A quick review of the Growth Capital…

A quick review of the Growth Capital…

Louis DETALLE

In this article, Louis DETALLE (ESSEC Business School, Grande Ecole Program – Master in Management, 2020-2023) explains what is Growth Capital and what it consists in.

What does Growth Capital consist in?

Growth capital refers to the funding that a company receives in order to expand its operations, enter new markets, or develop new products and services. This type of financing is typically sought by companies that are already generating revenue and have a proven track record of success but need additional funds in order to take their business to the next level.

What are the main actors a company can resort to when it comes to Growth Capital?

What is interesting with growth capital is that it is all about companies that are halfway between Venture Capital and Private Equity.

For that matter, there are several sources of growth capital, including venture capital firms and private equity firms that invest at different times in the life of the company. Venture capital firms typically invest in early-stage companies that have high growth potential, but may not yet be profitable. Private equity firms, on the other hand, typically invest in more established companies that are looking to expand through acquisitions (see the notion of “build-up”) or other means. A company will choose its investor according to its stage of development, its sector, its objectives and the network of the investors that it will be able to benefit from.

What does an analyst in Growth Equity work on?

The tasks of a Growth Equity analyst are diverse but similar to those of Private Equity & Venture Capital. They include for example, the producing and challenging a business plan, modelling different scenarios and strategies in Excel. The analyst and the investment teams thoroughly analyze the companies seeking for funding and the environments they are trying to grow into. If a company A well anchored in France is willing to conquer a new market European market, the job will consist in assessing the German market and see if the product developed by company A will work efficiently in the next country or if it is more accurate to try and find a similar company that can be bought there!

In other words, an analyst in Growth Equity will try to determine whether the projections of the seeked investment are reasonable, not overestimated and feasible.

What is the life cycle of a company and where does growth capital intervene?

At the beginning, when the startup is only an idea, the founders talk to Business Angels and VC funds that invest very early (called “seed investors”) and therefore small tickets. However, VC can come at the very beginning, as “seed investors”, of later in core venture with “A-B and C series”. These series mean the different funding rounds of the company that is growing.

Later on, companies can resort to growth capital, which aims at entering the capital of a company that has reached a certain maturity and profitability. The funds collected will then be used for internal and external growth: respectively the development of the company’s offers in order to develop its activities or the acquisition of competitors.

For that matter, Growth Capital will be the bridge between Venture Capital and Private Equity. Indeed, companies will finally reach Private Equity funds interest who will keep investing much more money than the previous actors…

After being bought, the most powerful and resilient companies will reach the IPO which can be considered as the ultimate goal. However, as you may have seen, the IPO arrives very late in the life cycle of a company

PRIVATE-EQUITY

Source: https://www.dlacalle.com/en/private-equity-and-cheap-money/

Related posts on the SimTrade blog

▶ Akshit GUPTA Growth Investment strategy

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

▶ Marie POFF Film analysis: The Wolf of Wall Street

Resources

Youtube Video explaining the different cycles of companies: VC/Growth/Private Equity

The top 10 VC actors in France

About the author

The article was written in December 2022 by Louis DETALLE (ESSEC Business School, Grande Ecole Program – Master in Management, 2020-2023).

A quick review of the Private Debt job…

Louis DETALLE

In this article, Louis DETALLE (ESSEC Business School, Grande Ecole Program – Master in Management, 2020-2023) explains what private debt is and what the working days look like when you work in this sector…

What does the private debt job consist in?

Private debt refers to the money borrowed by private companies from investors, rather than from banks or other financial institutions. Private debt jobs typically involve working for a private debt fund or a private equity firm, where the focus is on providing financing to companies that are seeking capital for expansion, acquisitions, or other business purposes.

What are the missions of the private debt analyst?

Private debt professionals are responsible for sourcing and underwriting investment opportunities, structuring and negotiating debt financing deals, and managing portfolio investments. This often involves conducting thorough due diligence on potential borrowers, evaluating their creditworthiness and financial health, and determining the appropriate terms and conditions for the debt financing.

Private debt professionals must have a strong understanding of the various types of debt financing available, including senior debt, mezzanine debt, and subordinated debt, as well as an in-depth knowledge of credit analysis, financial modeling, and risk management. They must also be adept at building and maintaining relationships with borrowers, investors, and other stakeholders in the private debt market.

Who are the main private debt lenders?

The private debt market is highly dynamic and constantly evolving. However, some of the largest private debt funds and private equity firms that focus on providing debt financing to companies include Apollo Global Management, Blackstone, KKR, Bain Capital, and TPG Capital, among others. These firms typically have significant financial resources and expertise in the private debt market and are well-positioned to provide large-scale financing to companies in need of capital. In France, Eurazeo and Tikehau Capital are very famous actors of this sector.

How to become a private debt analyst?

First, it is important to obtain a solid educational foundation in finance, accounting, and economics. This can be achieved through a bachelor’s or master’s degree program in a relevant field, such as finance, business, or economics. Coursework should focus on topics such as financial analysis, corporate finance, investment management, and risk management.

In addition to formal education, it is also important to gain practical experience in the private debt market. This can be achieved through internships or entry-level positions at private debt funds or private equity firms. These opportunities can provide valuable hands-on experience, as well as the chance to network with industry professionals and learn from more experienced colleagues.

Having gathered these two abilities, you should be able to make a strong application to private debt jobs and get started!

What is especially appealing in Private Debt jobs?

Private debt jobs can be highly rewarding, both financially and personally. In addition to competitive salaries, many private debt professionals also have the opportunity to earn substantial performance-based bonuses and other incentives. Furthermore, private debt young professionals often have the opportunity to work on a wide variety of deals and transactions, providing them with a diverse and challenging workload that can be both intellectually stimulating and professionally fulfilling.

Related posts on the SimTrade blog

   ▶ Rodolphe CHOLLAT-NAMY The rise in corporate debt…

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

Resources

Amundi Private Debt

Youtube A Webinar on Private Debt

About the author

The article was written in December 2022 by Louis DETALLE (ESSEC Business School, Grande Ecole Program – Master in Management, 2020-2023).

A quick review of the Sovereign Advisory job…

A quick review of the Sovereign Advisory job…

Louis DETALLE

In this article, Louis DETALLE (ESSEC Business School, Grande Ecole Program – Master in Management, 2020-2023) explains what a Sovereign Advisor works on, on a daily basis.

What does the Sovereign Advisory job consist in?

Sovereign advisory is a specialized field of finance that involves providing advice and guidance to governments and sovereign entities on a range of financial matters. This includes things like helping governments to develop and implement economic policies, advising on the issuance of sovereign bonds, and assisting with the management of public debt.

The job of a sovereign advisor is to help governments to make informed financial decisions that are in the best interests of the country and its citizens. This can involve providing expert analysis and guidance on a wide range of issues, including economic growth, public spending, and the management of public debt.

What are the missions of the accountant?

The missions of the Sovereign Advisor consist mainly of three tasks.

About a country’s economic policies

One of the key responsibilities of a sovereign advisor is to help governments to develop and implement economic policies that are effective and sustainable. This can involve providing guidance on the design and implementation of fiscal and monetary policies, as well as helping to identify potential risks and opportunities in the global economy.

About issuing sovereign bonds

Another important aspect of the job is to assist governments with the issuance of sovereign bonds. This can involve providing advice on the structure and terms of the bonds, as well as helping to market the bonds to investors and manage the sale process.

Helping a country master its commercial policy and global regulations

In addition to these core responsibilities, sovereign advisors may also be called upon to provide advice on a range of other financial matters. This can include things like helping governments to manage their public debt, providing guidance on the management of foreign exchange reserves, and assisting with the development of financial sector regulations.

Who are the main Sovereign Advisors?

The main actors of sovereign advisory are typically large financial institutions, such as investment banks and consulting firms. These firms typically have teams of experts with deep knowledge of global economic trends and the ability to provide expert guidance and advice to governments on a range of financial matters. In addition to these large financial institutions, there may also be smaller specialized firms that focus exclusively on providing sovereign advisory services. These firms may have a particular area of expertise, such as public debt management or economic policy development, and may be sought out by governments for their specific knowledge and expertise in these areas.

Examples of banks that provide sovereign advisory services include:
1. Goldman Sachs
2. JPMorgan Chase
3. Citigroup
4. Morgan Stanley
5. Deutsche Bank

How to become a Sovereign Advisor?

A career in sovereign advisory typically requires a strong background in economics, finance, or a related field. Many sovereign advisors hold advanced degrees, such as a Master’s in Business Administration (MBA) or a PhD in Economics. In addition to academic training, many sovereign advisors also have practical experience in the field, such as working in government or in other financial institutions.

In order to work in sovereign advisory, it is important to have a deep understanding of global economic trends and the ability to analyze and interpret complex financial data. This may require studying economics, finance, and related subjects at the undergraduate and graduate levels, as well as gaining practical experience through internships or other job opportunities. Additionally, many sovereign advisors also participate in professional development programs and continuing education courses in order to stay up to date with the latest developments in the field.

Resources

Rothschild & Co Sovereign Advisory

Youtube Interview of a Sovereign Advisor

Lazard Sovereign Advisory

Related posts on the SimTrade blog

   ▶ Rodolphe CHOLLAT-NAMY Government bonds

About the author

The article was written in December 2022 by Louis DETALLE (ESSEC Business School, Grande Ecole Program – Master in Management, 2020-2023).

A quick review of an Analyst in Transaction Services’ job…

A quick review of an Analyst in Transaction Services’ job…

Louis DETALLE

In this article, Louis DETALLE (ESSEC Business School, Grande Ecole Program – Master in Management, 2020-2023) explains what does an analyst in Transaction Services work on.

What does Transaction Services consist in?

The Transaction Services consultant assists clients and advises them on their financial transactions. He or she works on disposals, mergers and acquisitions, and restructuring. Clients of a Transaction Services department are generally investment funds, investment banks or very large companies that conduct financial transactions and require the expertise of a Transaction Services team.

What does a Transaction Services analyst work on?

There are two types of missions: buy-side and sell-side due diligence. The approach is different depending on whether you are on the buy side or the sell side. We will review what these missions consist in.

A due diligence is conducted by a specialized audit firm, its objective is to evaluate the risks inherent in the target company when the latter is being sold for instance. All the checks are made possible to understand the company’s strategy, to analyze its strengths and weaknesses, and also to have an overview of its accounting, financial, tax, social and environmental situation.

This analysis is therefore based on the analysis of the historical performance, cash flow and assumptions made in the business plans of the target company.

Calculations of metrics and normative ratios (e.g., EBITDA) or an in-depth analysis of the company’s working capital requirements, sector and business model are also carried out.

In short, the mission of Transaction Services is to carry out all the analyses to ensure that the client and the parties involved do not make any mistakes on the valuation of the company.

What are the biggest Transaction Services firms?

Deloitte, Ernst and Young (EY), PricewaterhouseCoopers (PwC) and KPMG are the four audit and consulting firms that make up the Big Four. They are the most influential consultancies in the world, employing nearly 1,200,000 people worldwide.

What are the main jobs possible after a Transaction Services position?

Some former Transaction Services staff move into areas such as investment banking, private equity (PE), controlling or mergers and acquisitions (M&A). Others use their time in Transaction Services to target departments where they can re-use the skills they have acquired.

To go into M&A or PE, Transaction Services will lack modelling, and this should be kept in mind. Thus, consultants are often found in managerial positions, M&A managers or even in the financial department. Eventually, the excellent command of numbers, operations and the ecosystem allow some to become partners.

Related posts on the SimTrade blog

   ▶ Louis DETALLE My experience as a Transaction Services intern at EY

   ▶ Basma ISSADIK My experience as an M&A/TS intern at Deloitte

Resources

Youtube How to nail TS interviews?

KPMG Careers website

EY Careers website

About the author

The article was written in December 2022 by Louis DETALLE (ESSEC Business School, Grande Ecole Program – Master in Management, 2020-2023).

My experience as an Audit intern at PwC

My experience as an Audit intern at PwC

Louis DETALLE

In this article, Louis DETALLE (ESSEC Business School, Grande Ecole Program – Master in Management, 2020-2023) interviews a former Audit intern at PwC.

First of all, let’s recall what Audit consists in?

The financial auditor expresses an opinion on the financial statements of a company. Their objective is to carry out the work necessary to enable the auditor to give an informed opinion on the true and fair nature of the published accounts.

The financial auditor is therefore the guarantor of the reliability of the company’s financial information and has a great responsibility, in particular to the company’s third-party stakeholders who invest in the company on the basis of the information published by the company.

Where had you applied for and what makes PwC different from other big 4?

It was my first internship in corporate finance, for that matter, I wanted to get into something but I did not really know what was possible. Since, an internship in Audit is a great way to launch one’s career; because you can do whatever you want after; I figured that it would be easier for me to apply there. I quickly got interviews at KPMG and PwC.

The reason why I chose PwC is because I was accepted there first! They offered me the position first and I was very keen to get over my internship hunting!

What does an intern in Audit work on?

An intern in audit at PwC will work on different tasks depending on the specific organization and the needs of the audit team. Some common tasks that an audit intern may be responsible for include:

• Assisting with the preparation of audit plans and procedures
• Conducting research and gathering information to support the audit process
• Analyzing financial statements and other data to identify potential risks and issues
• Participating in meetings with clients to discuss audit findings and recommendations
• Preparing reports and presentations to communicate audit results to clients and internal stakeholders
• Assisting with the development and implementation of internal controls and other risk management processes

Overall, the work of an audit intern typically involves providing support to the audit team in order to ensure that the audit is conducted in a thorough and professional manner. This may involve conducting research, analyzing data, and participating in meetings with clients and other stakeholders.

What do you plan to do next?

Most former Audit intern go for transaction services, investment banking, private equity or M&A internships.

As a consequence, I am not sure, but I think I will try to get into M&A and see if I like it.

Overall, would you recommend this experience to younger students? Why?

I would personally recommend this experience to anyone who is interested in corporate finance. Because it is one of the rare fields of corporate finance that you can have a with no experience before.

For that matter, it is an excellent internship, and anyone would be very lucky to do this internship because it would mean great opportunity to do things after. However, if you are lucky, you will be able to find a more interesting internship in banking perhaps or even in a financial department of a large corporate firm.

Resources

PwC Careers website

Youtube How to succeed in Audit interviews?

Related posts on the SimTrade blog

   ▶ Haiyuan XU My professional experience as financial research assistant in a green finance institute

   ▶ Tanmay DAGA My experience as a sell-side equity research analyst

About the author

The article was written in December 2022 by Louis DETALLE (ESSEC Business School, Grande Ecole Program – Master in Management, 2020-2023).

A quick review of the Accountant job in France…

A quick review of the Accountant job in France…

Louis DETALLE

In this article, Louis DETALLE (ESSEC Business School, Grande Ecole Program – Master in Management, 2020-2023) explains what an accountant (comptable en français) works on, on a daily basis, in France.

What does the Accountant job consist in?

All businesses and organizations need an accountant whose role is to record the day-to-day expenditure, income, and investments of the business.

The accountant is therefore the internal guarantor of the reliability of the company’s financial information and has a great responsibility, in particular to the company’s auditors & third-party stakeholders, who invest in the company on the basis of the information certified by the Audit firm and the Accountancy Department. The Audit firm will have to certify or to reject the authenticity of the accounts from an external point of view whereas the accountancy department will have this function internally.

What are the missions of the accountant?

The missions of the accountant depend on where he or she works.

In a small company

In a small company, the sole accountant is on all fronts. He or she monitors the company’s payrolls and various tax and social security declarations on a daily basis. On the other hand, the accountant must also anticipate the preparation of the closing of the annual accounts, which will be checked by the chartered accountant and certified by the auditor.

In a large company

In a large company, his or her tasks will in theory be the same, but given the size of the company, a transversality of subjects is not possible. Therefore they will work in a team and will be required to specialise rapidly: in charge of accounts receivable or payable, in charge of payroll. He will be working under the responsibility of the chief accountant.

In an accounting firm

In an accounting firm, the accountant will have various companies whose accounts he or she will have to monitor. He will be in charge of different company files, as an assistant, under the responsibility of the chartered accountant (expert comptable en français). Given the way the accounting firm operates, a great deal of advice and commercial work will be required to maintain and develop the client portfolio. It is a profession that includes busy periods, particularly during the closing of accounts, and is sometimes stressful, but which recruits a lot.

What are the academic diploma required to become an accountant?

In France, although it is possible to become an accountant after 2 years of higher studies, for big accountancy firms, it is often required to obtain specific diploma in accountancy.

The DCG (diploma in accounting and management in French – Diplôme de Comptabilité et de Gestion) is a 3-year training after A level at the end of which the accountant to be will have to take an exam in order to check that the knowledge has been well learnt.

The DSCG (Superior Diploma in accounting and management in French – Diplôme Supérieur de Comptabilité et de Gestion) is a 2-year program that one can take after obtaining the DCG. This will give the accountant a Master’s level, often needed for certain jobs.

The DEC (diploma of certified accountant in French – Diplôme d’Expertise Comptable) …allows you to work as a chartered accountant in an accounting firm. To register for the DEC exams, you must have completed a three-year internship in a public accounting firm and have a baccalaureate +5 years of higher education. The DEC is prepared in 3 years after a Master’s degree, which is often the DSCG mentioned above.

How AI can impact the Accountancy’s job?

Artificial intelligence (AI) can potentially impact the field of accounting especially as regards the automation of tasks. Indeed, AI can be used to automate certain tasks that are currently performed by accountants, such as data entry, reconciliation, and financial reporting. This can potentially save time and reduce the risk of human error. In addition, AI can analyze large amounts of data and identify patterns and trends that might not be immediately apparent to a human accountant. This can help accountants make more informed decisions and provide valuable insights to their clients. AI can also be used to identify unusual patterns or transactions that may indicate fraudulent activity. This can help accountants detect and prevent fraud before it occurs.

Overall, AI has the potential to significantly improve efficiency and effectiveness in the field of accounting, but it’s important to underline that although AI can assist accountants in their work, the final word belongs to humans when it comes to making informed decisions based on their expertise and the help of AI.

Related posts on the SimTrade blog

▶ Pierre-Alain THIAM My experience as a junior audit consultant at KPMG

▶ Louis DETALLE Wirecard: At the heart of the biggest German financial scandal of the 21st century

Resources

KPMG Careers website

EY Careers website

About the author

The article was written in December 2022 by Louis DETALLE (ESSEC Business School, Grande Ecole Program – Master in Management, 2020-2023).

Interest Rate Swaps

Akshit Gupta

This article written by Akshit GUPTA (ESSEC Business School, Grande Ecole Program – Master in Management, 2019-2022) presents the derivative contract of interest rate swaps used to hedge interest rate risk in financial markets.

Introduction

In financial markets, interest rate swaps are derivative contracts used by two counterparties to exchange a stream of future interest payments with another for a pre-defined number of years. The interest payments are based on a pre-determined notional principal amount and usually include the exchange of a fixed interest rate for a floating interest rate (or sometimes the exchange of a floating interest rate for another floating interest rate).

While hedging does not necessarily eliminate the entire risk for any investment, it does limit or offset any potential losses that the investor can incur.

Forward rate agreements (FRA)

To understand interest rate swaps, we first need to understand forward rate agreements in financial markets.

In an FRA, two counterparties agree to an exchange of cashflows in the future based on two different interest rates, one of which is a fixed rate and the other is a floating rate. The interest rate payments are based on a pre-determined notional amount and maturity period. This derivative contract has a single settlement date. LIBOR (London Interbank Offered Rate) is frequently used as the floating rate index to determine the floating interest rate in the swap.

The payoff of the contract is as shown in the formula below:

(LIBOR – Fixed Interest Rate) * Notional amount * Number of days / 100

Interest rate swaps (IRS)

An interest rate swap is a hedging mechanism wherein a pre-defined series of forward rate agreements to buy or sell the floating interest rate at the same fixed interest rate.

In an interest rate swap, the position taken by the receiver of the fixed interest rate is called “long receiver swaps” and the position taken by the payer of the fixed interest rate is called “long payer swaps”.

How does an interest rate swap work?

Interest rate swaps can be used in different market situations based on a counterparty’s prediction about future interest rates.

For example, when a firm paying a fixed rate of interest on an existing loan believes that the interest rate will decrease in the future, it may enter an interest rate swap agreement in which it pays a floating rate and receives a fixed rate to benefit from its expectation about the path of future interest rates. Conversely, if the firm paying a floating interest rate on an existing loan believes that the interest rate will increase in the future, it may enter an interest rate swap in which it pays a fixed rate and receives a floating rate to benefit from its expectation about the path of future interest rates.

Example

Let’s consider a 4-year swap between two counterparties A and B on January 1, 2021. In this swap, counterparty A agrees to pay a fixed interest rate of 3.60% per annum to counterparty B every six months on an agreed notional amount of €10 million. Counterparty B agrees to pay a floating interest rate based on the 6-month LIBOR rate, currently at 2.60%, to Counterparty A on the same notional amount. Here, the position taken by Counterparty A is called long payer swap and the position taken by Counterparty B is called the long receiver swap. The projected cashflow receipt to Counterparty A based on the assumed LIBOR rates is shown in the below table:

Table 1. Cash flows for an interest rate swap.
 Cash flows for an interest rate swap
Source: computation by the author

In the above example, a total of eight payments (two per year) are made on the interest rate swap. The fixed rate payment is fixed at €180,000 per observation date whereas the floating payment rate depend on the prevailing LIBOR rate at the observation date. The net receipt for the Counterparty A is equal to €77,500 at the end of 5 years. Note that in an interest rate swap the notional amount of €10 million is not exchanged between the counterparties since it has no financial value to either of the counterparties and that is why it is called the “notional amount”.

Note that when the two counterparties enter the swap, the fixed rate is set such that the swap value is equal to zero.

Excel file for interest rate swaps

You can download below the Excel file for the computation of the cash flows for an interest rate swap.

Download the Excel file to compute the protective put value

Related Posts

   ▶ Jayati WALIA Derivative Markets

   ▶ Akshit GUPTA Forward Contracts

   ▶ Akshit GUPTA Options

Useful resources

Hull J.C. (2015) Options, Futures, and Other Derivatives, Ninth Edition, Chapter 7 – Swaps, 180-211.

www.longin.fr Pricer of interest swaps

About the author

Article written in December 2022 by Akshit GUPTA (ESSEC Business School, Grande Ecole Program – Master in Management, 2019-2022).

My apprenticeship experience within client services at BNP Paribas

Akshit Gupta

In this article Akshit GUPTA (ESSEC Business School, Grande Ecole Program – Master in Management, 2019-2022) shares his apprenticeship experience as a client services analyst at BNP Paribas, which is the leading European banking group.

Introduction

BNP Paribas is a French banking group which was formed as a result of a merger between Banque Nationale de Paris (BNP) and Paribas in the year 2000. The group’s business is divided in 3 major operating divisions including: Commercial, Personal Banking & Services (CPBS), Investment & Protection Services (IPS) and Corporate Institutional Banking (CIB) and the bank has its presence in 65 countries.

 BNP Paribas Logo

BNP Paribas is ranked as the largest banking group in Europe and amongst top 10 in the world in terms of total assets which reflects the size of financial institution. BNP Paribas is a publicly listed company on Euronext Paris and is a part of the CAC 40 and Euro Stoxx 50 index.

Table 1. Ranking of banks by total assets

 BNP Paribas Ranking

Source: www.advratings.com

My Apprenticeship Experience

I worked as a Client Services Analyst within the Corporate and Institutional Banking (CIB) division of the bank.

Missions

I had the opportunity to undertake two missions during the apprenticeship at BNP Paribas. During my first year, I worked as a Client Services Officer in the Factsheets team wherein I was responsible for creating and producing factsheets on equity and fixed income linked structured products and custom indices for the institutional clients of the bank. The Client Services is a cross functional team within the BNP Paribas Global Markets. They aim to provide the clients with the best possible post-trade service on the global market activity of the bank. The team works in close coordination with various teams operating on the capital markets (Sales, Traders, Business Managers, Middle and Back Office, Compliance, and Lawyers) and on all types of products (equities, fixed income, commodities, foreign exchange, and derivatives).

My work involved analysing the technical term-sheets (documents which present technical information about the products) of different structured products and produce factsheets (documents which mainly present the financial performance of the products) related to these products in conjunction with the Structuring and Sales teams at the bank. The factsheets were automated and produced on different frequencies like daily, weekly, bi-weekly, and monthly to serve the needs of different clients. These reports included products’ performance measures, and commentary on market data and current economic scenarios on these products.

During the second year of my apprenticeship, I worked as an Operational Client Relationship Manager (OCRM) within the same division at BNP Paribas but with a change of business responsibilities and duties to gain more exposure on the client facing side of the business.

In this role, I was responsible for developing and maintaining strong commercial relationships with the top institutional clients of our bank and manage client’s transversal escalations for multi asset classes including Equities, Fixed Income, Foreign Exchange, and Credit Derivatives. I worked on pre and post trade issues in close coordination with cross functional teams like Sales, Trading, Onboarding, Legal, Compliance and Operations to resolve breaks and efficiently serve the clients.

Required skills and knowledge

  • Strong knowledge of investment banking, equity, and capital markets.
  • Strong skillset in MS Office pack including MS Excel, MS Word, MS Access, and MS PowerPoint to produce reports and KPI dashboards for internal and external purposes.
  • Familiarity with programming in VBA and SQL.
  • Understanding of front-to-back trade lifecycle of different products.
  • Effective communication skills to interact with clients and internal stakeholders
  • Strong interpersonal skills.

What I learnt?

With this apprenticeship experience, I gained strong exposure to the different structured products issued by a bank like BNP Paribas in the global markets, understanding of client communication side, and programming skills in VBA and SQL. Along with the technical skillsets, I also learnt the importance of working as a team, understanding each other’s viewpoints, and aiming towards a common goal. It brought into focus the importance of banking sector and has given me a platform to sharpen my financial acumen.

Key concepts

The following are the two concepts that were required in my work at BNP Paribas:

Global markets

Global Markets is a division within an investment bank which handles all the sales and trading services on both the primary and secondary markets for different financial products. It caters to different clients including financial institutions, corporates and large-scale investors. The teams within this division are generally split based on different asset classes. Relevant knowledge of the different functions within this division is important to facilitate and coordinate client escalations and projects.

Structured products

Structured products are pre-packaged product offerings which are designed as per the client’s risk-return profile. The returns on the investments in these products are based on the performance of the underlying assets. These underlying assets can include individual assets or indices in various markets like equities, bonds and commodities, and derivatives on these underlying assets like futures, swaps, and options.
The structured products are highly sophisticated products since they are tailor-made as per the client’s requirements and risk/return profile. These products have pre-defined features like maturity date, early – redemption mechanism, coupon payments (fixed or variable coupons), underlying asset, and the degree of capital protection. They can guarantee full or partial capital protection and a flexible degree of leverage as well.

Why should I be interested in this post

This post is interesting for anyone looking to enter the Global Markets side of an investment bank and looking to kickstart a career in this field by looking for an apprenticeship or an internship contract.

Useful resources

BNP Paribas

BNP Paribas financial reports

BNP Paribas financial report for year 2021

Related posts on the SimTrade blog

   ▶ All posts about Professional experiences

   ▶ Alexandre VERLET Classic brain teasers from real-life interviews

   ▶ Akshit GUPTA Equity structured products

About the author

Article written in December 2022 by Akshit GUPTA (ESSEC Business School, Grande Ecole Program – Master in Management, 2019-2022).

A quick review of the Audit job…

A quick review of the Audit job…

Louis DETALLE

In this article, Louis DETALLE (ESSEC Business School, Grande Ecole Program – Master in Management, 2020-2023) explains what an Audit analyst works on, on a daily basis.

What does the Audit job consist in?

The financial auditor expresses an opinion on the financial statements of a company. Its objective is to carry out the work necessary to give an informed opinion on the true and fair nature of the published accounts.

The financial auditor is therefore the guarantor of the reliability of the company’s financial information and has a great responsibility, in particular to the company’s third party stakeholders who invest in the company on the basis of the information published by the company.

What are the biggest audit firms?

Deloitte, Ernst and Young (EY), PricewaterhouseCoopers (PwC) and KPMG are the four audit and consulting firms that make up the Big Four. They represent the most influential consulting firms in the world. They are the most influential consultancies in the world, employing nearly 1,200,000 people worldwide.

However, some other players are very influential, such as Mazars in France, which is ranked neck and neck with the Anglo-Saxon Big Four. On the other hand, smaller companies do not necessarily need to call on such large firms as their audits are not as labour intensive.

What does an Auditor work on?

In the case of an accounting and financial audit, it is an examination of the company’s financial statements in order to assess the company’s accounts and verify their fairness, compliance and regularity. As the auditor is expected to give an opinion on the fairness of the accounts, the auditor and his team will study the different accounting cycles of the company: income and customers, costs and suppliers, but also equity, cash flow, stocks and fixed assets, etc.

The objective of this review of the major financial masses is to understand the client’s challenges related to its business, its environment, its organisation, and to understand its internal processes in order to see how all this is reflected in the accounts. A meticulous verification of the accounts and invoice amounts is carried out (often subcontracted).

The common objective of all engagements is to provide confidence to both external investors and the client, who may need to make adjustments after the annual audit. The client may have to make adjustments after the annual audit because their internal control systems are more or less effective, and they may present inaccurate accounts unintentionally but more inadvertently.

Other audits may therefore cover the environment, the production system, ethics, safety and many others. The role of a quality audit, for example, is to check whether the client company’s stated quality objectives are being met. The auditors must ensure that the quality management systems comply with the applicable contractual and regulatory requirements.

The use of AI in order to quicken the audit job.

Artificial intelligence (AI) can potentially impact the audit profession in a number of ways. Here are a few examples:

Auditing large amounts of data: AI technologies, such as machine learning algorithms, can help auditors analyze and interpret large amounts of data more efficiently and accurately. For example, an AI system could be used to identify patterns and anomalies in financial data that might indicate fraudulent activity or other problems.

Improving efficiency: AI can automate certain tasks, such as data entry and analysis, allowing auditors to focus on higher-value activities, such as interpreting results and communicating findings. This can help improve the efficiency and effectiveness of the audit process.

Enhancing risk assessment: AI can help auditors better understand and assess the risks associated with a particular business or industry. For example, an AI system could analyze data on economic conditions, market trends, and other factors to help identify potential risks and provide recommendations for how to mitigate them.

Providing real-time monitoring: AI can be used to monitor a company’s financial data in real-time, alerting auditors to any unusual activity or trends that may warrant further investigation. This can help auditors identify potential issues earlier in the process, which can lead to more timely and effective interventions.

Overall, the use of AI in the audit profession has the potential to improve the accuracy and efficiency of the audit process, while also helping auditors to identify and address risks more effectively.

Related posts on the SimTrade blog

   ▶ Pierre-Alain THIAM My experience as a junior audit consultant at KPMG

   ▶ Louis DETALLE Wirecard: At the heart of the biggest German financial scandal of the 21st century

Resources

Youtube The Audit Methodology

KPMG Careers website

EY Careers website

About the author

The article was written in December 2022 by Louis DETALLE (ESSEC Business School, Grande Ecole Program – Master in Management, 2020-2023).

A quick review of the Venture Capitalist’s job…

A quick review of the Venture Capitalist’s job…

Louis DETALLE

In this article, Louis DETALLE (ESSEC Business School, Grande Ecole Program – Master in Management, 2020-2023) explains what a Venture Capitalist works on, on a daily basis.

What does Venture Capital consist in?

Venture Capital (VC) represents fundamental and indispensable early funding-support throughout the life cycle of the company.

VC consists in taking (minority or majority) stakes in the capital of small companies which are generally unlisted on the stock exchange and that have not reached break-even point. It is therefore a method of financing companies in order to support them on the path to growth. Indeed, the objective of a VC fund is obviously to realize a capital gain at the exit, when the start-up has matured and has become a powerful actor.

This is risky because start-ups are less successful in borrowing from banking institutions, so they attract other investors such as business angels and venture capitalists.

What are the main differences among Venture Capitalists?

VC funds can be specialized in sectors such as deep tech, biology, marketplace, telecom and plenty of others. A start-up will therefore have better chances at obtaining funding from them if they target funds that know well the field in which they evolve.

In addition, another aspect of VC is the stage of investment and the size of tickets.

Because VC can come at the very beginning, as “seed investors”, of later in core venture with “A-B and C series”.

Later on, companies can resort to growth capital, which aims at entering the capital of a company that has reached a certain maturity and profitability. The funds collected will then be used for internal and external growth: respectively the development of the company’s offers in order to develop its activities or the acquisition of competitors.

For that matter, Growth Capital will be the bridge between Venture Capital and Private Equity.

What are the main VC actors a company can resort to?

Start-ups and small companies can resort to a wide range of financial investors:

  •  Early-stage investment funds (BPI, Axeleo Capital, Alven Capital, etc.
  • Corporate funds represented by large groups that are interested in the creation of innovative companies.
  • Business angels, represented mainly by entrepreneurs, who organize themselves into associations or investment companies.
  • Crowdfunders, who are individuals who invest in start-ups such as Xavier Niel for instance.

A company must choose its investors according to its stage of development, its sector and according to its objectives.

What does an analyst in VC work on?

The tasks of a Venture Capitalist are diverse and include, for example, the producing and challenging a business plan, modelling different scenarios and strategies in Excel. The analyst and the investment teams of the VC teams thoroughly analyze the companies seeking for funding. They try to determine whether the projections of the seeked investment are reasonable and not overestimated.

Indeed, bear in mind that private equity funds intend to fund companies trough equity. And as equity investors (i.e. shareholders) are reimbursed at last in the event of a bankruptcy, their work is to determine if the company will really generate growth with the capital at stake. That’s why deep sector-analysis are also required from a VC analyst.

This is all the truer for Venture Capitalist who will take on huge risks since they are the first financial actors the start-up can turn to.

Why do VC jobs appeal so much to business school students?

First of all, it should be noted that this profession combines corporate finance skills with entrepreneurial thinking, which is rare!

Indeed, the best Venture Capitalist often has previous entrepreneurial background, and this is what enables him to see things that startups cannot: because this person has already made the mistakes the fund-seeking entrepreneur has not.

This entrepreneurial aspect of the job is very well known and argued by VC actors and it attracts young & ambitious students who don’t want to get into large corporate firms and favor more agile structures.

Related posts on the SimTrade blog

▶ Jessica BAOUNON Why Berlin could be the new Silicon Valley for startups?

Resources

The top 10 VC actors in France

Youtube How to get a VC internship?

About the author

The article was written in December 2022 by Louis DETALLE (ESSEC Business School, Grande Ecole Program – Master in Management, 2020-2023).

My experience as a Transaction Services intern at EY

My experience as a Transaction Services intern at EY

Louis DETALLE

In this article, Louis DETALLE (ESSEC Business School, Grande Ecole Program – Master in Management, 2020-2023) interviews a former Transaction Services intern at EY.

First of all, let’s recall what Transaction Services consists in?

The Transaction Services (TS) consultant assists clients and advises them on their financial transactions like disposals, mergers and acquisitions and restructuring. Its clients are generally investment funds, investment banks or very large companies that conduct transactions and require the expertise of Transaction Services teams.

In short, the mission of Transaction Services is to carry out all the analyses to ensure that the client and the parties involved do not make any mistakes on the valuation of the company.

Where had you applied for and what makes EY different from other big 4?

It was my second significant internship in corporate finance, for that matter, I wanted to get into M&A or Private Equity, but both are pretty complicated to get into. For that matter, I figured that it would be easier for me to apply for a Transaction Services internship or in M&A corporate. I quickly got interviews at EY, Deloitte and KPMG.

I chose EY because I really got along with my manager-to-be; he insisted that they would make me work on interesting stuff and they offered be the position first.

What does an intern in TS work on?

As you may know, in TS, there are two types of missions: buy-side and sell-side due diligence. The approach is different depending on whether you are on the buy side or the sell side.

As an intern, my job was to help my team assess the risks inherent in the target company while preparing the due diligence. For that matter, all of the checks are made possible to understand the company’s strategy, to analyse its strengths and weaknesses, and also to have an overview of its accounting, financial, tax, social and environmental situation. I could help them on any of the topics above, although the tax aspect of the company was given to a dedicated department.

In the due diligence, I can assist my team in the reading of documents from the major international institutions for all the data relating to global and entire sectors for the specific sections of the due diligence.

Also, a last type of task that I was given was taking notes about Q&A sessions that occur during the M&A process. I would thereafter write a summary for the team.

What do you plan to do next?

Most former Transaction Services intern go for investment banking, private equity, controlling or M&A internships.

As a consequence, I believe that this is what I will do next, I can wait to be on the banking side of the merger! The advantage of my internship is in fact twofold. On the one hand, it allows me to have EY on my CV and on the other hand, I have experience that finance recruiters describe as “significant finance work experience”. So I can do many things afterwards and that is the strength of my internship.

Overall, would you recommend this experience to younger students? Why?

I would personally recommend this experience to anyone who is interested in corporate finance. Because it is one of the rare fields where you gain a lot of knowledge about financial modelling. When you work in TS, you spend most of your time on Excel and this will be a valuable skill for your following internships.

For that matter, it is an excellent internship, and anyone would be very lucky to do this internship because it would mean great exposure and lots of financial analysis.

Related posts on the SimTrade blog

▶ Haiyuan XU My professional experience as financial research assistant in a green finance institute

▶ Tanmay DAGA My experience as a sell-side equity research analyst

Resources

EY Careers website

Youtube How to nail TS interviews?

About the author

The article was written in December 2022 by Louis DETALLE (ESSEC Business School, Grande Ecole Program – Master in Management, 2020-2023).

My experience as an Equity Research Intern at Oddo BHF…

My experience as an Equity Research Intern at Oddo BHF…

Louis DETALLE

In this article, Louis DETALLE (ESSEC Business School, Grande Ecole Program – Master in Management, 2020-2023) interviews a former Equity Research Intern at Oddo BHF.

First of all, let’s recall what Equity Research consists in?

The objective of equity research is to make buy or sell recommendations on stocks to advise investors on their asset allocation. In doing so, the Equity Research team will closely monitor certain stocks to see if the stock is outperforming or underperforming. In doing so, they will closely monitor the share price and sell their monitoring as a service to determine whether to buy or sell a share.

This equity research service is therefore sold to investors in the financial markets to provide them with a comprehensive financial analysis, as well as advice on whether to buy or sell particular securities. The analysis report presented by an equity analyst is used by investment banks and private equity firms to evaluate the company for an initial public offering (IPO), a leveraged buy-out (LBO), alliances and others. Therefore, all these investors constitute clients of Equity Research teams.

What banks did you apply for and what makes Oddo BHF different from others?

Most banks have Equity Research teams such as Société Générale, UBS, BNP Paribas, Barclays, Goldman Sachs and Citi for instance. In short, equity research analysts are mainly employed by investment banks but also investment funds (KKR, Blackstone, Bpifrance, etc.) or asset management firms (BlackRock, Vanguard, Amundi, etc.).

For that matter, I had applied virtually everywhere but I only got interviews from UBS, BNP Paribas & Oddo BHF. I was refused at UBS but got the offer at BNP Paribas. However, since I had gotten along very well with the team at Oddo BHF, I chose to go there instead!

Is your equity research team specialised in a specific sector? Which one?

Whereas most equity research teams are specialised in a specific sector such as automotive, aerospace, healthcare, telecoms and biotech, mine isn’t. Some of the team members follow very closely the stock prices and market indicators of certain companies but it is more about personal interest!

That makes the experience super interesting, because I am able to see for myself how the stocks of companies in the luxury sector are impacted by the announcement of the quarter results and how they evolve, relatively to companies from other sectors.

What does an intern in Equity Research work on?

As explained above, an equity research analyst will follow the release of sector or company specific information to write a note for subsequent use by the clients as part of their investment strategy.

As an intern, I have assisted the work of the equity research analyst by doing information research, reading quarterly financial reports, and press releases which may provide information on the company’s performance to date compared to expectations. As the analyst will also look for information on upcoming mergers, I have to keep an eye on financial news as this will impact significantly the prices of stocks.

As for the sectoral notes, I can assist my team in the reading of documents from the major international institutions for all the data relating to global and entire sectors.
Once this research work is completed, equity research analysts proceed to forecast results through financial modelling. I can look at the financial modelling but I must say I am not allowed to work on it since the slightest mistake could cause significant errors.

Also, a last type of task that I was given was taking notes about clients’ questions by telephone during morning meetings. I would thereafter write a summary for the team.

Overall, would you recommend this experience to younger students? Why?

I would personally recommend this experience to anyone who is interested in finance, be it corporate finance or market finance. Because it is one of the rare fields where you enjoy the benefits of each: you analyze financial market products while comparing them to the financial results announced by companies.

For that matter, it is an excellent first internship in this field and anyone would be very lucky to do this internship because it would mean great exposure and lots of financial analysis.

Related posts on the SimTrade blog

▶ Louis DETALLE A quick review of the ECM (Equity Capital Market) analyst’s job…

▶ Haiyuan XU My professional experience as financial research assistant in a green finance institute

▶ Tanmay DAGA My experience as a sell-side equity research analyst

Resources

Finance walk Equity Research Interview Questions with answers

Youtube An analyst in Equity Research’s Youtube Interview

Youtube How to do the Equity Research of a company?

About the author

The article was written in December 2022 by Louis DETALLE (ESSEC Business School, Grande Ecole Program – Master in Management, 2020-2023).

Netflix’s announcement impacts Disney’s stock price

Netflix’s announcement impacts Disney’s stock price

Ines ILLES MEJIAS

In this article, Ines ILLES MEJIAS (ESSEC Business School, Global BBA, 2020-2024) analyzes how Netflix announcement regarding its decrease in earnings and subscribers also affected Disney’s stock price.

Description of firm

Netflix (1997) and Disney + are both world leading entertainment streaming services. They both offer a wide variety of content ranging from TV shows, Movies, Documentaries and even original series and movies. Both streaming services are available as an app for mobile phones, tablets, etc, as well as streaming to watch online on our computers. This allows users to enjoy from their services anytime and anywhere, and, through the app even download content to watch offline. They both work as subscriptions with different plans which customers can choose to subscribe to depending on their income and needs. However, Netflix, having been launched before, was the market leader in the streaming entertainment industry for a very long time.

Description of event

Netflix reports its first customer decline of 26% in over 10 years, and Disney stocks fell 5.3% also consequently. Netflix reported a loss of 200,000 members in the first quarter and forecasted a loss of 2 million subscribers in the current quarter (April 2022). Investors and analysts are rethinking on new ways of boosting their forecasts for the entire industry, and fear that a reopening economy will cripple entertainment companies.

Figure 1. Impact of Netflix announcement.
Impact of Netflix announcement
Source: Bloomberg.

This article talks about the current decline in Netflix subscribers and how it has affected not only their stocks, but also created a fear among analysts and investors in the entertainment streaming industry, as well as impacted other companies’ stocks such as Disney, Warner Bros, etc.

Reaction of market to event

Disney shares fell by 6% after the news. Disney is a competitor, which means that normally it could have benefitted from a cut in Netflix (its competitor) stocks. But this did not seem to happen. Instead, investors feared that Disney might also suffer from a slower growth in earnings like Netflix, which resultantly affected Disney’s stocks negatively. By the end of April, Disney stocks fell by 19%, and, according to S&P Global Market Intelligence, down roughly 40% from its peak last fall.

It is said that one of the main reasons for Netflix big decline in returns and subscribers was content, especially since other entertainment such as HBO are gaining the exclusivity over shows such as Game of Thrones or Sex in the City. Therefore, Netflix plays on offering new Netflix Original content to more attract customers. However, Disney should do good after this as it has a deep content library of franchises that it can leverage to produce hit shows, so in the long-term its growth and revenues should not seem to be very affected by Netflix.

Figure 2. Impact of Netflix announcement on Walt Disney stock price.
Impact of Netflix announcement on Walt Disney stock price
Source: Bloomberg.

Link with market efficiency

The efficient market hypothesis states that the market cannot be beaten because it incorporates all information into current share prices, so stocks trade at the fairest value. There are three types of market efficiency that we must know of. First, weak efficiency, where all information contained in past stock market data (prices and transaction volumes) is already reflected in today’s price. Then, we have semi-strong efficiency which in addition to the information contained in historical stock market data, all public information (company accounts, analyst reports, etc.) is already reflected in today’s price. Finally, strong efficiency where all information, public as well as private, is already reflected in today’s price.

I believe this is an example of a semi-strong efficiency as company accounts and reports as well as historical data are included in the price. Disney’s price was subject and result of Netflix public accounts.

Justification of your choice of the event and the firm

I, myself, am a subscriber for both of these entertainment streaming services, so when I heard the news, I was actually surprised about the power and influence that these have on one another. Especially since I believe that both have completely different content which interest me. From a very young age, I’ve been a fan of Disney and their content, which is what made me subscribe to Disney +, while I became a subscriber for Netflix because it was “a trend” back in time and everyone was speaking about all the content available. After reading this news, I also agreed that Netflix has decreased in terms of content and quality, which is why I use more Disney plus, another reason why I was surprised by the news.

Why should you be interested in this post?

Netflix and Disney are two of the most know streaming companies in the world. It’s important to be aware of the impacts that companies from the same industry have on one another, especially to be able to avoid, fight or tackle if news like these were to happen again.

Useful resources

Netflix

Disney+

Why Disney Stock fell 19& in April

Stocks fall after shocking drop in Netflix subscribers

About the author

The article was written in December 2022 by Ines ILLES MEJIAS (ESSEC Business School, Global BBA, 2020-2024).

My professional experience as a marketing assistant at Auris Gestion

My professional experience as a marketing assistant at Auris Gestion

Ines ILLES MEJIAS

In this article, Ines ILLES MEJIAS (ESSEC Business School, Global BBA, 2020-2024) shares her experience as a marketing assistant at Auris Gestion (France).

About the company

Auris gestion is an asset management company created in 2004 which currently manages 3 billion euros. At the beginning, Auris Gestion focused on assisting only private clients with a worldwide offer by providing tailor-made solutions to their investment needs and demands. However, it decided to merge along with Salamandre AM in June 2020 to improve its positioning with financial advisor and Family Office partners. As a result, Auris Gestion makes its expertise and institutional management approaches available to a larger clientele, including individual consumers, asset management advisers, and institutions.

Logo of Auris Gestion.
 Logo of Auris Gestion
Source: Auris Gestion.

One of Auris Gestion main strengths is their close relationship with their clients and the fact that it places a high importance on developing this one by providing excellent tailored management, advising, and reporting solutions. To accomplish this successfully, they have decided to dive their team into two independent business divisions: the Private Banking and the Corporate Banking.

My internship

My internship lasted a total of three months and took place in Paris.

What I enjoyed the most about my internship is that I could work in different areas of business and not only finance, which I was quite scared of considering that jobs in finance are known to be very intense and I didn’t consider myself having a wide financial knowledge after my first year at ESSEC. However, I really enjoyed being able to do some marketing. This helped me to get to know inside out. Additionally, it really helped me to improve my finance vocabulary and knowledge in French.

My missions

I was in charge of creating customer master records and separating them into the two different clients and divisions which Auris works for: Private Banking/management and Institutional/Corporate finance.

In addition, I also worked as an assistant in the Marketing department. In this one, some of my tasks included:

  • Editing and writing up content for the new Auris and Salamander websites that they were working on to update their information and highlight their partnership with Salamander. Also, their aim was to create a more visually attractive website for customers to understand better the information and improve Auris’ positioning in terms of modern in technology and marketing.
  • Also, I was in charge of adjusting the website’s vocabulary according the two client divisions: Private Banking (simpler financial language) and Institutional/Corporate finance (advanced financial language and more precise information regarding the services offered).
  • Finally, within the marketing department, I had to create information documents and “poster style” documents about ESG. These documents had as a purpose informing and inciting clients to invest in this growing and important, although dangerous sector (greenwashing) funds. Also, to highlight Auris’ implications and contribution in green finance.

Using excel was one of my competences, which is why they also charged me to create and complete fund factsheets and reports. For successful completion, I had to search in Websites such as Morning Star, or the main company/fund websites, information about the funds which then I needed to update or fill in the Due Diligence factsheet template.

Another of my many jobs, which I found interesting and in which I got to learn loads was by attending and representing Auris during fund presentation and pitches. Here, I got to meet different company representatives and got to see how people pitched a fund. One of my other roles after these meetings, was not only making notes about what I learnt, but also summarizing pros and cons from the funds pitched and presented.

Required skills and knowledge

During my internship some of the skills which I most made use of and I believe were required to do my job were teamwork, adaptability, creativity, critical thinking, communication skills and Analytical skills, considering I worked for the financial department which is very quantitative, and the marketing department which is a bit more qualitative and visual.

Also, autonomy was very important, especially since the manager asked me what would be something that I’ve seen in the company that I’m interested in working on, and then I would go ahead and work on that and do research on my own.

Then, I would say one of the most important required skills is being an advanced user of the Pack Office. This is because I was required to use daily either Microsoft teams, Word, PowerPoint, and Excel.

To continue, some finance and asset management knowledge and vocabulary are obviously essential. However, if you are pursuing a business degree you should have a good base of knowledge already. The same goes for marketing and strategic marketing knowledge.

Finally, knowledge and skills on how to use of marketing tools for the creation of digital content such as Canvas and Adobe Photoshop/Photopea were needed.

What I learned

During my internship I was lucky to learn and expand my knowledge in few areas.
First, I learned how to elaborate and fill Due Diligence factsheets to evaluate different funds from different companies. For this, I had to become familiar with the company websites, Morning Star, understand fund rating, etc.

Then, I got to further improve my knowledge on finance thanks to personal research that I did as well as to some of the employees which were eager in teaching me new financial terms and concepts. Some examples of new things I learnt are structured products, ESG, greenwashing, different bond ratings, etc. One of the workers was very kind and once every few days he would sit with me and explain me concepts which I came across that I didn’t understand or was struggling with.

Moreover, the weekly “Rendez-vous de Lundi”, which is a concept set up by the company which consisted of weekly newsletters sent to workers and published publicly, helped me stay informed about the main the weekly performance of markets through the overview of the markets with charts showing their risk, inflation, and summaries regarding their importance and other news, etc.

Finally, the “Point macro”, which was done every two weeks by the company with the aim of keeping up to date all the workers with the main macroeconomic factors affecting today’s investing world. This really got me to improve my macroeconomics knowledge as well as got me to learn a lot about the diversity and importance of this one in the asset management and investing world.

Key financial concepts related to your work

During my internship, I came across the following key financial concepts: structured products, ESG funds, and bond rating.

Structured Products

Structured products are investments that normally include assets linked to interest plus one or more derivatives. These are sometimes attached to an index or group of assets and create extremely specific risk-return objectives. The package is known to be composed of: a bond, some underlying assets, and the derivatives strategy.

ESG Funds

ESG Funds are bands which carry Environmental, Societal and Governance principles investments. This means that the bonds have gone through a test which determines how sustainable the company or government is in terms of the ESG criteria. This index has pushed a lot of companies to become more responsible. Also, they’re important today due to the importance sustainability, and they’re becoming more popular as investors want to be seen as contributors of stopping global warming and contributing to human development without impacting their returns.

Bond Ratings

Bond ratings are letters which define and judge the quality and creditworthiness of a bond. Normally starts with triple letter A (“AAA” for Standard & Poor’s, and “Aaa” for Moody’s), and starting from BB bonds are known as “Junk bonds” due to their low ratings. What we must remember is that the higher a bond’s rating, the lower the interest rate it will carry, and the lower the risk, etc.

Why should I be interested in this post?

This post might interest you if you plan on working in a future in an asset management company or in this sector as a marketing or asset management assistant. You will be able to see what tasks you might be asked to do, the skills that you must have to perform successfully during your internship, as well as terms you might come across that you will need to learn about.

Related posts on the SimTrade blog

   ▶ All posts about Professional experiences

   ▶ Anna BARBERO Career in finance

   ▶ Alexandre VERLET Classic brain teasers from real-life interviews

   ▶ Jayati WALIA My experience as a credit analyst at Amundi Asset Management

Useful resources

Auris Gestion

Standard & Poor’s

Moody’s

About the author

The article was written in December 2022 by Ines ILLES MEJIAS (ESSEC Business School, ESSEC Business School, Global BBA, 2020-2024).

My experience as an Oil Analyst at an oil and energy trading company

Youssef_Louraoui

In this article, Youssef LOURAOUI (Bayes Business School, MSc. Energy, Trade & Finance, 2021-2022) shares his experience as an oil market analyst during a summer internship at Petroineos Trading Ltd.

About the company

Petroineos is a joint venture between PetroChina International London (PCIL) and the INEOS Group for refining and energy trading. PetroChina is one of the world’s major oil and gas enterprises and the INEOS is a refining and petrochemical group. This joint venture is a young and ambitious firm that was founded in 2011 with a dynamic approach to business and a strong ambition for long-term success.

In Petroineos, there are three sections which handle trading in different products: crude, refined products, and power and emissions. Petroineos’s annual trading volume exceeds 70 million tonnes, with assets worth around $6 billion and trading revenue in excess of $30 billion (Figure 1).

Its strategically positioned refineries in Grangemouth (Scotland) and Lavera (France), is among the oldest crude oil refineries in Europe. It provides gasoline to both domestic (Scotland and
France) and international markets, while also sustaining local economies. Every year, the two refineries process about 360,000 barrels of crude oil per day and create over 16 million tonnes of oil products.

Figure 1. Petroineos Trading Ltd. key numbers.
 Petroineos Trading Ltd. numbers
Source: Petroineos Trading Ltd. (2022)

My internship

I was affected along with seven other interns, each with their own specific project that had to be completed throughout the 12-week internship. The first days were intense because we had to deal with jargon, practitioners’ concepts, and the dynamic nature of the trading floor. Fortunately, I had the opportunity to be supervised by a seasoned analyst during the first month of the internship, which allowed me step up my skills and be up and running for the next two months. There was a healthy mix of autonomous work and fruitful discussions with the other colleagues. This forced me to be independent in my job while also working in groups when required, allowing for some flexibility in how I performed.

The highlight of this internship was the relationships created with my fellow interns. It really helped a lot to make this experience so enjoyable. The teamwork, the feedbacks, the help that was offered among interns was really amazing; it created a strong bond inside and outside the office. It was a blessing to meet and learn from them as they are all well accomplished individuals who have a bright future in front of them.

By the end of my internship, I felt that I improved significantly in terms of notions regarding crude oil market, time management, relationships with my colleagues and good memories overall.

Missions

During this internship, I was assigned to the analysis department, which was in charge of providing reports and market updates for the major commodity markets. I did my internship in extraordinary times for the oil and commodity markets as it was a few months after the beginning of the Ukrainian-Russian conflict. At that time, the world was experiencing a global energy crisis, a shock of extraordinary scope and complexity. This crisis reminded us of the events of the 1970s (Oil shocks 73-79). This crisis had many dimensions, including coal, oil, gas, food security, and climate change. Governments around the world are seeking for an equilibrium that would deliver a good energy mix while retaining affordable and secure resources for their people, not only reducing reliance on a single commodity.

Natural gas spot prices had reached unprecedented highs, the equivalent of USD 250 for a barrel of oil. Furthermore, the crisis had fueled inflationary pressures and raised the prospect of a recession, as well as a massive USD 2 trillion windfall for fossil fuel producers above their 2021 net revenue. In response to energy shortages and high costs, governments have invested well over USD 500 billion, primarily in industrialized nations, to protect consumers from the immediate consequences of inflation (especially in gas and oil).

Keeping this in mind, I was assigned coverage on the impact of Western sanctions on the Russian crude oil market. Every market participant seeked to predict the impact of the sanctions on the number of barrels shipped from Russia.

  • Is Russia going to reduce its crude oil export since Europe represented alone more than 80% of its exports volume before the war?
  • Who are the new market players that are profiting from this situation and capitalizing on a discounted Russian crude oil in the international crude oil market?
  • Are there any patterns that can help in better understanding the crude flows?

Those three questions captured the importance of the analysis that had to be conducted in order to give sound and well detailed answers in order to capitalize with trading strategies that could leverage this information.

The main task was the redaction of the report which was shared across the whole company. The basic idea of this report was to give a micro overview on a weekly basis on the main changes that can impact the Urals market. I was in charge of analysing the vessels movement from the main ports in Russia and capture their discharging patterns in order to extract valuable information into the main discharging regions that are profiting from this market.

I also collaborated on other analyses with another intern from the Data Science department, which involved analyzing alternative data to identify any interesting signals that may be used as a trading strategy. In addition, I shared two further quantitative analyses involving econometric relationships to analyze Russian and global oil demand in analysis to other factors of relevance. The projects were incredibly interesting, and the insights were also helpful in understanding the complexities of collecting insights in an environment where analysts are surrounded by noisy data that must be filtered in order to communicate valuable information.

The main conclusions of the Russian coverage:

India and China as the main actors profiting from the discounted price of Urals

Russia becomes the highest exporter of crude oil to India (Urals crude). The pattern change since the war unfolded. Historically, India imported oil from Irak and Saudi Arabia. This interest is based on the decision by the Asian countries to capitalise on a devaluated Russian oil price in the international crude oil market, which reached at some point of the war 30$/bbl difference with the main international oil benchmark (Brent). According to the Indian energy minister, they want to lock in the best price available in the international crude oil market (Figure 1).

According to US treasury Janet Yellen, this trend will continue, profiting from the western price cap on russian crude oil. G7 countries agreed in September to implement the price cap, which the US government hopes will be in place by December 5 when an EU embargo on the shipment of Russian crude comes into force. Under the mechanism, European companies will be permitted to transport and insure shipments of Russian oil to third countries as long as it is sold below a fixed price — an effort to limit the impact of the sanctions on global oil flows but ensure Russia’s earns less from the trade.

Dislocation of the market between Europe and Asia

Europe decreased importantly its dependence from Russian crude oil after the war in Ukraine. There is a shifting of actors in this market, with Asia skyrocketing demand compared to previous years because of the attractivity of the Urals in the international crude oil market. Also, if we shrink oil price volatility to its components, we see that:

  • External factors, other than supply and demand, play a more important role now specifically policy issues are more important than ever, accounting for more than 25% of oil volatility
  • 20 years ago we could explain 90% of oil volatility by supply and demand, now this rate dropped to 65%.

Required skills

I would mention two main skills: market understanding and programming expertise. It is very beneficial to stay on top of market news, as it is good industry practice (especially for an analyst position) to understand the many market events that affect the specific commodity covered. As most businesses strive for automation, acquiring and mastering a programming language can only benefit future analysts. It has become a wider pre-requirement for most analyst positions.

Key learning

Key numbers

Some key numbers to have in mind to understand the crude oil market:

  • Estimation according to a reliable source: 1.43 trillion barrels left in the ground (2022)
  • Estimated part of oil consumption in most developed economies (around 30-45% of crude oil in the energy mix)
  • Estimated daily production per day in the world: around 100mb/d
  • Russia produce approximately 10% of the world daily crude oil demand. Urals production (the most traded grade of crude in the Russian oil market) was fluctuating on average around the 2mb/d threshold

Refinery margins

Refinery margin is derived from the difference between the refinery cost (buying crude) and the profit (selling refined product).

Refinery margin and crack spread

Crack spread represents the differential between the price of crude oil and the price of products refined. It is an industry specific metric to assess refining profitability. Crack refers also to the chemical process of decomposing the crude oil into different petroleum products. As different variables affect the price of crude oil and its refined products, this has an implication for refining margins.

Implementation of a crack strategy

  • Single product crack: Differential of one barrel of crude with one barrel of refined product
  • Multi product crack: Use of different refined products to secure a margin

Trading the crack spread

  • Either long or short crack: If long crack, confident view that refinery margins will strengthen (either crude oil price decreasing or products demand increasing)
  • If short crack, confident view that refinery margins are worsening, either because crude oil price increase or decrease of products demand

Reading crack spread as market signal

  • If crack widens, refined products more expensive than crude oil price, market expects that crude oil price will increase (to tighten back the spread to historical norm)
  • If crack tightens, refined products are sold cheaper than the price of crude oil, market expects that refined products (will reduce production) in order to get more expensive to widen the spread

Why should I be interested in this post?

This post will help any student looking to break into the work of oil or energy trading, but more generally for any analyst position, to have a grasp of the main concepts and skills that are required in the market and have a better understanding of the energy industry.

Related posts on the SimTrade blog

   ▶ All posts about Professional experiences

   ▶ Youssef LOURAOUI My experience as a portfolio manager in a central bank

   ▶ Aastha DAS My experience during a summer internship as an investment banking analyst at G2 Capital Advisors

   ▶ Aamey MEHTA My experience as a credit analyst at Wells Fargo

Useful resources

Business Analysis

Petroineos

Financial Times (2022) Russia becomes India’s top oil supplier as sanctions deflate price.

About the author

The article was written in December 2022 by Youssef LOURAOUI (Bayes Business School, MSc. Energy, Trade & Finance, 2021-2022).

Asset allocation techniques

Youssef LOURAOUI

In this article, Youssef LOURAOUI (Bayes Business School, MSc. Energy, Trade & Finance, 2021-2022) presents the concept of asset allocation, a pillar concept in portfolio management.

This article is structured as follows: we introduce the notion of asset allocation, and we use a practical example to illustrate this notion.

Introduction

An investment portfolio is a collection of assets that are owned by an investor. Individual assets, such as bonds and stocks, as well as asset baskets, such as mutual funds or exchange-traded funds, can be employed. When constructing a portfolio, investors often consider both the projected return and risk. A well-balanced portfolio includes a wide range of investments to benefit from diversification.

The asset allocation is one of the processes in the portfolio construction process. At this point, the investor (or fund manager) must divide the available capital into a number of assets that meet the criteria in terms of risk and return trade-off, while adhering to the investment policy, which specifies the amount of exposure an investor can have and the amount of risk the fund manager can hold in his or her portfolio.

The next phase in the process is to evaluate the risk and return characteristics of the various assets. The analyst develops economic and market expectations that can be used to develop a recommended asset allocation for the customer. The distribution of equities, fixed-income securities, and cash; sub asset classes, such as corporate and government bonds; and regional weightings within asset classes are all decisions that must be taken in the portfolio’s asset allocation. Real estate, commodities, hedge funds, and private equity are examples of alternative assets. Economists and market strategists may set the top-down view on economic conditions and broad market movements. The returns on various asset classes are likely to be altered by economic conditions; for example, equities may do well when economic growth has been surprisingly robust whereas bonds may do poorly if inflation soars. These situations will be forecasted by economists and strategists.

The top-down approach

A top-down approach begins with assessment of macroeconomic factors. The investor examines markets and sectors based on the existing and projected economic climate in order to invest in those that are predicted to perform well. Finally, funding is evaluated for specific companies within these categories.

The bottom up approach

A bottom-up approach focuses on company-specific variables such as management quality and business potential rather than economic cycles or industry analysis. It is less concerned with broad economic trends than top-down analysis is, and instead focuses on company particular.

Types of asset allocations

Arnott and Fabozzi (1992) divide asset allocation into three types: 1) policy asset allocation; 2) dynamic asset allocation; and 3) tactical asset allocation.

Policy asset allocation

The policy asset allocation decision is a long-term asset allocation decision in which the investor aims to assess a suitable long-term “normal” asset mix that represents an optimal mixture of controlled risk and enhanced return. The strategies that offer the best prospects of achieving strong long-term returns are inherently risky. The strategies that offer the greatest safety tend to offer very moderate return opportunities. The balancing of these opposing goals is known as policy asset allocation. The asset mix (i.e., the allocation among asset classes) is mechanistically altered in response to changing market conditions in dynamic asset allocation. Once the policy asset allocation has been established, the investor can focus on the possibility of active deviations from the regular asset mix established by policy. Assume the long-run asset mix is established to be 60% equities and 40% bonds. A variation from this mix under certain situations may be tolerated. A decision to diverge from this mix is generally referred to as tactical asset allocation if it is based on rigorous objective measurements of value. Tactical asset allocation does not consist of a single, well-defined strategy.

Dynamic asset allocation

The term “dynamic asset allocation” can refer to both long-term policy decisions and intermediate-term efforts to strategically position the portfolio to benefit from big market swings, as well as aggressive tactical strategies. As an investor’s risk expectations and tolerance for risk fluctuate, the normal or policy asset allocation may change. It is vital to understand what aspect of the asset allocation decision is being discussed and in what context the words “asset allocation” are being used when delving into asset allocation difficulties.

Tactical asset allocation

Tactical asset allocation broadly refers to active strategies that seek to enhance performance by opportunistically adjusting the asset mix of a port- folio in response to the changing patterns of reward available in the capi- tal markets. Notably, tactical asset allocation tends to refer to disciplined techniques for evaluating anticipated rates of return on various asset classes and constructing an asset allocation response intended to capture larger rewards.

Asset allocation application: an example

For this example, lets suppose the fictitious following scenario with real data involved:

Mr. Dubois recently sold his local home construction company in the south of France to a multinational homebuilder with a nationwide reach. He accepted a job as regional manager for that national homebuilder after selling his company. He is now thinking about the financial future for himself and his family. He is looking forward to his new job, where he enjoys his new role and where he will earn enough money to meet his family’s short- and medium-term liquidity demands. He feels strongly that he should not invest the profits of the sale of his company in real estate because his income currently rely on the state of the real estate market. He speaks with a financial adviser at his bank about how to invest his money so that he can retire comfortably in 20 years.

The initial portfolio objective they created seek a nominal return goal of 7% with a Sharpe ratio of at least 1 (for this example, we consider the risk-free rate to be equal to zero). The bank’s asset management division gives Mr Dubois and his adviser with the following data (Figure 1) on market expectations.

Figure 1. Risk, return and correlation estimates on market expectation.
 Time-series regression
Source: computation by the author (Data: Refinitiv Eikon).

In order to replicate a global asset allocation approach, we shortlisted a number of trackers that would represent our investment universe. To keep a well-balanced approach, we took trackers that would represent the main asset classes: global equities (VTI – Vanguard Total Stock Market ETF), bonds (IEF – iShares 7-10 Year Treasury Bond ETF and TLT – iShares 20+ Year Treasury Bond ETF) and commodities (DBC – Invesco DB Commodity Index Tracking Fund and GLD – SPDR Gold Shares). To create the optimal asset allocation, we extracted the equivalent of a ten-year timeframe from Refinitiv Eikon to capture the overall performance of the portfolio in the long run. As captured in Figure 1, the global equities was the best performing asset class during the period covered (13.02% annualised return), followed by long term bond (4.78% annualised return) and by gold (4.65% annualised return).

Figure 2. Asset class performance (rebased to 100).
 Time-series regression
Source: computation by the author (Data: Refinitiv Eikon).

After analyzing the historical return on the assets retained, as well as their volatility and covariance (and correlation), we can apply Mean-Variance portfolio optimization to determine the optimal portfolio. The optimal asset allocation would be the end outcome of the optimization procedure. The optimal portfolio, according to Markowitz’ seminal study on portfolio construction, will seek to create the best risk-return trade-off for an investor. After performing the calculations, we notice that investing 42.15% in the VTI fund, 30.69% in the IEF fund, 24.88% in the TLT fund, and 2.28% in the GLD fund yields the best asset allocation. As reflected in this asset allocation, the investor intends to invest his assets in a mix of equities (about 43%) and bonds (approximately 55%), with a marginal position (around 3%) in gold, which is widely employed in portfolio management as an asset diversifier due to its correlation with other asset classes. As captured by this asset allocation, we can clearly see the defensive nature of this portfolio, which relies significantly on the bond part of the allocation to operate as a hedge while relying on the equities part as the main driver of returns.

As shown in Figure 3, the optimal asset allocation has a better Sharpe ratio (1.27 vs 0.62) and is captured farther along the efficient frontier line than a naive equally-weighted allocation . The only portfolio with the needed characteristics is the optimal one, as the investor’s goal was to attain a 7% projected return with a minimum Sharpe ratio of 1.

Figure 3. Optimal asset allocation and the Efficient Frontier plot.
 Time-series regression
Source: computation by the author (Data: Refinitiv Eikon).

Will this allocation, however, continue to perform well in the future? The market’s reliance on future expectations, return, volatility, and correlation predictions, as well as the market regime, will ultimately determine how much the performance predicted by this study will really change in the future.

Excel file for asset allocation

You can find below the Excel spreadsheet that complements the example above.

 Download the Excel file for asset allocation

Why should I be interested in this post?

The purpose of portfolio management is to maximize (expected) returns on the entire portfolio, not just on one or two stocks for a given level of risk. By monitoring and maintaining your investment portfolio, you can build a substantial amount of wealth for a variety of financial goals, such as retirement planning. This post facilitates comprehension of the fundamentals underlying portfolio construction and investing.

Related posts on the SimTrade blog

   ▶ Youssef LOURAOUI Markowitz Modern Portfolio Theory

   ▶ Youssef LOURAOUI Optimal portfolio

   ▶ Youssef LOURAOUI Portfolio

Useful resources

Academic research

Arnott, R. D., and F. J. Fabozzi. 1992. The many dimensions of the asset allocation decision. In Active asset allocation, edited by R. Arnott and F. J. Fabozzi. Chicago: Probus Publishing.

Fabozzi, F.J., 2009. Institutional Investment Management: Equity and Bond Portfolio Strategies and Applications. I (4-6). John Wiley and Sons Edition.

Pamela, D. and Fabozzi, F., 2010. The Basics of Finance: An Introduction to Financial Markets, Business Finance, and Portfolio Management. John Wiley and Sons Edition.

About the author

The article was written in December 2022 by Youssef LOURAOUI (Bayes Business School, MSc. Energy, Trade & Finance, 2021-2022).

Quantitative equity investing

Youssef_Louraoui

In this article, Youssef LOURAOUI (Bayes Business School, MSc. Energy, Trade & Finance, 2021-2022) elaborates on the concept of quantitative equity investing, a type of investment approach in the equity trading space.

This article follows the following structure: we introduce the quantitative equity investing. We present a review of the major types of quantitative equity strategies and we finish with a conclusion.

Introduction

Quantitative equity investing refers to funds that uses model-driven decision making when trading in the equity space. Quantitative analysts program their trading rules into computer systems and use algorithmic trading, which is overseen by humans.

Quantitative investing has several advantages and disadvantages over discretionary trading. The disadvantages are that the trading rule cannot be as personalized to each unique case and cannot be dependent on “soft” information such human judgment. These disadvantages may be lessened as processing power and complexity improve. For example, quantitative models may use textual analysis to examine transcripts of a firm’s conference calls with equity analysts, determining whether certain phrases are commonly used or performing more advanced analysis.

The advantages of quantitative investing include the fact that it may be applied to a diverse group of stocks, resulting in great diversification. When a quantitative analyst builds an advanced investment model, it can be applied to thousands of stocks all around the world at the same time. Second, the quantitative modeling rigor may be able to overcome many of the behavioral biases that commonly impact human judgment, including those that produce trading opportunities in the first place. Third, using past data, the quant’s trading principles can be backtested (Pedersen, 2015).

Types of quantitative equity strategies

There are three types of quantitative equity strategies: fundamental quantitative investing, statistical arbitrage, and high-frequency trading (HFT). These three types of quantitative investing differ in various ways, including their conceptual base, turnover, capacity, how trades are determined, and their ability to be backtested.

Fundamental quantitative investing

Fundamental quantitative investing, like discretionary trading, tries to use fundamental analysis in a systematic manner. Fundamental quantitative investing is thus founded on economic and financial theory, as well as statistical data analysis. Given that prices and fundamentals only fluctuate gradually, fundamental quantitative investing typically has a turnover of days to months and a high capacity (meaning that a large amount of money can be invested in the strategy), owing to extensive diversification.

Statistical arbitrage

Statistical arbitrage aims to capitalize on price differences between closely linked stocks. As a result, it is founded on a grasp of arbitrage relations and statistics, and its turnover is often faster than that of fundamental quants. Statistical arbitrage has a lower capacity due to faster trading (and possibly fewer stocks having arbitrage spreads).

High Frequency Trading (HFT)

HFT is based on statistics, information processing, and engineering, as the success of an HFT is determined in part by the speed with which they can trade. HFTs focus on having superfast computers and computer programs, as well as co-locating their computers at exchanges, actually trying to get their computer as close to the exchange server as possible, using fast cables, and so on. HFTs have the fastest trading turnover and, as a result, the lowest capacity.

The three types of quants also differ in how they make trades: Fundamental quants typically make their deals ex ante, statistical arbitrage traders make their trades gradually, and high-frequency traders let the market make their transactions. A fundamental quantitative model, for example, identifies high-expected-return stocks and then buys them, almost always having their orders filled; a statistical arbitrage model seeks to buy a mispriced stock but may terminate the trading scheme before completion if prices have moved adversely; and, finally, an HFT model may submit limit orders to both buy and sell to several exchanges, allowing the market to determine which ones are hit. Because of this trading structure, fundamental quant investing can be simulated with some reliability via a backtest; statistical arbitrage backtests rely heavily on assumptions on execution times, transaction costs, and fill rates; and HFT strategies are frequently difficult to simulate reliably, so HFTs must rely on experiments.

Table 1. Quantitative equity investing main categories and characteristics.
 Quantitative equity investing
Source: Source: Pedersen, 2015.

Conclusion

Quants run their models on hundreds, if not thousands, of stocks. Because diversification eliminates most idiosyncratic risk, firm-specific shocks tend to wash out at the portfolio level, and any single position is too tiny to make a major impact in performance.

An equity market neutral portfolio eliminates total stock market risk by being equally long and short. Some quants attempt to establish market neutrality by ensuring that the long side’s dollar exposure equals the dollar worth of all short bets. This technique, however, is only effective if the longs and shorts are both equally risky. As a result, quants attempt to balance market beta on both the long and short sides. Some quants attempt to be both dollar and beta neutral.

Why should I be interested in this post?

It may provide an opportunity for investors to diversify their global portfolios. Including hedge funds in a portfolio can help investors obtain absolute returns that are uncorrelated with typical bond/equity returns.

For practitioners, learning how to incorporate hedge funds into a standard portfolio and understanding the risks associated with hedge fund investing can be beneficial.

Understanding if hedge funds are truly providing “excess returns” and deconstructing the sources of return can be beneficial to academics. Another challenge is determining whether there is any “performance persistence” in hedge fund returns.

Getting a job at a hedge fund might be a profitable career path for students. Understanding the market, the players, the strategies, and the industry’s current trends can help you gain a job as a hedge fund analyst or simply enhance your knowledge of another asset class.

Related posts on the SimTrade blog

   ▶ Youssef LOURAOUI Introduction to Hedge Funds

   ▶ Youssef LOURAOUI Portfolio

   ▶ Youssef LOURAOUI Long-short strategy

Useful resources

Academic research

Pedersen, L. H., 2015. Efficiently Inefficient: How Smart Money Invests and Market Prices Are Determined. Chapter 9 : 133 – 164. Princeton University Press.

About the author

The article was written in December 2022 by Youssef LOURAOUI (Bayes Business School, MSc. Energy, Trade & Finance, 2021-2022).

Optimal portfolio

Youssef_Louraoui

In this article, Youssef LOURAOUI (Bayes Business School, MSc. Energy, Trade & Finance, 2021-2022) presents the concept of optimal portfolio, which is central in portfolio management.

This article is structured as follows: we first define the notion of an optimal portfolio (in the mean-variance framework) and we then illustrate the concept of optimal portfolio with an example.

Introduction

An investor’s investment portfolio is a collection of assets that he or she possesses. Individual assets such as bonds and equities can be used, as can asset baskets such as mutual funds or exchange-traded funds (ETFs). When constructing a portfolio, investors typically evaluate the expected return as well as the risk. A well-balanced portfolio contains a diverse variety of investments.

An optimal portfolio is a collection of assets that maximizes the trade-off between expected return and risk: the portfolio with the highest expected return for a given level of risk, or the portfolio with the lowest risk for a given level of expected return.

To obtain the optimal portfolio, Markowitz sought to optimize the following dual program:

The first optimization seeks to maximize expected return with respect to a specific level of risk, subject to the short-selling constraint (weights of the portfolio should be equal to one).

img_SimTrade_implementing_Markowitz_2

The second optimization seeks to minimize the variance of the portfolio with respect to a specific level of expected return, subject to the short-selling constraint (weights of the portfolio should be equal to one).

img_SimTrade_implementing_Markowitz

Mathematical foundations

The investment universe is composed of N assets characterized by their expected returns μ and variance-covariance matrix V. For a given level of expected return μP, the Markowitz model gives the composition of the optimal portfolio. The vector of weights of the optimal portfolio is given by the following formula:

img_SimTrade_implementing_Markowitz_1

With the following notations:

  • wP = vector of asset weights of the portfolio
  • μP = desired level of expected return
  • e = identity vector
  • μ = vector of expected returns
  • V = variance-covariance matrix of returns
  • V-1 = inverse of the variance-covariance matrix
  • t = transpose operation for vectors and matrices

A, B and C are intermediate parameters computed below:

img_SimTrade_implementing_Markowitz_2

The variance of the optimal portfolio is computed as follows

img_SimTrade_implementing_Markowitz_3

To calculate the standard deviation of the optimal portfolio, we take the square root of the variance.

Optimal portfolio application: the case of two assets

To create the optimal portfolio, we first obtain monthly historical data for the last two years from Bloomberg for two stocks that will comprise our portfolio: Apple and CMS Energy Corporation. Apple is in the technology area, but CMS Energy Corporation is an American company that is entirely in the energy sector. Apple’s historical return for the two years covered was 41.86%, with a volatility of 35.11%. Meanwhile, CMS Energy Corporation’s historical return was 13.95% with a far lower volatility of 15.16%.

According to their risk and return profiles, Apple is an aggressive stock pick in our example, but CMS Energy is a much more defensive stock that would serve as a hedge in our example. The correlation between the two stocks is 0.19, indicating that they move in the same direction. In this example, we will consider the market portfolio, defined as a theoretical portfolio that reflects the return of the whole investment universe, which is captured by the wide US equities index (S&P500 index).

As captured in Figure 1, CMS Energy suffered less severe losses than Apple. When compared to the red bars, the blue bars are far more volatile and sharp in terms of the size of the move in both directions.

Figure 1. Apple and CMS Energy Corporation return breakdown.
 Time-series regression
Source: computation by the author (Data: Bloomberg)

After analyzing the historical return on both stocks, as well as their volatility and covariance (and correlation), we can use Mean-Variance portfolio optimization to find the optimal portfolio. According to Markowitz’ foundational study on portfolio construction, the optimal portfolio will attempt to achieve the best risk-return trade-off for an investor. After doing the computations, we discover that the optimal portfolio is composed of 45% Apple stock and 55% CMS Energy corporation stock. This portfolio would return 26.51% with a volatility of 19.23%. As captured in Figure 2, the optimal portfolio is higher on the efficient frontier line and has a higher Sharpe ratio (1.27 vs 1.23 for the theoretical market portfolio).

Figure 2. Optimal portfolio.
 Optimal portfolio plot 2 asset
Source: computation by the author (Data: Bloomberg)

You can find below the Excel spreadsheet that complements the example above.

 Optimal portfolio spreadsheet for two assets

Optimal portfolio application: the general case

We generated a large time series to obtain useful results by downloading the equivalent of 23 years of market data from a data provider (in this example, Bloomberg). We generate the variance-covariance matrix after obtaining all necessary statistical data, which includes the expected return and volatility indicated by the standard deviation of the returns for each stock during the provided period. Table 1 depicts the expected return and volatility for each stock retained in this analysis.

Table 1. Asset characteristics of Apple, Amazon, Microsoft, Goldman Sachs, and Pfizer.
img_SimTrade_implementing_Markowitz_spreadsheet_1
Source: computation by the author.

We can start the optimization task by setting a desirable expected return after computing the expected return, volatility, and the variance-covariance matrix of expected return. With the data that is fed into the appropriate cells, the model will complete the optimization task. For a 20% desired expected return, we get the following results (Table 2).

Table 2. Asset weights for an optimal portfolio.
Optimal portfolio case 1
Source: computation by the author.

To demonstrate the effect of diversification in the reduction of volatility, we can form a Markowitz efficient frontier by tilting the desired anticipated return with their relative volatility in a graph. The Markowitz efficient frontier is depicted in Figure 1 for various levels of expected return. We highlighted the portfolio with 20% expected return with its respective volatility in the plot (Figure 3).

Figure 3. Optimal portfolio plot for 5 asset case.
Optimal portfolio case 1
Source: computation by the author.

You can download the Excel file below to use the Markowitz portfolio allocation model.

 Download the Excel file for the optimal portfolio with n asset case

Why should I be interested in this post?

The purpose of portfolio management is to maximize the (expected) returns on the entire portfolio, not just on one or two stocks. By monitoring and maintaining your investment portfolio, you can build a substantial amount of wealth for a variety of financial goals such as retirement planning. This post facilitates comprehension of the fundamentals underlying portfolio construction and investing.

Related posts on the SimTrade blog

   ▶ Youssef LOURAOUI Portfolio

   ▶ Youssef LOURAOUI Factor Investing

   ▶ Youssef LOURAOUI Origin of factor investing

   ▶ Youssef LOURAOUI Markowitz Modern Portfolio Theory

Useful resources

Academic research

Pamela, D. and Fabozzi, F., 2010. The Basics of Finance: An Introduction to Financial Markets, Business Finance, and Portfolio Management. John Wiley and Sons Edition.

Markowitz, H., 1952. Portfolio Selection. The Journal of Finance, 7(1): 77-91.

About the author

The article was written in December 2022 by Youssef LOURAOUI (Bayes Business School, MSc. Energy, Trade & Finance, 2021-2022).

Long-short equity strategy

Youssef LOURAOUI

In this article, Youssef LOURAOUI (Bayes Business School, MSc. Energy, Trade & Finance, 2021-2022) presents the long-short equity strategy, one of pioneer strategies in the hedge fund industry. The goal of the long-short equity investment strategy is to buy undervalued stocks and sell short overvalued ones.

This article is structured as follow: we introduce the long-short strategy principle. Then, we present a practical case study to grasp the overall methodology of this strategy. We conclude with a performance analysis of this strategy in comparison with a global benchmark (MSCI All World Index).

Introduction

According to Credit Suisse, a long-short strategy can be defined as follows: “Long-short equity funds invest on both long and short sides of equity markets, generally focusing on diversifying or hedging across particular sectors, regions, or market capitalizations. Managers have the flexibility to shift from value to growth; small to medium to large capitalization stocks; and net long to net short. Managers can also trade equity futures and options as well as equity related securities and debt or build portfolios that are more concentrated than traditional long-only equity funds.”

This strategy has the particularity of potentially generate returns in both rising and falling markets. However, stock selection is key concern, and the stock picking ability of the fund manager is what makes this strategy profitable (or not!). The trade-off of this approach is to reduce market risk but exchange it for specific risk. Another key characteristic of this type of strategy is that overall, funds relying on long-short are net long in their trading exposure (long bias).

Equity strategies

In the equity universe, we can separate long-short equity strategies into discretionary long-short equity, dedicated short bias, and quantitative.

Discretionary long-short

Discretionary long-short equity managers typically decide whether to buy or sell stocks based on a basic review of the value of each firm, which includes evaluating its growth prospects and comparing its profitability to its valuation. By visiting managers and firms, these fund managers also evaluate the management of the company. Additionally, they investigate the accounting figures to judge their accuracy and predict future cash flows. Equity long-short managers typically predict on particular companies, but they can also express opinions on entire industries.

Value investors, a subset of equity managers, concentrate on acquiring undervalued companies and holding these stocks for the long run. A good illustration of a value investor is Warren Buffett. Since companies only become inexpensive when other investors stop investing in them, putting this trading approach into practice frequently entails being a contrarian (buy assets after a price decrease). Because of this, cheap stocks are frequently out of favour or purchased while others are in a panic. Traders claim that deviating from the standard is more difficult than it seems.

Dedicated short bias

Like equity long-short managers, dedicated short bias is a trading technique that focuses on identifying companies to sell short. Making a prediction that the share price will decline is known as short selling. Similar to how purchasing stock entails profiting if the price increases, holding a short position entail profiting if the price decreases. Dedicated short-bias managers search for companies that are declining. Since dedicated short-bias managers are working against the prevailing uptrend in markets since stocks rise more frequently than they fall (this is known as the equity risk premium), they make up a very small proportion of hedge funds.

Most hedge funds in general, as well as almost all equity long-short hedge funds and dedicated short-bias hedge funds, engage in discretionary trading, which refers to the trader’s ability to decide whether to buy or sell based on his or her judgement and an evaluation of the market based on past performance, various types of information, intuition, and other factors.

Quantitative

The quantitative investment might be seen as an alternative to this traditional style of trading. Quants create systems that methodically carry out the stated definitions of their trading rules. They use complex processing of ideas that are difficult to analyse using non-quantitative methods to gain a slight advantage on each of the numerous tiny, diversified trades. To accomplish this, they combine a wealth of data with tools and insights from a variety of fields, including economics, finance, statistics, mathematics, computer science, and engineering, to identify relationships that market participants may not have immediately fully incorporated in the price. Quantitative traders use computer systems that use these relationships to generate trading signals, optimise portfolios considering trading expenses, and execute trades using automated systems that send hundreds of orders every few seconds. In other words, data is fed into computers that execute various programmes under the supervision of humans to conduct trading (Pedersen, 2015).

Example of a long-short equity strategy

The purpose of employing a long-short strategy is to profit in both bullish and bearish markets. To measure the profitability of this strategy, we implemented a long-short strategy from the beginning of January 2022 to June 2022. In this time range, we are long Exxon Mobile stock and short Tesla. The data are extracted from the Bloomberg terminal. The strategy of going long Exxon Mobile and short Tesla is purely educational. This strategy’s basic idea is to profit from rising oil prices (leading to a price increase for Exxon Mobile) and rising interest rates (leading to a price decrease for Tesla). Over the same period, the S&P 500 index has dropped 23%, while the Nasdaq Composite has lost more than 30%. The Nasdaq Composite is dominated by rapidly developing technology companies that are especially vulnerable to rising interest rates.

Overall, the market’s net exposure is zero because we are 100% long Exxon Mobile and 100% short Tesla stock. This strategy succeeded to earn significant returns in both the long and short legs of the trade over a six-month timeframe. It yielded a 99.5 percent return, with a 36.8 percent gain in the value of the Exxon Mobile shares and a 62.8 percent return on the short Tesla position. Figure 1 shows the overall performance of each equity across time.

Figure 1. Long-short equity strategy performance over time
 Time-series regression
Source: computation by the author (Data: Bloomberg)

You can find below the Excel spreadsheet that complements the example above.

 Download the Excel file to analyse a long-short equity strategy

Performance of the long-short equity strategy

To capture the performance of the long-short equity strategy, we use the Credit Suisse hedge fund strategy index. To establish a comparison between the performance of the global equity market and the long-short hedge fund strategy, we examine the rebased performance of the Credit Suisse index with respect to the MSCI All-World Index. Over a period from 2002 to 2022, the long-short equity strategy index managed to generate an annualised return of 5.96% with an annualised volatility of 7.33%, leading to a Sharpe ratio of 0.18. Over the same period, the MSCI All World Index managed to generate an annualised return of 6.00% with an annualised volatility of 15.71%, leading to a Sharpe ratio of 0.11. The low correlation of the long-short equity strategy with the MSCI All World Index is equal to 0.09, which is closed to zero. Overall, the Credit Suisse hedge fund strategy index performed somewhat slightly worse than the MSCI All World Index, but presented a much lower volatility leading to a higher Sharpe ratio (0.18 vs 0.11).

Figure 2. Performance of the long-short equity strategy compared to the MSCI All-World Index across time.
 Time-series regression
Source: computation by the author (Data: Bloomberg)

You can find below the Excel spreadsheet that complements the explanations about the Credit Suisse hedge fund strategy index.

 Download the Excel file to perform a Fama-MacBeth regression method with N-asset

Why should I be interested in this post?

Long-short funds seek to reduce negative risk while increasing market upside. They might, for example, invest in inexpensive stocks that the fund managers believe will rise in price while simultaneously shorting overvalued stocks to cut losses. Other strategies used by long-short funds to lessen market volatility include leverage and derivatives. Understanding the profits and risks of such a strategy might assist investors in incorporating this hedge fund strategy into their portfolio allocation.

Related posts on the SimTrade blog

   ▶ Youssef LOURAOUI Introduction to Hedge Funds

   ▶ Youssef LOURAOUI Portfolio

Useful resources

Academic research

Pedersen, L. H., 2015. Efficiently Inefficient: How Smart Money Invests and Market Prices Are Determined. Princeton University Press.

Business Analysis

BlackRock Long-short strategy

BlackRock Investment Outlook

Credit Suisse Hedge fund strategy

Credit Suisse Hedge fund performance

Credit Suisse Long-short strategy

Credit Suisse Long-short performance benchmark

About the author

The article was written in December 2022 by Youssef LOURAOUI (Bayes Business School, MSc. Energy, Trade & Finance, 2021-2022).

Fama-MacBeth two-step regression method: the case of K risk factors

Fama-MacBeth two-step regression method: the case of K risk factors

Youssef LOURAOUI

In this article, Youssef LOURAOUI (Bayes Business School, MSc. Energy, Trade & Finance, 2021-2022) presents the Fama-MacBeth two-step regression method used to test asset pricing models in the case of K risk factors.

This article is structured as follows: we introduce the Fama-MacBeth two-step regression method. Then, we present the mathematical foundation that underpins their approach for K risk factors. We provide an illustration for the 3-factor mode developed by Fama and French (1993).

Introduction

Risk factors are frequently employed to explain asset returns in asset pricing theories. These risk factors may be macroeconomic (such as consumer inflation or unemployment) or microeconomic (such as firm size or various accounting and financial metrics of the firms). The Fama-MacBeth two-step regression approach found a practical way for measuring how correctly these risk factors explain asset or portfolio returns. The aim of the model is to determine the risk premium associated with the exposure to these risk factors.

The first step is to regress the return of every asset against one or more risk factors using a time-series approach. We obtain the return exposure to each factor called the “betas” or the “factor exposures” or the “factor loadings”.

The second step is to regress the returns of all assets against the asset betas obtained in Step 1 using a cross-section approach. We obtain the risk premium for each factor. Then, Fama and MacBeth assess the expected premium over time for a unit exposure to each risk factor by averaging these coefficients once for each element.

Mathematical foundations

We describe below the mathematical foundations for the Fama-MacBeth regression method for a K-factor application. In the analysis, we investigated the Fame-French three factor model in order to understand their significance as a fundamental driver of returns for investors under the Fama-MacBeth framework.

The model considers the following inputs:

  • The return of N assets denoted by Ri for asset i observed every day over the time period [0, T].
  • The risk factors denoted by Fk for k equal from 1 to K.

Step 1: time-series analysis of returns

For each asset i from 1 to N, we estimate the following linear regression model:

Fama-French time-series regression

From this model, we obtain the βi, Fk which is the beta associated with the kth risk factor.

Step 2: cross-sectional analysis of returns

For each period t from 1 to T, we estimate the following linear regression model:

Fama-French cross-sectional regression

Application: the Fama-French 3-Factor model

The Fama-French 3-factor model is an illustration of Fama-MacBeth two-step regression method in the case of K risk factors (K=3). The three factors are the market (MKT) factor, the small minus big (SMB) factor, and the high minus low (HML) factor. The SMB factor measures the difference in expected returns between small and big firms (in terms of market capitalization). The HML factor measures the difference in expected returns between value stocks and growth stock.

The model considers the following inputs:

  • The return of N assets denoted by Ri for asset i observed every day over the time period [0, T].
  • The risk factors denoted by FMKT associated to the MKT risk factor, FSMB associated to the MKT risk factor which measures the difference in expected returns between small and big firms (in terms of market capitalization) and FHML associated to 𝐻𝑀𝐿 (“High Minus Low”) which measures the difference in expected returns between value stocks and growth stock

Step 1: time-series regression

img_SimTrade_Fama_French_time_series_regression

Step 2: cross-sectional regression

img_SimTrade_Fama_French_cross_sectional_regression

Figure 1 represents for a given period the cross-sectional regression of the return of all individual assets with respect to their estimated individual beta for the MKT factor.

Figure 1. Cross-sectional regression for the market factor.
 Cross-section regression for the MKT factor Source: computation by the author.

Figure 2 represents for a given period the cross-sectional regression of the return of all individual assets with respect to their estimated individual beta for the SMB factor.

Figure 2. Cross-sectional regression for the SMB factor.
 Cross-section regression for the SMB factor Source: computation by the author.

Figure 3 represents for a given period the cross-sectional regression of the return of all individual assets with respect to their estimated individual beta for the SMB factor.

Figure 3. Cross-sectional regression for the HML factor.
 Cross-section regression for the HML factor Source: computation by the author.

Empirical study of the Fama-MacBeth regression

Fama-MacBeth seminal paper (1973) was based on an analysis of the market factor by assessing constructed portfolios of similar betas ranked by increasing values. This approach helped to overcome the shortcoming regarding the stability of the beta and correct for conditional heteroscedasticity derived from the computation of the betas for individual stocks. They performed a second time the cross-sectional regression of monthly portfolio returns based on equity betas to account for the dynamic nature of stock returns, which help to compute a robust standard error and assess if there is any heteroscedasticity in the regression. The conclusion of the seminal paper suggests that the beta is “dead”, in the sense that it cannot explain returns on its own (Fama and MacBeth, 1973).

Empirical study: Stock approach for a K-factor model

We collected a sample of 440 significant firms’ end-of-day stock prices in the US economy from January 3, 2012 to December 31, 2021. We calculated daily returns for each stock as well as the factor used in this analysis. We chose the S&P500 index to represent the market since it is an important worldwide stock benchmark that captures the US equities market.

Time-series regression

To assess the multi-factor regression, we used the Fama-MacBeth 3-factor model as the main factors assessed in this analysis. We regress the average returns for each stock against their factor betas. The first regression is statistically tested. This time-series regression is run on a subperiod of the whole period from January 03, 2012, to December 31, 2018. We use a t-statistic to explain the regression’s behavior. Because the p-value is in the rejection zone (less than the significance level of 5%), we can conclude that the factors can first explain an investor’s returns. However, as we will see later in the article, when we account for a second regression as proposed by Fama and MacBeth, the factors retained in this analysis are not capable of explaining the return on asset returns on its own. The stock approach produces statistically significant results in time-series regression at 10%, 5%, and even 1% significance levels. As shown in Table 1, the p-value is in the rejection range, indicating that the factors are statistically significant.

Table 1. Time-series regression t-statistic result.
 Cross-section regression Source: computation by the author.

Cross-sectional regression

Over a second period from January 04, 2019, to December 31, 2021, we compute the dynamic regression of returns at each data point in time with respect to the betas computed in Step 1.

That being said, when the results are examined using cross-section regression, they are not statistically significant, as indicated by the p-value in Table 2. We are unable to reject the null hypothesis. The premium investors are evaluating cannot be explained solely by the factors assessed. This suggests that factors retained in the analysis fail to adequately explain the behavior of asset returns. These results are consistent with the Fama-MacBeth article (1973).

Table 2. Cross-section regression t-statistic result.
Source: computation by the author.

Excel file

You can find below the Excel spreadsheet that complements the explanations covered in this article.

 Download the Excel file to perform a Fama-MacBeth regression method with K-asset

Why should I be interested in this post?

Fama-MacBeth made a significant contribution to the field of econometrics. Their findings cleared the way for asset pricing theory to gain traction in academic literature. The Capital Asset Pricing Model (CAPM) is far too simplistic for a real-world scenario since the market factor is not the only source that drives returns; asset return is generated from a range of factors, each of which influences the overall return. This framework helps in capturing other sources of return.

Related posts on the SimTrade blog

   ▶ Youssef LOURAOUI Fama-MacBeth regression method: stock and portfolio approach

   ▶ Youssef LOURAOUI Fama-MacBeth regression method: Analysis of the market factor

   ▶ Jayati WALIA Capital Asset Pricing Model (CAPM)

   ▶ Youssef LOURAOUI Security Market Line (SML)

   ▶ Youssef LOURAOUI Origin of factor investing

   ▶ Youssef LOURAOUI Factor Investing

Useful resources

Academic research

Brooks, C., 2019. Introductory Econometrics for Finance (4th ed.). Cambridge: Cambridge University Press. doi:10.1017/9781108524872

Fama, E. F., MacBeth, J. D., 1973. Risk, Return, and Equilibrium: Empirical Tests. Journal of Political Economy, 81(3), 607–636.

Roll R., 1977. A critique of the Asset Pricing Theory’s test, Part I: On Past and Potential Testability of the Theory. Journal of Financial Economics, 1, 129-176.

American Finance Association & Journal of Finance (2008) Masters of Finance: Eugene Fama (YouTube video)

About the author

The article was written in December 2022 by Youssef LOURAOUI (Bayes Business School, MSc. Energy, Trade & Finance, 2021-2022).