. However, the performance of all markets or sectors is not accurately reflected by the IBEX 35 index, which only includes the 35 Spanish stocks with the highest level of liquidity. Therefore, when evaluating the performance of the Spanish equity market, investors should also consider other indices like the FTSE Spain Index and the MSCI Spain Index.

Benchmark for equity funds

Investors frequently use the IBEX 35 index as a benchmark. When using the IBEX 35 index as a benchmark for equity funds in Spain, it is important to remember that it only includes 35 of the largest and most popularly traded companies listed on the Spanish stock exchange. As a result, it might not accurately represent the whole Spanish market, as there are many small and mid-cap companies in Spain that are not represented by the index. The benchmark index to be used will ultimately depend on the specific investment objectives and strategies of the fund in question.

Financial products around the IBEX 35 index

Through the IBEX 35 index, these financial products give investors access to the Spanish stock market, portfolio diversification, and the potential to profit from market fluctuations.

Some of the main financial products related to the IBEX 35 index are:

Exchange-Traded Funds (ETFs): Through ETFs, which are traded like stocks, investors can gain access to the IBEX 35 index. ETFs that follow the Ibex 35 index include the iShares Ibex 35 UCITS ETF and the Amundi ETF Ibex 35.
Options and Futures Contracts: Investors can use options and futures contracts to buy or sell the IBEX 35 index at a predetermined price and date in the future. This is typically done to generate income through trading strategies, hedge against market volatility, or predict the index’s performance.
Mutual Funds and Index Funds: Some mutual funds and index funds concentrate on investing in businesses that are part of the IBEX 35 index or seek to replicate the performance of the index by acquiring the same stocks that comprise the index.

Historical data for the IBEX 35 index

How to get the data?

The IBEX 35 index is the most common index used in finance, and historical data for the IBEX 35 index can be easily downloaded from the internet.

For example, you can download data for the IBEX 35 index from July 12, 1993 on Yahoo! Finance (the Yahoo! code for IBEX 35 index is ^IBEX).

Source: Yahoo! Finance.

You can also download the same data from a Bloomberg terminal.

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 IBEX 35 index.

Data file

The R program that you can download above allows you to download the data for the IBEX 35 index from the Yahoo! Finance website. The database starts on July 12, 1993. It also computes the returns (logarithmic returns) from closing prices.

Table 3 below represents the top of the data file for the IBEX 35 index downloaded from the Yahoo! Finance website with the R program.

Table 3. Top of the data file for the IBEX 35 index.
Top of the file for the IBEX 35 index data
Source: computation by the author (data: Yahoo! Finance website).

Evolution of the IBEX 35 index

Figure 1 below gives the evolution of the IBEX 35 index from July 12, 1993 to December 30, 2022 on a daily basis.

Figure 1. Evolution of the IBEX 35 index.

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

Figure 2 below gives the evolution of the IBEX 35 index returns from July 12, 1993 to December 30, 2022 on a daily basis.

Figure 2. Evolution of the IBEX 35 index returns.

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

Summary statistics for the IBEX 35 index

The R program that you can download above also allows you to compute summary statistics about the returns of the IBEX 35 index.

Table 4 below presents the following summary statistics estimated for the IBEX 35 index:

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 4. Summary statistics for the IBEX 35 index.

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

Statistical distribution of the IBEX 35 index returns

Historical distribution

Figure 3 represents the historical distribution of the IBEX 35 index daily returns for the period from July 12, 1993 to December 30, 2022.

Figure 3. Historical distribution of the IBEX 35 index 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 July 12, 1993 to December 30, 2022. The mean of daily returns is equal to 0.02% and the standard deviation of daily returns is equal to 1.37% (or equivalently 3.94% for the annual mean and 28.02% for the annual standard deviation as shown in Table 3 above).

Figure 4 below represents the Gaussian distribution of the IBEX 35 index daily returns with parameters estimated over the period from July 12, 1993 to December 30, 2022.

Figure 4. Gaussian distribution of the IBEX 35 index returns.
Gaussian distribution of the daily IBEX 35 index returns
Source: computation by the author (data: Yahoo! Finance website).

Risk measures of the IBEX 35 index returns

The R program that you can download above also allows you to compute risk measures about the returns of the IBEX 35 index.

Table 5 below presents the following risk measures estimated for the IBEX 35 index:

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 5. Risk measures for the IBEX 35 index.

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 IBEX 35 index while the study of the right tail is relevant for an investor holding a short position in theIBEX 35 index.

Why should I be interested in this post?

Students can gain useful knowledge about the Spanish stock market and its major sectors by looking at the IBEX 35 index. These firms represent a wide range of industries, including consumer goods, energy, finance, and telecommunications, making the index a useful benchmark for the Spanish economy. Students can learn how industries function, how competition affects the market, and what elements contribute to business success in Spain by examining the performance of the companies included in the index.

Furthermore, investors can use financial products linked to the IBEX 35 index, such as exchange-traded funds (ETFs), futures, and options contracts, to access the Spanish market and potentially generate returns. By understanding the dynamics of the IBEX 35 index and the Spanish economy, students can develop valuable skills for careers in investment banking, portfolio management, and corporate finance.

Useful resources

About the IBEX 35 index

Wikipedia What is the IBEX 35 index

AVA trade An Overview of Spain’s Financial Engine – IBEX 35

DailyFX What is the IBEX 35 Index and what influences its price?

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 Data for the IBEX 35 index

About the author

The article was written in June 2023 by Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management, 2021-2023).

Decoding Business Performance: The Top Line, The Line, and The Bottom Line

June 3, 2023 by Isaac ALLIALI

Decoding Business Performance: The Top Line, The Line, and The Bottom Line

In this article, Isaac ALLIALI (ESSEC Business School, Bachelor in Business Administration (BBA), 2019-2023) decodes the business performance by analyzing the top line, the line, and the bottom line.

Introduction

In the realm of finance and business, terms like “top line,” “the line,” and “bottom line” often dominate discussions. But what do they really mean, and why are they so important in evaluating a company’s financial health? This article aims to elucidate these key financial terms and their relevance to business performance assessment.

The Top Line

The “top line” refers to a company’s gross revenue or sales, so named because it appears at the top of a company’s income statement. It reflects the total revenue earned from the sale of goods or services before deducting any costs or expenses. This figure is crucial as it indicates the company’s ability to sell its products or services, which is fundamental to its business operations.

The strategies for increasing the top line generally focus on enhancing sales through marketing efforts, pricing strategies, product development, or expanding into new markets. While it may seem that a growing top line (revenue) is indicative of profitability, it is important to recognize that this metric alone does not consider the expenses associated with generating that revenue. In other words, the increase in revenue does not guarantee increased profitability. It is crucial for investors to understand that a company’s top line growth does not always align with its profitability.

For instance, if the cost of producing goods or services is rising faster than sales, profits might be shrinking despite increased revenues.

The Line

While “the line” is a less commonly used term in comparison to the “top line” and “bottom line”, it is often used to refer to the “break-even line.” The break-even line represents a point where total costs (including both fixed and variable costs) are equal to total revenue.

At this juncture, the company isn’t making a profit, but it isn’t incurring a loss either. Understanding the break-even point is essential for businesses because it provides a clear target to cover costs and start making profits.

Knowing when a company will hit its break-even point can help investors understand when it might start turning a profit. In addition, a company with a lower break-even point can withstand market fluctuations better, representing a potentially less risky investment.

The Bottom Line

The “bottom line” is arguably the most significant figure on an income statement, representing the company’s net income. It’s the residue left after deducting all expenses, including cost of goods sold (COGS), operating expenses, interest payments, and taxes from the top line. This term gets its name because net income is listed at the bottom of the income statement.

The bottom line demonstrates a company’s profitability, and strategies to improve it usually focus on enhancing gross revenue or reducing costs. Shareholders closely monitor the bottom line because it directly affects earnings per share and dividends. However, solely focusing on improving the bottom line can sometimes lead to unsustainable strategies like excessive cost-cutting.

However, investors should also be aware that an increasing bottom line can sometimes be achieved through aggressive cost-cutting, which may not be sustainable in the long run. It’s important to scrutinize the sources of bottom-line growth: Is it due to increased sales, improved operational efficiency, or simply cost-cutting?

Conclusion

Understanding the terms “top line,” “the line,” and “bottom line” is crucial for interpreting a company’s financial performance. While the top line provides insight into sales performance and the bottom line into profitability, it’s the intricate story that unfolds between these two lines that often holds the most valuable insights for sustainable growth and profitability. As such, a holistic view of a company’s financial health should consider all these aspects.

By focusing on each line in tandem, companies can better navigate their path to profitability, creating strategies that stimulate sales growth (top line), manage costs effectively (the line), and ultimately drive profit (bottom line). However, these metrics should not be used in isolation. Investors should use them in conjunction with other financial ratios and indicators to make informed decisions.

By aligning their strategies to promote sales growth (top line) and efficient cost management practices (the line), companies can navigate their path to profitability. The aim is to strike a balance between revenue generation and cost control to drive profitability (bottom line). However, it’s important to note that these metrics should not be evaluated in isolation. Investors should consider utilizing other financial ratios and indicators to gain a comprehensive understanding of a company’s financial health. These may include profitability ratios (such as gross profit margin, operating margin, and net profit margin), liquidity ratios (like current ratio and quick ratio), debt ratios (such as debt-to-equity ratio and interest coverage ratio), and efficiency ratios (like inventory turnover and receivables turnover). Evaluating these indicators collectively provides a more comprehensive assessment of a company’s performance and prospects, empowering investors to make informed investment decisions. Each line tells a different part of the company’s financial story, and understanding the interplay between them is crucial for investment decision-making.

Illustration

Income statement of Ford.
The Top Line, The Line, and The Bottom Line
Source: the company.

Why should I be interested in this post?

These concepts form the foundation of financial analysis and provide valuable insights into a company’s financial performance. Understanding the top line, which represents revenue or sales, is crucial as it demonstrates a company’s ability to generate income and sustain growth. The bottom line, which reflects the net income or profit after deducting expenses, taxes, and interest, provides a measure of overall profitability. By delving into the line, which encompasses various expenses impacting profitability, finance students can gain a comprehensive understanding of financial statements and develop the analytical skills necessary to evaluate a company’s financial health, make informed investment decisions, and contribute to effective financial strategies. This knowledge is highly applicable in various finance-related roles and is instrumental in navigating the complexities of the business world.

About the author

The article was written in June 2023 by Isaac ALLIALI (ESSEC Business School, Bachelor in Business Administration (BBA), 2019-2023).

Understanding the Gordon-Shapiro Dividend Discount Model: A Key Tool in Valuation

January 30, 2024June 2, 2023 by Isaac ALLIALI

Understanding the Gordon-Shapiro Dividend Discount Model: A Key Tool in Valuation

In this article, Isaac ALLIALI (ESSEC Business School, Bachelor in Business Administration (BBA), 2019-2023) explains about the Gordon-Shapiro Dividend Discount Model, which is a key tool in valuation.

Introduction

The Gordon-Shapiro Dividend Discount Model, also known as the Gordon-Shapiro formula and the Gordon Growth Model, is a central tenet in finance. It provides investors and financial analysts a simple tool to value a company based on its future dividends that are expected to remain at a constant growth rate. This model was named after economists Myron J. Gordon and Eli Shapiro, who developed it.

The Gordon-Shapiro formula

The Gordon-Shapiro formula is articulated through a relatively simple equation:

Gordon Shapiro formula

where:

V stands for the value of the stock.
DIV1 represents the expected dividend in the next period.
k is the investor’s required rate of return.
g is the constant growth rate of dividends.

This formula is premised on the idea that a company’s stock is worth the present value of all its future dividends.

Proof of the Gordon-Shapiro formula

To understand the derivation of the formula, let us consider a perpetuity model for valuing stocks. In a perpetuity model, the value of an asset is determined by the discounted value of its future cash flows. In the case of stocks, dividends represent the cash flows received by investors (shareholders or stockholders).

Assuming that the company pays a constant dividend indefinitely, the present value of the future dividends can be expressed as follows:

Gordon Shapiro formula

where DIV₁, DIV₂, DIV₃ and so on, represent the expected dividends in subsequent periods.

To simplify the formula, we assume that the dividend grows at a constant rate (g). This means that each subsequent dividend can be expressed as a multiple of the previous dividend:

Gordon Shapiro formula

Substituting these dividend expressions into the perpetuity formula, we have:

Gordon Shapiro formula

Inside the parentheses, we recognize an infinite geometric series with a ratio q equal to (1+g)/(1+k) for the geometric sequence.

Gordon Shapiro formula

The sum of an infinite geometric series denoted by S with a ratio q is equal to 1/(1-q). Applied to the case above, we obtain:

Gordon Shapiro formula

This leads to the Gordon Shapiro formula:

Gordon Shapiro formula

Simplifying further:

Gordon Shapiro formula

Therefore, the Gordon-Shapiro formula for estimating the intrinsic value of a stock is derived.

Assumptions of the Gordon Growth Model

The Gordon-Shapiro Dividend Discount Model is based on several key assumptions:

Constant Growth Rate: the model assumes that dividends grow at a constant rate indefinitely.

Required Rate of Return: the required rate of return exceeds the dividend growth rate. This condition is necessary for the formula to work.

Dividends: the company is expected to distribute dividends.

While these assumptions may not hold in all cases, they offer a starting point for the valuation process.

Applicability of the Gordon Growth Model

The Gordon Growth Model is especially useful in certain scenarios. For example, it is an excellent tool when assessing companies with stable growth rates, such as utility companies or large, mature firms.

However, the model has limitations when used for companies that don’t pay dividends or those with a dividend growth rate that is not consistent. High-growth companies, for instance, reinvest their profits for expansion rather than paying dividends. Similarly, companies facing fluctuating growth rates may present challenges for the model’s assumptions.

Example

After researching Pfizer’s data, we assume that this company pays an annual dividend per share (DPS) of $0.40. The required rate of return (k) for the company’s stock 9,16% was computed with the CAPM Model under the following assumptions: (Risk free rate of return= 4,73%; Beta of Pfizer stock is 0,62 and Market rate of return =11,88%), and the expected growth rate of dividends (g) is 6,40%.

Using the Gordon Shapiro formula:

Gordon Shapiro formula

In this example, based on the given assumptions, the Gordon Shapiro model estimates the intrinsic value (V0) of Pfizer’s stock to be $14.48 per share. The current market price of Pfizer’s stock ($37,60) is significantly higher than the estimated intrinsic value, it could suggest that the stock is potentially overvalued. This may indicate a cautionary signal for investors, as it implies that the stock’s market price may not be justified by the projected dividends and required rate of return. It’s important to note that the Gordon Shapiro model is a simplified valuation tool and relies on various assumptions. The actual value of a stock is influenced by numerous factors, including market conditions, company performance, industry trends, and investor sentiment. Investors should conduct further research, analyze additional factors, and seek professional advice before making investment decisions based solely on the findings of the Gordon Shapiro model or any other valuation model.

Conclusion

Despite its limitations, the Gordon-Shapiro Dividend Discount Model remains a valuable tool in financial analysis and investment decision-making. Its simplicity and focus on dividends make it an attractive model for investors, especially when applied appropriately and in the right context. Investors and financial analysts alike should understand this model as part of their toolkit for assessing a company’s inherent value.

Useful resources

SimTrade course Financial analysis

Gordon, Myron J., and Eli Shapiro (1956) “Capital Equipment Analysis: The Required Rate of Profit.” Management Science, 3(1): 102-110.

About the author

The article was written in June 2023 by Isaac ALLIALI (ESSEC Business School, Bachelor in Business Administration (BBA), 2019-2023).

My experience as an EMEA Regional Treasurer intern at Sanofi

June 2, 2023 by Isaac ALLIALI

My experience as an EMEA Regional Treasurer intern

In this article, Isaac ALLIALI (ESSEC Business School, Bachelor in Business Administration (BBA), 2019-2023) shares his professional experience an EMEA Regional Treasurer intern at Sanofi.

Sanofi

During my internship at Sanofi, a leading global pharmaceutical company headquartered in Paris, I had the privilege of working in the Treasury Department. Sanofi is renowned for its extensive research, development, manufacturing, and marketing of pharmaceutical products across various therapeutic areas. With a steadfast commitment to improving global health, Sanofi’s portfolio includes treatments for diabetes, cardiovascular diseases, vaccines, and rare diseases. As a key player in the pharmaceutical industry, Sanofi holds a significant share of the prescription market.

Logo of Sanofi.
Logo of
Source: the company.

Financial accounts

Income statement of Sanofi.
Logo of
Source: the company.

Strategy

Strategy of Sanofi.
Logo of
Source: the company.

My internship

As a Europe Middle East and Africa (EMEA) Regional Treasurer intern at Sanofi, my internship involved two main aspects. Firstly, I was responsible for reporting on the performance of the company’s subsidiaries on a monthly basis, focusing on key financial metrics such as Days Sales Outstanding (DSO), Days Payable Outstanding (DPO), Days Inventory Outstanding (DIO), and cash flows. This required analyzing financial data, preparing comprehensive reports, and providing insights into the subsidiaries’ financial health. I developed a deep understanding of financial ratios and gained proficiency in financial analysis and reporting.

Additionally, on a day-to-day basis, I played a vital role in implementing alternative banking channels to ensure the sustainability of cash receipts from high-risk countries. This involved close collaboration with banks and local teams to establish robust procedures and systems. To ensure accurate cash receipts matching with product sales, I diligently contacted banks and the local teams on a daily basis. This rigorous process involved verifying and validating each transaction, ensuring the precise quantity of products sold aligned with the corresponding justifying claims. By maintaining meticulous attention to detail, I ensured that every transaction was accurately registered and properly accounted for.

This aspect of my internship demanded strong communication skills, attention to detail, and the ability to manage complex transactions efficiently. It provided firsthand exposure to the challenges and intricacies of international banking operations, risk management, and compliance in high-risk countries.

During my internship as an EMEA Regional Treasurer at Sanofi, I had the additional responsibility of consolidating the representative offices’ register, which included all the bank accounts and power of attorneys (legal documents allowing appointed employees to make decisions on behalf of Sanofi).

This task required me to meticulously reconcile and align the information from various regions before the audit control. To ensure accuracy and completeness, I actively communicated with every regional treasurer, collaborating closely to verify the documentation and address any discrepancies. This process of effective communication and coordination with the regional treasurers was crucial in achieving a thorough and successful consolidation. By ensuring that everything was in order, I contributed to the smooth audit control process and maintained the integrity of the company’s financial records.

My missions

My internship involved two main aspects. Firstly, I was responsible for reporting on the performance of the company’s subsidiaries on a monthly basis, focusing on key financial metrics such as Days Sales Outstanding (DSO), Days Payable Outstanding (DPO), Days Inventory Outstanding (DIO), and cash flows. This required analyzing financial data, preparing comprehensive reports, and providing insights into the subsidiaries’ financial health. I developed a deep understanding of financial ratios and gained proficiency in financial analysis and reporting.

During my internship,I had the additional responsibility of consolidating the representative offices’ register, which included all the bank accounts and power of attorneys (legal documents allowing appointed employees to make decisions on behalf of Sanofi).

Required skills and knowledge

The EMEA Regional Treasurer role at Sanofi requires a combination of knowledge and skills. Here are key areas of expertise and proficiencies relevant to the position:

Financial Analysis: A strong foundation in financial analysis is essential for evaluating subsidiary performance, assessing financial health, and providing meaningful insights. Proficiency in financial ratios, financial modeling, and data analysis enables you to make informed decisions and recommendations.

Treasury Operations: Familiarity with treasury operations, including cash flow management, liquidity management, risk management, and financial reporting, is crucial. Understanding financial instruments, banking relationships, and compliance procedures ensures effective treasury operations and supports decision-making.

Communication and Collaboration: Effective communication skills are vital to engage and collaborate with internal stakeholders, such as regional financial management and local teams. Clear and concise communication fosters productive relationships and ensures the smooth execution of financial processes.

Attention to Detail and Compliance: Meticulous attention to detail is necessary when reporting on subsidiary performances and implementing alternative banking channels. Compliance with internal control procedures, risk mitigation protocols, and financial regulations ensures accuracy, transparency, and integrity in financial operations.

Analytical Thinking: Strong analytical skills are critical for analyzing financial data, identifying trends, and making data-driven decisions. The ability to evaluate risks, identify opportunities, and propose solutions contributes to effective financial management.

Adaptability and Problem-Solving: The dynamic nature of the role requires adaptability, as well as the ability to think critically and solve problems in a fast-paced environment. Resilience, flexibility, and a proactive approach enable you to navigate challenges and drive continuous improvement.

Financial concepts related my internship

Days Sales Outstanding (DSO)

DSO is a financial metric that measures the average number of days it takes for a company to collect payment after a sale is made. Monitoring DSO is crucial for assessing a company’s liquidity position and efficiency in collecting accounts receivable. During my internship, I actively analyzed and reported on DSO, gaining a practical understanding of its significance in cash flow management.

Days Payable Outstanding (DPO)

DPO is a financial metric that measures the average number of days it takes for a company to pay its suppliers after receiving an invoice. Managing DPO effectively is essential for optimizing working capital and maintaining strong supplier relationships. In my reporting responsibilities, I monitored and analyzed DPO, contributing to a comprehensive assessment of the company’s financial performance.

Cash Receipts and Compliance

Ensuring the accurate and timely recording of cash receipts is vital for financial integrity. Implementing alternative banking channels and verifying transactions from high-risk countries required a keen eye for detail and compliance with internal control procedures. This experience emphasized the importance of maintaining rigorous standards to mitigate risk and ensure accurate financial reporting.

Why should I be interested in this post?

The role of EMEA Regional Treasurer at Sanofi offers a compelling opportunity for individuals interested in finance, treasury operations, or the pharmaceutical industry. Here are a few reasons why you should be interested in this post:

Industry Leadership: Sanofi is a global leader in the pharmaceutical industry, renowned for its innovative research and development. Joining the Treasury Department of such a prominent company provides exposure to the complexities of finance within a multinational pharmaceutical corporation, offering a unique and valuable experience.

Financial Responsibility: As an EMEA Regional Treasurer, you would have a significant role in managing the financial assets of Sanofi across the EMEA region. This level of responsibility allows you to make strategic financial decisions, analyze financial performance, and contribute to the company’s financial health.

International Exposure: Working within the EMEA region exposes you to diverse markets, cultures, and business practices. It presents an opportunity to develop a global mindset, adaptability, and cross-cultural communication skills, which are increasingly valuable in today’s interconnected business world.

Learning Opportunities: The Treasury Department at Sanofi offers a dynamic and challenging environment where you can continually enhance your financial knowledge and skills. You will gain exposure to various aspects of treasury operations, financial risk management, liquidity management, and financial reporting.

Impactful Contributions: By actively participating in the implementation of alternative banking channels, you will contribute to ensuring the sustainability of cash receipts from high-risk countries. This responsibility allows you to make a tangible impact on the company’s financial operations and play a vital role in managing financial risks.

Useful resources

Sanofi

Careers at Sanofi

About the author

The article was written in June 2023 by Isaac ALLIALI (ESSEC Business School, Bachelor in Business Administration (BBA), 2019-2023).

The Psychology of Trading

May 29, 2023 by Theo SCHWERTLE

The Psychology of Trading

In this article, Theo SCHWERTLE (Maastricht University, School of Business and Economics, Bachelor in International Business, 2023) explains how behavioral biases can influence trading of market aprticiapnts.

Behavioral biases of investors

In complex decision environments, people use basic judgements and preferences to simplify the scenario rather than adhere to a strictly rational approach. This use of mental shortcuts is called heuristics, which are quick and instinctively appealing but may result in poor outcomes (Tversky and Kahneman, 1974). The traditional financial theory (based on expected utility theory) assumes that people are rational agents. In contrast to traditional financial theory, behavioral theories argue that people are generally risk-averse with a skewed view of probability (Kahneman and Tversky, 1979). Some common behavioral biases that have been identified in the literature on investment decisions include overconfidence, the disposition effect and herding behavior.

Prospect Theory

We start with the two main drivers of irrationality: value perception and probability perception.

Value perception. The value function proposed by Kahneman and Tversky (1979) is characterized by the following features. First, it is determined based on departures from a reference point. Second, it typically has a downward, concave slope for gains and an upward, convex slope for losses. This suggests that individuals perceive losses as more painful gains as shown in Figure 1.

Figure 1. Perceived value function.

Source: Kahneman and Tversky (1979).

Probability perception. Individuals tend to assign a lower probability value to outcomes that are more likely to occur and, a higher probability value to outcomes that are less likely to occur as shown in Figure 2.

Figure 2. Perceived probability.

Source: Kahneman and Tversky (1979).

Overconfidence

Overconfidence manifests as an inclination to have an irrationally excessive level of trust in one’s own abilities and opinions and has been thoroughly investigated across many fields (Fischhoff et al., 1977).

Gervais and Odean (2001) explore how overconfidence develops as a result of a dynamic change in beliefs about one’s ability after observing successes and failures. Successful traders tend to be overconfident due to attributing too much credit to their own ability. They showed that overconfidence is highest among inexperienced traders, as proper self-assessment only develops over time. This leads to suboptimal behavior, such as increased trading volume and volatility, lower expected profits, and poor information utilization (Statman et al., 2006).

Ekholm and Pasternack (2007) investigate the link between overconfidence and investor size.
They show that larger investors are less overconfident than small investors. They also show that larger investors, on average, react more positively to good news and more negatively to bad news than smaller investors. Evidence suggests that smaller, more overconfident investors have worse performance following negative news (Ekholm and Pasternack, 2007).

Grinblatt and Keloharju (2009) argue that sensations seekers (people receiving more speeding tickets) and those who showed more overconfidence as measured by a psychological assessment traded more than the average, even after controlling for other factors that might explain trading activity like age, income and gender. Similarly, individual investors tend to buy stocks that have recently caught their attention, like stocks with high trading volume, extreme one-day returns, or those in the news, whereas institutional investors, especially those who follow a value strategy, do not (Barber and Odean, 2007). These results are confirmed by Barber et al. (2022) as Robinhood users, which are, as evidence suggests, less experienced traders, trade substantially more high-attention stocks.

Additionally, men are more prone to overconfidence than women, particularly in male-dominated industries like finance. Thus, men trade more than women and perform worse in terms of returns. Male investors not only engage in more frequent trading but, compared to female investors, also hold larger and less diversified portfolios (Barber & Odean, 2001; Lepone et al., 2022).

Why should I be interested in this post?

This post explores heuristics and behavioral biases in decision-making, particularly in the context of investment decisions. Overconfidence can lead to poor outcomes. Additionally, it touches on gender differences, with men being more prone to overconfidence and engaging in more frequent trading. By understanding these biases, readers can gain insights into human behavior, make more informed investment decisions, and explore the impact of gender on financial outcomes. Overall, this post offers valuable insights into decision-making processes and their implications.

Useful resources

Barber, B.M. and Odean, T. (2007) All That Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors Review of Financial Studies 21(2):785–818.

Barber, B.M. and Odean, T. (2001) Boys will be Boys: Gender, Overconfidence, and Common Stock Investment The Quarterly Journal of Economics 116(1):261–292.

Ekholm, A. and Pasternack, D. (2007) Overconfidence and Investor Size European Financial Management.

Fischhoff, B., Slovic, P. and Lichtenstein, S. (1977) Knowing with certainty: The appropriateness of extreme confidence. Journal of Experimental Psychology: Human Perception and Performance 3(4):552–564.

Gervais, S. and Odean, T. (2001) Learning to Be Overconfident Review of Financial Studies 14(1):1–27.

Grinblatt, M. and Keloharju, M. (2009) Sensation Seeking, Overconfidence, and Trading Activity The Journal of Finance 64(2):549–578.

Kahneman, D. and Tversky, A. (1979) Prospect Theory: An Analysis of Decision under Risk Econometrica 47(2): 263.

Lepone, G., Westerholm, J. and Wright, D. (2022) Speculative trading preferences of retail investor birth cohorts Accounting & Finance.

Statman, M., Thorley, S. and Vorkink, K. (2006) Investor Overconfidence and Trading Volume Review of Financial Studies 19(4):1531–1565.

Tversky, A. and Kahneman, D. (1974) Judgment under Uncertainty: Heuristics and Biases Science 185(4157):1124–1131.

About the author

The article was written in May 2023 by Theo SCHWERTLE (Maastricht University, School of Business and Economics, Bachelor in International Business, 2018-2023).

My professional experience as B2B Project assistant manager at Dance

May 29, 2023 by Theo SCHWERTLE

My professional experience as B2B Project assistant manager at Dance

In this article, Theo SCHWERTLE (Maastricht University, School of Business and Economics, Bachelor in International Business, 2023) shares his experience as a B2B Project assistant manager at Dance which is a start-up in urban mobility.

About the company

Dance is a progressive company that is reshaping urban mobility by providing an electric mobility subscription service. The company offers members the freedom to explore their city with an electric bike or moped, with maintenance and repairs included in the membership. Founded by the creators of SoundCloud and Jimdo, Dance is currently operating in Berlin, Hamburg, Munich, Vienna, and Paris, with a focus on making urban commuting more connected, convenient, and environmentally friendly.

Logo of the company.
Logo of Dance
Source: Dance.

My internship

As part of the Dance for Business department, I was privileged to contribute to various crucial aspects of the business, including the development and standardization of Business-to-Business (B2B) playbooks for client outreach, engagement, and account management. I also had the opportunity to manage the company pipeline using our Customer Relationship Management (CRM) tool, conduct competitive market research, and collaborate with cross-functional teams to execute lead generation strategies and client retention initiatives.

My missions

My mission at Dance was multifaceted, encompassing both client relationship management and sales strategy. I was responsible for creating and developing B2B pitch decks, preparing and supporting pitch meetings with new clients, and building long-term relationships with our clients to provide the best service possible. Serve as the first point of contact for all B2B clients, but also to find new strategies to acquire more customers. Furthermore, we were making Partnership deals with other service providers to spread the word about the mobility solution that Dance offers.

Required skills and knowledge

This role required strong interpersonal skills for building and maintaining client relationships, as well as proficiency in using CRM tools to manage the company pipeline. It also called for a solid understanding of sales strategies and market research methodologies. Since we were only a small team, communication and constant prioritization of tasks was paramount. Interpersonal skills have strongly increased during that time since I was constantly pitching to the management of firms like AboutYou or Inditex while also taking care of our current clients.

What I learned

Project Management: In preparing B2B pitch decks and supporting pitch meetings, you would have honed your project management and organization skills.

Communication: Being the first point of contact for all B2B clients and building long-term relationships with them would have strengthened your communication and interpersonal skills.

Strategic Thinking: Conducting competitive market research and collaborating on lead generation strategies likely helped develop your strategic thinking and market analysis abilities.

Problem Solving: Proposing solutions in line with business objectives and incorporating new initiatives shows your problem-solving capabilities.

Financial concepts related my internship

Customer Acquisition Cost (CAC)

Customer Acquisition Cost (CAC) refers to the total expenses a company incurs to convince a potential customer to purchase its product or service. It includes costs related to marketing and sales efforts and is a key metric for determining the return on investment for acquisition strategies.

Contribution Margin

Contribution Margin is a financial metric that calculates the profitability for individual items sold by a company. It is determined by subtracting the variable costs (costs that change with the amount of goods or services produced) associated with a product from the revenue generated by that product.

Customer Lifetime Value

Customer Lifetime Value (LTV) is a projection of the total net profit a company expects to earn from a customer throughout the business relationship. It takes into account the revenue a customer would generate, the costs of acquiring and serving the customer, and the duration of the relationship with the customer.

Why should I be interested in this post?

If you’re looking to gain insights into the world of business operations or contemplating a career in a similar industry, this post should be of high interest to you. The financial concepts discussed here form the backbone of many successful businesses. Understanding these concepts can help you view business operations from a new perspective, providing you with a solid base for making informed decisions.

Furthermore, sharing my experience at Dance provides an insider’s perspective into how the start-up operates and how different roles contribute to its success.

My experience at Dance was nothing short of enriching. With the right blend of motivation, attention to detail, and focus on business objectives, I was able to contribute effectively to the company’s success. I hope my insights will inspire and guide those looking to embark on a similar professional journey.

Useful resources

Dance

About the author

The article was written in May 2023 by Theo SCHWERTLE (Maastricht University, School of Business and Economics, Bachelor in International Business, 2018-2023).

The Collapse of Silicon Valley Bank (2023)

May 19, 2023 by Mirabelle DING

The Collapse of Silicon Valley Bank (2023)

In this article, Mirabelle DING (Telfer School of Management, Bachelor in Finance, 2015-2019) analyzes the collapse of Silicon Valley Bank (SVB).

On March 10^th 2023, Silicon Valley Bank, the primary financial institution for the US technology sector, was shut down by California and Federal regulators due to illiquidity and insolvency concerns after depositors withdrew $42 billion within a single day, marking the second largest bank failure in the United States history.

Background of SVB

Silicon Valley Bank (SVB) was founded in 1983 in the Bay Area with its mission to provide banking services to venture capital-backed startups that would have been considered high risk by traditional banks. As a result of its pioneering vision, SVB had established a notable reputation among the tech community, and was providing financing services to nearly half of the venture-backed technology and life science companies in the United States. SVB was ranked the 16^th largest bank in the United States with total assets of $209 billion and was recognized as one of America’s Best Banks by Forbes for five consecutive years before its defunction.

Logo of Silicon Valley Bank.

Source: Silicon Valley Bank.

The Solvency-Liquidity Problem

In 2020, the Federal Reserve cut the Federal Funds rate down to a range of 0% to 0.25% and implemented an unlimited quantitative easing policy in response to the impact of the Covid-19 pandemic, which led to a substantial increase in the financial market’s liquidity and the price of financial assets. The deposit base of SVB also experienced a skyrocket from $60 billion to an impressive $190 billion by the end of 2021. With little demand for loans from its clients, SVB allocated almost three quarters of the incremental deposits in long-maturity US Treasury bonds and mortgage-back securities purchases in order to gain capitalize on the interest rate spread. As a result, SVB exposed itself to greater interest rate and market risks.

Starting from March 2022, the Federal Reserve started to raise the Funds rate to counter inflation. The benchmark rate hiked to 4.5%-4.75% within 12 months, causing a plunge in the financial market liquidity and a severe inverted yield curve of long-term bonds and securities.
As interest rates rose, SVB started suffering deep unrealized losses on much of its securities portfolio, amounting to more than $2 billion by the end of 2022.

Furthermore, due to the declining inflow of venture capital funding, many tech start-ups resorted to withdrawing from SVB to support their daily operations. From March to December, the deposits of SVB shrank rapidly from $200 billion to $175 billion. Since SVB did not protect their liabilities with short term investments for quick liquidations, they had to start selling their bonds at a significant loss and relied heavily on short term loans from Federal Home Loan Banks to accommodate these large withdrawals, totaling $15 billion by the end of 2022.

“The Social Media Bank Run”

On March 8^th 2023, SVB announced a $1.8 billion loss on its investment portfolio, alongside a plan to raise $2.25 billion. Consequently, Moody’s downgraded the bank’s credit rating, and the stock price of SVB’s parent company, SVB Financial Group, crashed at the next market opening. Prominent entrepreneurs raised concerns about SVB’s financial situation on social media, which went viral and amplified the panic among the bank’s clients. Depositors rushed to withdraw from their SVB account, culminating a total amount of $42 billion in attempted withdraws within 24 hours. SVB was on the verge of collapse as they could not generate enough cash to meet the escalating need for withdrawals.

On March 10^th 2023, the Federal Deposit Insurance Corporation, which protects the stability of the financial system, took over Silicon Valley Bank in an effort to protect depositors. Unlike personal banking, most clients held more the $250,000 FDIC insured limit in their accounts, putting them at the risk of losing a portion or all of their deposits that exceeded the threshold. To restrain the fear of financial contagion, the Federal Reserve later implemented emergency measures, ensuring that all deposits at SVB will be guaranteed, even for the amount above the $250,000 limit.

Later, the Federal government announced an emergency lending programing to allow distressed banks to borrow from the Federal Reserve as a contingency liquidity plan to cover their withdrawal needs and to restore public confidence in the financial system.

Conclusion

The collapse of SVB reflected an inadequacy in its risk management and strategy, which could have been avoided through regular review and valuation of their investment portfolio, avoidance of concentrating assets in long-term maturities, possession of sufficient liquid assets, and hedging strategies against rising interest rate. This demonstrates the importance for businesses and organizations to properly and promptly manage their financial risk to prevent or mitigate situations that may lead to financial distress.

Useful resources

Apricitas Economics The Death of Silicon Valley Bank

The Federal Reserve Re: Review of the Federal Reserve’s Supervision and Regulation of Silicon Valley Bank

About the author

The article was written in May 2023 by Mirabelle DING (Telfer School of Management, Bachelor in Finance, 2015-2019).

My experience as City Manager at HungryPanda

May 19, 2023 by Mirabelle DING

My experience as City Manager at HungryPanda

In this article, Mirabelle DING (Telfer School of Management, Bachelor in Finance, 2015-2019) shares her professional experience as City Manager at HungryPanda Tech.

About the company

HungryPanda Tech is a global platform focused on overseas Asian community, covering food delivery, online grocery, retail, and lifestyle services. Founded in 2017 in Nottingham, the United Kingdom (UK), HungryPanda has expanded its operations to more than 80 cities in 10 countries, with 3.5 million registered users and over 60,000 merchant partners.

Logo of HungryPanda.

Source: HungryPanda.

The operation team is typically composed of three segments: business development, marketing, and delivery operations. The business development team manages accounts for our existing merchant partnerships and reaches out to new business opportunities. The marketing team is responsible for the promotion of the platform and customer acquisition, as well as negotiating sponsorship with local events. The delivery team ensures the efficiency of the delivery dispatch, quality of service, and recruitment of new carriers. The city manager oversees the workflow and coordinates the three departments to ensure seamless teamwork and achievement of the company’s goal.

My job

I worked as City Manager at HungryPanda for the Toronto Area, which is equivalent to Business Manager.

My missions

As City Manager at HungryPanda, my primary mission was to expand market share and enhance profitability.

Asian food delivery is a niche but competitive market in Toronto. To reinforce the competitive advantage of the company, my team and I had to regularly conduct market research, including industry trends, consumer behaviour analysis, and competitor analysis, to develop strategies and stay on top of the game. For example, we initiated a virtual kitchen program with selective partner merchants, where we researched and identified marketable dishes that were popular in areas with a similar demographic as our customer base. We collaborated with the merchants to design the menu and build exclusive virtual brands that were innovative and appealing to the consumers, which helped the merchants boost their revenue while mitigating the risk of modification on their original menus.

Another important duty of the city manager is to analyze the operational and financial data. The financial analysis includes breaking down the contribution margin of each of our merchant partners and evaluating the return on investment (ROI) of each project and market campaign, which is crucial in understanding our financial performance. The operational data analysis, on the other hand, entails app traffic flow, conversion rate, customer retention rate, redemption rate of discount coupons, etc., which facilitates identifying areas of improvement and optimizing the allocation of online resources. For example, if we launch a promotional discount on selective merchants alongside in-app advertising and text message marketing, analyzing the contribution margin and the customer retention rate of each merchant can help us determine the merchants that will continue to generate growth even after the discount period ends. This approach allowed us to maximize the return on our budget spending and ensure efficient utilization of marketing resources.

Knowledge and skills

During my time at HungryPanda, I have come to recognize several important skills that are essential for business operations:

Effective communication and coordination among different departments
Financial analysis and forecasting to support sustainable growth
Strategic planning to identify opportunities and challenges
Adaptability to react and adjust strategies in a dynamic business environment

Financial concepts related my job

I describe below the following financial concepts related my job: contribution margin, Gross merchandise volume, and the lifetime value (LTV) to customer acquisition cost (CAC) ratio.

Contribution margin

The contribution margin is calculated by sales revenue less the variable costs, and it represents the available revenue to cover the fixed costs (rent, salaries, market spending, etc.). I used contribution margin analysis to identify the profitability of each project and market campaign, and thereby determined which project or market campaign to continue and to invest in.

Gross merchandise volume

Gross merchandise volume (GMV) is the total money value of transactions on the platform. We used GMV as a key performance indicator to assess the scale and growth of our business and to track the overall performance of our long-term operational strategies.

LTV to CAC ratio

The lifetime value (LTV) to customer acquisition cost (CAC) ratio is the expected revenue from new customers relative to the cost of acquiring them. To encourage potential customers to try out the products and services offered on our platform, we frequently launched campaigns targeted at new registers, including offline promotional giveaways, new user discounts, referral rewards, etc. It is essential to analyze the customer acquisition cost and Lifetime value to evaluate the effectiveness and sustainability of each acquisition channel.

Why should I be interested in this post?

The experience at HungryPanda has instilled in me the importance of financial analysis and forecasting in making informed decisions for business operations. I hope this post shares some perspectives on how the application of financial concepts is used in driving business growth and improving profitability.

Useful resources

HungryPanda

About the author

The article was written in May 2023 by Mirabelle DING (Telfer School of Management, Bachelor in Finance, 2015-2019).

Key participants in the Private Equity ecosystem

May 18, 2023 by Matisse FOY

Key participants in the Private Equity ecosystem

In this article, Matisse FOY (ESSEC Business School, Bachelor in Business Administration (BBA), 2019-2023) explains who the key participants in Private Equity (PE) are, and what are their role in the PE ecosystem.

Private Equity is an increasingly important model of financing for companies at different scales. Whether you’re simply interested in the subject or want to find a professional experience, here is a list of the main participants in the PE ecosystem and their function.

Key participants in the Private Equity ecosystem

Source: production by the author

A glossary of the participants

Private Equity funds

PE funds are the central actors in the private equity ecosystem, pooling capital from various sources (mainly from Limited Partners and Investment Banks) and invest this money in private companies, meaning companies whose shares cannot be freely bought and sold on the stock market.

The employees of PE funds are responsible for sourcing, evaluating, and managing investments in “Portfolio Companies”.

Their objective is to enhance the performance of those Portfolio Companies. By doing so, they aim to sell these firms later and generate profit. This profit is primarily derived from the investment capital provided by their investors, from which they take a percentage as their fee.

General Partners (GPs)

These are the managers of the PE fund who make the investment decisions. They have a fiduciary duty to act in the best interest of the LPs.

GPs are typically compensated through a management fee, which is a fixed annual fee for the fund’s operation, and a performance fee (also known as “carry”), which is a percentage of the profits of the fund.

Limited Partners (LP)

Limited Partners are the investors in a PE fund. They include institutional investors like pension funds, university endowments (like Harvard University endowment), insurance companies (e.g., AXA, Allianz), and sovereign wealth funds, as well as high net worth individuals.

Limited Partners provide the capital that the PE funds invest and expect a return on their investment.

Portfolio Companies

Portfolio Companies are the companies in which PE funds invest. They are often in need of capital for growth, restructuring, or as part of a strategy to transition the company from public to private.

The goal of PE funds is to take a share in these companies, improve their performance and sell them for a profit.

Investment Banks

Investment Banks often play a crucial role in the PE ecosystem, especially with regards to the acquisition and sale of portfolio companies by PE funds. They can help PE funds identify potential investment opportunities, facilitate transactions, and provide financing by leveraging Limited Partners’ equity. Moreover, they can help portfolio companies go public when they are sold.

Law Firms and Consultants

These professional service providers support PE funds throughout the investment process:

Law firms help with legal aspects of transactions, including drafting and reviewing contracts, to ensure compliance with relevant laws and regulations, and advising on the structure of deals to minimize legal risks and tax liabilities.
Consultants, on the other hand, assist with due diligence and the development of strategies for improving the performance of portfolio companies. They might also be delegated the sourcing and contact with portfolio companies by PE funds.

Regulators

Regulators oversee and govern the operations of PE funds. They aim to protect the interests of investors and the integrity of the financial markets, in order for the local environment to be as attractive to invest in as possible.

Why should I be interested in this post?

Private Equity is a wide ecosystem. Knowing about its different participants is very important when deciding to work in one of them, in order to understand their importance (who knows, maybe you will be asked questions about these actors will be asked to you in your next interview).

Useful resources

The Financial Times Private Equity

Wall Street Journal Private Equity

Coursera’s MOOC Private Equity and Venture Capital

About the author

The article was written in May 2023 by Matisse FOY (ESSEC Business School, Bachelor in Business Administration (BBA), 2019-2023).

My professional experience as an Assistant to the CFO at Association Science Ouverte

May 18, 2023 by Matisse FOY

My professional experience as an Assistant to the CFO at Association Science Ouverte

In this article, Matisse FOY (ESSEC Business School, Bachelor in Business Administration (BBA), 2019-2023) shares his professional experience as an Assistant to the CFO at Association Science Ouverte.

About the structure

The missions of the Science Ouverte Association are “to open young people to science and science to young people, to fight against a feeling of powerlessness and confinement often too present”. It aims to create a visible and effective structure in Seine-Saint-Denis, capable of arousing scientific vocations and helping young people who are committed to this path.

It offers various activities, especially to high school students: tutoring, science and technology courses, various workshops on 3D graphics, programming, etc.

Logo of Science Ouverte Association
Logo of Association Science Ouverte
Source: Association Science Ouverte

I was a part of the Finance Department, a critical unit within the organization that was responsible for managing the association’s financial resources. As a district association, our department was made of only two people: the CFO and me.

The Finance Department oversees a wide range of functions, including budgeting, accounting, and financial reporting. It also plays a strategic role in decision-making processes by providing financial analysis to guide the association’s decisions.

Furthermore, the Department works with external stakeholders, such as auditors, as well as private and public funders.

My internship

My missions

Throughout my internship, I was tasked with various missions to operate and enhance the accounting and financial tools of the Association. Those missions had both short-term, operational objectives, and long-term objectives. Here is what they mainly consisted in:

Preparation of files for the audit of the accounts
Improving timesheet maintenance (e.g., adding indicators and summary tables for them to be as ergonomic and easy to use as possible)
Verification and updating of financial statements, individual funds and association budgets.

Required skills and knowledge

To work in a corporate finance position and be efficient at your job, you will need to acquire many skills:

Knowledge of financial concepts: During my internship, I was accompanied by the CFO in my learning of specific financial notions related to an association. My previous knowledge of finance and accounting helped understand and assimilate those notions faster.
Basic knowledge of a spreadsheet like Excel: In most structures, Excel will play a key role in your everyday job. Don’t forget to learn basic Excel skills and shortcuts to save time and make your tasks easier.
An understanding of the organization’s industry: Each structure has its financial specificities in terms of business model, objectives and regulatory environment. Learning about them as soon as possible will help shape your decision to be most effective.

What I learned

This experience brought me key valuable lessons about professional environment and work ethic. Here are three of them:

Attention to details: my time in the Finance department taught me how every piece of documentation, and every penny is important. The margin for error is low, and it allowed me to become meticulous is my work.
Effective communication: clear, concise, and timely communication was vital when communicating with my colleagues and superior to accomplished task I was assigned to. When confronted with a new problem, I did not hesitate to contact relevant persons if I couldn’t find the solution myself.
Proactivity: I tried to show initiative, anticipate needs, and propose solutions to existing problems that weren’t directly asked by my manager. This helps to create a positive impression and demonstrate your commitment.

Financial concepts related my internship

Financial forecasting

Financial forecasting refers to the process of estimating the future financial performance of an organization. These forecasts played a crucial role in strategic planning, helping the organization know what they could be able to invest in or not in the months and years to come.

Budgeting

Budgeting allows to estimate revenues and expenditures over a future period. During my internship, I saw how a well-structured budget serves as a roadmap, guiding the association’s financial decisions, and keeping the organization on track financially.

Financial Reporting

Financial reporting involves the process of producing statements that disclose an organization’s financial status to funders and the government. As part of my role, I helped in the preparation of the 2021 and had to work on financial reports. These reports were critical in understanding the financial health of the association, making informed decisions, and ensuring regulatory compliance.

Why should I be interested in this post?

An experience in the financial department of an association helps apply your theoretical knowledge about finance while taking a step back about its role: concretize the most impactful project by allocating resources, reporting, and optimizing them, to get the most of every euro you inject in the structure’s activities.

As I was working next to the association’s activity rooms, it was really gratifying to see that my work has a concrete influence on the young people the association is helping.

Useful resources

Association Science Ouverte

About the author

The article was written in May 2023 by Matisse FOY (ESSEC Business School, Bachelor in Business Administration (BBA), 2019-2023).

My professional experience as a Strategy and Innovation Consultant at Planet Impact Advisory

May 18, 2023 by Matisse FOY

My professional experience as a Strategy and Innovation Consultant at Planet Impact Advisory

In this article, Matisse FOY (ESSEC Business School, Bachelor in Business Administration (BBA), 2019-2023) shares his professional experience as a Strategy and Innovation Consultant at the firm Planet Impact Advisory.

About the company

Planet Impact Advisory is a consulting firm located in Paris and providing strategy consulting services for corporates and venture funds.

The firm uses methodologies mixing strategy consulting, design thinking, and a strong entrepreneurial approach to solve challenges and build impactful projects.

Its missions range from accompanying a mid-size company in the establishment of an investment strategy in the health sector, to the construction of a European program and two innovative platforms to solve the talent crunch in the health sector.

Logo of Planet Impact.

Source: Planet Impact.

My internship experience

My missions

My assignments within the firm were extremely diverse. I was assigned in the mobility, human resources (HR) and even healthcare sectors. These missions mainly consisted in:

Sourcing, production of one-pagers, presentation, and matchmaking with startups for a Swiss-German CVC (Corporate Venture Capital Fund)
Construction of the strategic documentation and support for a fundraising for a startup in the HR Tech / Future of Work.
Conceptualization and competitive analysis of two innovative platforms for an organization in the health sector
Participation in the construction of a database of 2,500 startups in the mobility sector.

Required skills and knowledge

Many soft skills are required to perform in the consulting world:

Strong analytical skills: much the work involves interpreting complex data through dense literature and translating it into actionable strategies.
Communication: whether when facing your superiors or clients, you need to be able to communicate idea in a concise and effective way.
Business fundamentals: you don’t need to be an expert with 10 years of experience in each and every business sector you will be working in, but you should at least know about the core aspects of marketing, finance, and project management.

What I learned

This experience brought me key valuable lessons about professional environment and work ethic. Here are three of them:

Be honest about what you can do and not to do in a timely manner. Being a people pleaser is not a good thing if you get buried under the workload that you will have accepted.
Learn to accept criticisms: there is always room for improvement, especially when starting an experience: don’t take criticism from your superiors personally, and show that you apply it.
Keep an eye for the details: the work you’re sending to the clients must be of excellent quality. One of the witnesses of this quality is the documentation that will be sent to them: check and double-check your work to avoid grammar or spelling errors.

Financial concepts related my internship

Return on Investment (ROI)

The ROI helps determine the profitability of an investment or compare the efficiency of different investments by measuring the gain or loss made on an investment relative to the amount of money invested. In consulting, you need to help clients make informed decisions about where they should be investing their money to get the most out of it.

Financial leverage

Financial leverage refers to the borrowed money used to finance the purchase of assets. In consulting, understanding a client’s industry and risk aversion with regards to how much financial leverage it is willing to take is crucial before taking any financial decision.

Profit margin

Profit margin is a profitability ratio calculated as net income divided by revenue, or net profits by sales. It measures how much percentage of sales a company keeps in earnings. Using profit margin analysis helps understand a company’s pricing strategy and cost structure, providing insights into the company’s operational efficiency.

Why should I be interested in this post?

Sometimes, thinking narrowly about your dream career can cut you off from excellent professional opportunities.

During my search for an internship, I was primarily interested in finance, but my position at the firm was not exclusively dedicated to this area. However, this opportunity broadened my horizons and allowed me to approach financial topics in a different context than finance-oriented position. This experience was thus unique compared to most people who wish to pursue a career in finance.

So, the next time you are looking for a professional experience, don’t hesitate to think broader about what you want to learn.

Useful resources

Planet Impact

About the author

The article was written in May 2023 by Matisse FOY (ESSEC Business School, Bachelor in Business Administration (BBA), 2019-2023).

The DAX 30 index

May 14, 2023 by Nithisha CHALLA

The DAX 30 index

In this article, Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management, 2021-2023) presents the DAX 30 index and details its characteristics.

The DAX 30 index

The largest and most liquid 30 publicly traded German companies are represented by the DAX 30 index. This index was established by the Frankfurt Stock Exchange on July 1, 1988. “Deutscher Aktienindex” or the German stock index in English, is abbreviated as DAX. Deutsche Boerse AG, which also runs the Frankfurt Stock Exchange, is in charge of managing the DAX 30.

The choice of the companies for the DAX index is based on a number of variables, such as trading volume, market capitalization, and liquidity. The Deutsche Boerse Index Commission regularly modifies and reviews the index’s composition, ensuring that DAX 30 accurately captures the overall performance of the German stock market.

The DAX 30 is a free float market capitalization-weighted index, which means that each company’s weight in the index is based on the calculation of its market capitalization. The performance of the German stock market is measured against the DAX 30, which is closely monitored by traders and investors worldwide. Investors and traders wishing to follow the performance of the German stock market can easily access the index as it is published and distributed in real-time by several financial news sources.

The ticker symbol “DAX” is used in trading platforms and financial websites to identify the DAX 30.

Table 1 below gives the Top 10 stocks in the DAX 30 index in terms of market capitalization as of January 31, 2023.

Table 1. Top 10 stocks in the DAX 30 index.

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

Calculation of the DAX 30 index value

The performance of the 30 largest and busiest German companies listed on Frankfurt Stock Exchange is reflected in the DAX 30, a blue-chip stock market index. A free-float market-capitalization-weighted methodology is utilized to calculate the index, which means that each company’s weight in the index is determined by its market capitalization adjusted for the shares that are actually traded in the secondary market (float).

The formula to compute the DAX 30 index is given by

Float Adjusted Market Capitalization Index value

In a float-adjusted market-capitalization-weighted index, the weight of asset k is given by formula

Float Adjusted Market Capitalization Weighted Index Weight

Use of the DAX 30 index in asset management

Investors can examine the sector weightings and geographic exposure of the index to gain insights into performance of the German economy to identify potential opportunities and risks in particular industries or regions. Asset managers compare performance of their equity portfolios to the performance of the complete market using the DAX 30 as the benchmark. Multiple investment products, including exchange-traded funds (ETFs), options, and futures contracts, all have the index as the starting point.

Benchmark for equity funds

One of the highly significant indices in Europe, the DAX 30 serves as standard for the overall performance of German stock market. The businesses represent numerous industries, including those in the automotive, financial, healthcare, technology, and retail sectors. Asset managers and investors use the DAX 30 as the benchmark to compare performance of their portfolios to that of the market as a whole. It is used as gauge of investor sentiment toward the nation’s businesses and financial markets as well as a barometer for the health of the German economy.

Financial products around the DAX 30 index

There are various financial products available that allow investors to gain exposure to German equity market through the DAX 30 index.

ETFs are investment funds traded on stock exchanges which are designed to track the performance of an index. Some of the ETFs that track the DAX 30 index include the iShares DAX UCITS and the X Trackers DAX UCITS.
Index funds are designed to track the performance of the index. Examples of the index funds based on the DAX 30 index include the DWS Deutschland Index Fund and the Allianz DAX Index Fund.
Futures and options contracts based on the DAX 30 index provide investors with ability to speculate on the future performance of the index. Eurex offers futures and options contracts based on the DAX 30 index.
Certificates are investment products allowing investors to gain exposure to the DAX 30 index. Commerzbank offers a range of certificates linked to the DAX 30 index, such as the ComStage DAX UCITS ETF.

Overall, these financial products offer investors the ability to diversify their portfolios and gain exposure to German equity market, as well as potentially benefit from the performance of the DAX 30 index.

Historical data for the DAX 30 index

How to get the data?

The DAX 30 index is the most common index used in finance, and historical data for the DAX 30 index can be easily downloaded from the internet.

For example, you can download data for the DAX 30 index from December 30, 1987 on Yahoo! Finance (the Yahoo! code for DAX 30 index is ^GDAXI).

Source: Yahoo! Finance.

You can also download the same data from a Bloomberg terminal.

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 DAX 30 index.

Data file

The R program that you can download above allows you to download the data for the DAX 30 index from the Yahoo! Finance website. The database starts on December 30, 1987. It also computes the returns (logarithmic returns) from closing prices.

Table 3 below represents the top of the data file for the DAX 30 index downloaded from the Yahoo! Finance website with the R program.

Table 3. Top of the data file for the DAX 30 index.
Top of the file for the DAX 30 index data
Source: computation by the author (data: Yahoo! Finance website).

Evolution of the DAX 30 index

Figure 1 below gives the evolution of the DAX 30 index from December 30, 1987 to December 30, 2022 on a daily basis.

Figure 1. Evolution of the DAX 30 index.

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

Figure 2 below gives the evolution of the DAX 30 index returns from December 30, 1987 to December 30, 2022 on a daily basis.

Figure 2. Evolution of the DAX 30 index returns.

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

Summary statistics for the DAX 30 index

The R program that you can download above also allows you to compute summary statistics about the returns of the DAX 30 index.

Table 4 below presents the following summary statistics estimated for the DAX 30 index:

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 4. Summary statistics for the DAX 30 index.

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

Statistical distribution of the DAX 30 index returns

Historical distribution

Figure 3 represents the historical distribution of the DAX 30 index daily returns for the period from December 30, 1987 to December 30, 2022.

Figure 3. Historical distribution of the DAX 30 index 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 December 30, 1987 to December 30, 2022. The mean of daily returns is equal to 0.02% and the standard deviation of daily returns is equal to 1.37% (or equivalently 3.94% for the annual mean and 28.02% for the annual standard deviation as shown in Table 3 above).

Figure 4 below represents the Gaussian distribution of the DAX 30 index daily returns with parameters estimated over the period from v to December 30, 2022.

Figure 4. Gaussian distribution of the DAX 30 index returns.

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

Risk measures of the DAX 30 index returns

The R program that you can download above also allows you to compute risk measures about the returns of the DAX 30 index.

Table 5 below presents the following risk measures estimated for the DAX 30 index:

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 5. Risk measures for the DAX 30 index.

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 DAX 30 index while the study of the right tail is relevant for an investor holding a short position in the DAX 30 index.

Why should I be interested in this post?

For a number of reasons, management students (as future managers and individual investors) should learn about the DAX 30 index. The index includes wide range of industries, including energy, finance, telecommunications, and consumer goods, and it covers the biggest and most liquid German companies. Understanding how the index is constructed, how it performs, and the companies that make up the index is important for anyone studying finance or business in Russia or interested in investing in German equities.

Individual investors can assess the performance of their own investments in the German equity market with the DAX 30 index. Last but not least, a lot of asset management firms base their mutual funds and exchange-traded funds (ETFs) on the DAX 30 index which can considered as interesting assets to diversify a portfolio. Learning about these products and their portfolio and risk management applications can be valuable for management students.

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.

Business

CFI DAX Stock Index Explained

Wikipedia An introduction to the DAX 30 index

Avatrade Trade the DAX index

Data

Yahoo! Finance

Yahoo! Finance Historical data for the DAX 30 index

About the author

The article was written in May 2023 by Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management, 2021-2023).

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