The MOEX Russia index

The MOEX Russia index

Nithisha CHALLA

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

The MOEX Russia index

The Moscow Exchange Russia Index (MOEX Russia Index) is market-capitalization-weighted index of the 50 biggest and most liquid companies listed on the Moscow Exchange. It was first presented in 1997 and serves as the benchmark index for the Russian stock market.

A wide range of sectors are covered by the MOEX Russia Index, including consumer goods, energy, finance, and telecommunications. By market capitalization, Gazprom, Sberbank, Lukoil, Novatek, and Tatneft were the top five index members as of September 2021.

The MOEX Russia Index is a market-capitalization-weighted index, which means that rather than using share price to determine a company’s weight in the index, it utilizes market capitalization. This enables it to depict the overall performance of the Russian equity market with greater accuracy.

Investors and asset managers frequently use the MOEX Russia Index as a benchmark to monitor the performance of the Russian equity market. ETFs and index funds are examples of financial products that are made to track the MOEX Russia Index.

The MOEX Russia Index has the ticker “IMOEX” in the financial sector.

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

Table 1. Top 10 stocks in the MOEX Russia index.
Top 10 stocks in the MOEX Russia index
Source: computation by the author (data: Yahoo! Finance website).

Calculation of the MOEX Russia index value

As per the free-float methodology, which is used to calculate the MOEX Russia Index, each company’s weight in the index is determined by the percentage of its shares that are available for public trading rather than by its overall market capitalization. The goal of this methodology is to present a more accurate picture of the market value of each company.

The formula to compute the MOEX Russia is given by

Float Adjusted Market Capitalization Index value

Where I is the index value, k a given asset, K the number of assets in the index, Pk the market price of asset k, Nk the number of issued shares for asset k, Fk the float factor of asset k, and t the time of calculation of the index.

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

Float Adjusted Market Capitalization Weighted Index Weight

Use of the MOEX Russia index in asset management

For asset managers who make investments in the Russian equity market, the MOEX Russia index serves as a crucial benchmark. It is used as an exchange-traded fund (ETF) and Russian equity fund performance benchmark. The index can be used by investors to assess the performance of their portfolios and compare it to the performance of the complete market.

Benchmark for equity funds

Equity funds that invest in Russian companies use the MOEX Russia Index as a benchmark. The MOEX Russia index can also serve as the foundation for the investment products that track indices, like index funds and ETFs. These goods are made to follow the index’s performance and give buyers access to Russian equity market. Investors can gain broad market exposure through the purchase of these products without picking individual stocks.

Financial products around the MOEX Russia index

There are several financial products tracking the performance of the MOEX Russia Index, allowing investors to gain exposure to the Russian stock market.

  • ETFs are investment funds traded on the stock exchanges, designed to track performance of an index. There are several ETFs that track the MOEX Russia Index, such as the Xtrackers Russia UCITS and the VanEck Vectors Russia
  • Index funds are designed to track performance of an index. Index funds based on the MOEX Russia Index include the Sberbank Asset Management MOEX Russia Index Fund and the Raiffeisen Russia Equity Fund.
  • Futures and options contracts based on the MOEX Russia Index provide investors with the ability to speculate on the future performance of the index. For example, the Moscow Exchange offers futures contracts based on the MOEX Russia Index.
  • Certificates are investment products that allow investors to get exposure to the MOEX Russia Index. Société Générale offers a range of certificates linked to the MOEX Russia Index, such as the MOEX Russia Index Tracker Certificate.

Historical data for the MOEX Russia index

How to get the data?

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

For example, you can download data for the MOEX Russia index from January 3, 1984 on Yahoo! Finance (the Yahoo! code for MOEX Russia index is IMOEX.ME).

Yahoo! Finance
Source: Yahoo! Finance.

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

R program

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

Download R file

Data file

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

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

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

Evolution of the MOEX Russia index

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

Figure 1. Evolution of the MOEX Russia index.
Evolution of the MOEX Russia index
Source: computation by the author (data: Yahoo! Finance website).

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

Figure 2. Evolution of the MOEX Russia index returns.
Evolution of the MOEX Russia index return
Source: computation by the author (data: Yahoo! Finance website).

Summary statistics for the MOEX Russia index

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

Table 4 below presents the following summary statistics estimated for the MOEX Russia index:

  • The mean
  • The standard deviation (the squared root of the variance)
  • The skewness
  • The kurtosis.

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

Table 4. Summary statistics for the MOEX Russia index.
Summary statistics for the MOEX Russia index
Source: computation by the author (data: Yahoo! Finance website).

Statistical distribution of the MOEX Russia index returns

Historical distribution

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

Figure 3. Historical distribution of the MOEX Russia index returns.
Historical distribution of the daily MOEX Russia index returns
Source: computation by the author (data: Yahoo! Finance website).

Gaussian distribution

The Gaussian distribution (also called the normal distribution) is a parametric distribution with two parameters: the mean and the standard deviation of returns. We estimated these two parameters over the period from January 3, 1984 to December 30, 2022. The mean of daily returns is equal to 0.02% and the standard deviation of daily returns is equal to 1.37% (or equivalently 3.94% for the annual mean and 28.02% for the annual standard deviation as shown in Table 3 above).

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

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

Risk measures of the MOEX Russia index returns

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

Table 5 below presents the following risk measures estimated for the MOEX Russia index:

  • The long-term volatility (the unconditional standard deviation estimated over the entire period)
  • The short-term volatility (the standard deviation estimated over the last three months)
  • The Value at Risk (VaR) for the left tail (the 5% quantile of the historical distribution)
  • The Value at Risk (VaR) for the right tail (the 95% quantile of the historical distribution)
  • The Expected Shortfall (ES) for the left tail (the average loss over the 5% quantile of the historical distribution)
  • The Expected Shortfall (ES) for the right tail (the average loss over the 95% quantile of the historical distribution)
  • The Stress Value (SV) for the left tail (the 1% quantile of the tail distribution estimated with a Generalized Pareto distribution)
  • The Stress Value (SV) for the right tail (the 99% quantile of the tail distribution estimated with a Generalized Pareto distribution)

Table 5. Risk measures for the MOEX Russia index.
Risk measures for the MOEX Russia index
Source: computation by the author (data: Yahoo! Finance website).

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

Why should I be interested in this post?

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

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

Related posts on the SimTrade blog

About financial indexes

   ▶ Nithisha CHALLA Financial indexes

   ▶ Nithisha CHALLA Calculation of financial indexes

   ▶ Nithisha CHALLA The business of financial indexes

   ▶ Nithisha CHALLA Float

Other financial indexes

   ▶ Nithisha CHALLA The S&P 500 index

   ▶ Nithisha CHALLA The FTSE 100 index

   ▶ Nithisha CHALLA The Nikkei 225 index

   ▶ Nithisha CHALLA The CSI 300 index

About portfolio management

   ▶ Youssef LOURAOUI Portfolio

   ▶ Jayati WALIA Returns

About statistics

   ▶ Shengyu ZHENG Moments de la distribution

   ▶ Shengyu ZHENG Mesures de risques

Useful resources

Academic research about risk

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

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

Business

wikipedia What is the MOEX Russia index?

Moex Everything about MOEX

Data

Yahoo! Finance

Yahoo! Finance MOEX Russia index

About the author

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

The BOVESPA index

The BOVESPA index

Nithisha CHALLA

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

The BOVESPA index

The BOVESPA Index, or IBOVESPA, is the benchmark stock market index of the São Paulo Stock Exchange (B3) in Brazil. The index was launched on January 2, 1968, and tracks the performance of the 80 most traded stocks on the exchange.

As of 2021, the top 10 constituents of the BOVESPA Index included companies from a range of sectors such as finance, energy, materials, and consumer goods. Some of the largest companies in the index include Petrobras, Vale, Itau Unibanco, and Banco Bradesco.

The BOVESPA Index is considered a crucial indicator of the Brazilian stock market’s overall health and serves as a benchmark for Brazilian equity mutual funds and exchange-traded funds (ETFs). The index is weighted by free float market capitalization, which means that the more valuable a company is, the more significant its impact on the index’s movements.

The BOVESPA Index has experienced significant fluctuations in the past due to factors such as political instability, economic crises, and shifts in global commodity prices. Trading platforms and financial websites represent the BOVESPA Index using the ticker symbol “IBOV”.

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

Table 1. Top 10 stocks in the BOVESPA index.
Top 10 stocks in the BOVESPA index
Source: computation by the author (data: Yahoo! Finance website).

Calculation of the BOVESPA index value

The index is a market-capitalization-weighted index, which means that the weight of each company in the index is determined by its market capitalization, calculated by multiplying the number of outstanding shares by the current market price per share. It tracks the performance of the largest and most actively traded companies listed on the Sao Paulo Stock Exchange (B3).

The formula to compute the BOVESPA index is given by

Market Capitalization Index value

Where I is the index value, k a given asset, K the number of assets in the index, Pk the market price of asset k, Nk the number of issued shares for asset k, and t the time of calculation of the index.

In a market capitalization-weighted index, the weight of asset k is given by formula can be rewritten as

Market Capitalization Weighted Index Weight

Which clearly shows that the weight of each asset in the index is its market capitalization of the asset divided by the sum of the market capitalizations of all assets.

Note that the divisor, whose calculation is based on the number of shares, is typically adjusted for events such as stock splits and dividends. The divisor is used to ensure that the value of the index remains consistent over time despite changes in the number of outstanding shares.

Use of the BOVESPA index in asset management

The BOVESPA Index is frequently used by investors, analysts, and financial institutions to track the overall trend of the Brazilian stock market and to make investment decisions. It is also used as a basis for the creation of financial products such as exchange-traded funds (ETFs) and index futures contracts.

Benchmark for equity funds

The BOVESPA index is widely considered as the benchmark index for the Brazilian stock market and is used as a measure of the performance of the Brazilian economy. It includes a diverse range of companies from various sectors such as finance, mining, energy, and consumer goods. Some of the largest companies listed on the BOVESPA Index include Petrobras, Vale, Itau Unibanco, and Banco Bradesco.

Financial products around the BOVESPA index

There are various financial instruments available to investors seeking to track the performance of the BOVESPA index.

  • ETFs are popular investment products that allow investors to gain exposure to the BOVESPA index. These include the iShares MSCI Brazil ETF and the BMO MSCI Brazil Index ETF.
  • Index funds are also designed to track the performance of an index. The BlackRock Brazil Equity Index Fund and the Bradesco FIA BOVESPA Index Fund are examples of index funds that track the BOVESPA index.
  • Futures and options contracts based on the BOVESPA index provide investors with the ability to speculate on the future performance of the index. BM&FBOVESPA, the Brazilian futures and options exchange, offers futures contracts based on the BOVESPA index.
  • Certificates are investment products that allow investors to gain exposure to the BOVESPA index. Credit Suisse and Itau Unibanco offer certificates linked to the BOVESPA index, such as the Brazil Index Tracker Certificate.

Historical data for the BOVESPA index

How to get the data?

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

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

Yahoo! Finance
Source: Yahoo! Finance.

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

R program

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

Download R file

Data file

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

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

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

Evolution of the BOVESPA index

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

Figure 1. Evolution of the BOVESPA index.
Evolution of the BOVESPA index
Source: computation by the author (data: Yahoo! Finance website).

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

Figure 2. Evolution of the BOVESPA index returns.
Evolution of the BOVESPA index return
Source: computation by the author (data: Yahoo! Finance website).

Summary statistics for the BOVESPA index

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

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

  • The mean
  • The standard deviation (the squared root of the variance)
  • The skewness
  • The kurtosis.

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

Table 4. Summary statistics for the BOVESPA index.
Summary statistics for the BOVESPA index
Source: computation by the author (data: Yahoo! Finance website).

Statistical distribution of the BOVESPA index returns

Historical distribution

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

Figure 3. Historical distribution of the BOVESPA index returns.
Historical distribution of the daily BOVESPA index returns
Source: computation by the author (data: Yahoo! Finance website).

Gaussian distribution

The Gaussian distribution (also called the normal distribution) is a parametric distribution with two parameters: the mean and the standard deviation of returns. We estimated these two parameters over the period from January 3, 1984 to December 30, 2022. The mean of daily returns is equal to 0.02% and the standard deviation of daily returns is equal to 1.37% (or equivalently 3.94% for the annual mean and 28.02% for the annual standard deviation as shown in Table 3 above).

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

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

Risk measures of the BOVESPA index returns

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

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

  • The long-term volatility (the unconditional standard deviation estimated over the entire period)
  • The short-term volatility (the standard deviation estimated over the last three months)
  • The Value at Risk (VaR) for the left tail (the 5% quantile of the historical distribution)
  • The Value at Risk (VaR) for the right tail (the 95% quantile of the historical distribution)
  • The Expected Shortfall (ES) for the left tail (the average loss over the 5% quantile of the historical distribution)
  • The Expected Shortfall (ES) for the right tail (the average loss over the 95% quantile of the historical distribution)
  • The Stress Value (SV) for the left tail (the 1% quantile of the tail distribution estimated with a Generalized Pareto distribution)
  • The Stress Value (SV) for the right tail (the 99% quantile of the tail distribution estimated with a Generalized Pareto distribution)

Table 5. Risk measures for the BOVESPA index.
Risk measures for the BOVESPA index
Source: computation by the author (data: Yahoo! Finance website).

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

Why should I be interested in this post?

For a number of reasons, management students (as future managers and individual investors) should learn about the BOVESPA index. The BOVESPA index is a key benchmark for the Indian equity market, which is a fast developing market. Understanding how the index is constructed, how it performs, and the companies that make up the index is important for anyone studying finance or business in India or interested in investing in Indian equities.

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

Related posts on the SimTrade blog

About financial indexes

   ▶ Nithisha CHALLA Financial indexes

   ▶ Nithisha CHALLA Calculation of financial indexes

   ▶ Nithisha CHALLA The business of financial indexes

   ▶ Nithisha CHALLA Float

Other financial indexes

   ▶ Nithisha CHALLA The S&P 500 index

   ▶ Nithisha CHALLA The FTSE 100 index

   ▶ Nithisha CHALLA The CSI 300 index

   ▶ Nithisha CHALLA The Nikkei 225 index

About portfolio management

   ▶ Youssef LOURAOUI Portfolio

   ▶ Jayati WALIA Returns

About statistics

   ▶ Shengyu ZHENG Moments de la distribution

   ▶ Shengyu ZHENG Mesures de risques

Useful resources

Academic research about risk

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

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

Business

Capital What is the Bovespa index?

Wikipedia An introduction to the Bovespa

International Finance Corporation Everything about Bovespa

Data

Yahoo! Finance

Yahoo! Finance BOVESPA index

About the author

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

The Nifty 50 index

The Nifty 50 index

Nithisha CHALLA

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

The Nifty 50 index

One of the important stock market indices in India is the Nifty 50 index, also referred to as the NSE Nifty. The National Stock Exchange (NSE) of India first introduced this index in 1996, and it currently measures the performance of the top 50 companies listed on the exchange.

Market capitalization, liquidity, and trading volumes are just a few of the criteria that are used to choose the companies that will be included in the Nifty 50 index. The index’s companies come from a variety of industries, including, among others, banking, IT, healthcare, and energy.

The Nifty50 is a free float market capitalization-weighted index, which means that the market capitalization of each stock determines how much of that stock is included in the index. In comparison to a price-weighted index, the Nifty 50 is a better representation of the Indian stock market as a whole because of this.

Indian mutual funds, exchange-traded funds, and other financial products frequently use the Nifty 50 index as a benchmark. Since it offers insightful information about how the Indian economy and stock market are performing, it is also closely watched by investors and traders worldwide.

The ticker symbol used for the Nifty 50 index is “NIFTY”.

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

Table 1. Top 10 stocks in the Nifty 50 index.
Top 10 stocks in the Nifty 50 index
Source: computation by the author (data: Yahoo Finance! financial website).

Calculation of the Nifty 50 index value

The top 50 companies listed on the National Stock Exchange (NSE) of India are tracked by the Nifty 50 stock market index in India. It is frequently used as the benchmark index for the Indian equity market and as a gauge of the state of the Indian economy as a whole. Companies from a variety of industries, including financial services, information technology, energy, and consumer goods, make up the Nifty50 index.

A free-float market-capitalization-weighted methodology is utilized to calculate the Nifty 50 index, which means that each company’s weight in the index is determined by its market capitalization adjusted for the shares that are actually traded in the secondary market (float).

The formula to compute the Nifty 50 index is given by

Float Adjusted Market Capitalization Index value

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

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

Float Adjusted Market Capitalization Weighted Index Weight

Use of the Nifty 50 index in asset management

The Nifty 50 serves as a benchmark for asset managers to assess the performance of their Indian equity portfolios. Asset managers can determine whether their investments are producing alpha, or outperforming the market, by comparing the returns of their portfolios to the performance of the index. If their portfolios underperform the index, they might need to adjust their stock selection or investment strategies to boost returns.

Benchmark for equity funds

In India, the Nifty 50 is frequently used as a benchmark for equity funds. By reflecting the performance of the top 50 companies listed on the National Stock Exchange of India, the index offers a snapshot of the performance of the Indian stock market. Investors can learn how well their investment is doing relative to the market by comparing the performance of a fund to the Nifty 50. If a fund consistently outperforms the index, the asset manager likely has a sound investment strategy and is adept at stock selection and market timing.

Financial products around the Nifty 50 index

There are several financial products that track the performance of the Nifty 50 index, allowing investors to gain exposure to the Indian stock market.

  • ETFs are investment funds traded on stock exchanges, designed to track the performance of an index. There are several ETFs that track the Nifty 50 index, such as the ICICI Prudential Nifty ETF and the Kotak Nifty ETF.
  • Index funds are also designed to track the performance of an index. Index funds based on the Nifty50 index include the HDFC Index Fund-Nifty 50 Plan and the UTI Nifty Index Fund.
  • Futures and options contracts based on the Nifty 50 index provide investors with the ability to speculate on the future performance of the index. For example, the National Stock Exchange of India (NSE) offers futures contracts based on the Nifty 50 index.
  • Certificates are investment products that allow investors to gain exposure to the Nifty50 index. Some banks in India offer certificates linked to the Nifty 50 index, such as the SBI Magnum Nifty Next 50 Index Fund.

With the help of these financial products, investors can invest in a diversified portfolio of 50 large-cap Indian companies from a range of industries and get exposure to the performance of the Nifty 50 index. Investors can gain a deeper understanding of industry trends, market competition, and the elements that contribute to business success by examining the performance of companies within these sectors. Asset managers can use these financial products as a benchmark to compare the performance of their equity portfolios to the performance of the entire market.

Historical data for the Nifty 50 index

How to get the data?

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

For example, you can download data for the Nifty 50 index from January 3, 1984 on Yahoo! Finance (the Yahoo! code for Nifty 50 index is ^NSEI).

Yahoo! Finance
Source: Yahoo! Finance.

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

R program

The R program below written by Shengyu ZHENG allows you to download the data from Yahoo! Finance website and to compute summary statistics and risk measures about the Nifty 50 index.

Download R file

Data file

The R program that you can download above allows you to download the data for the Nifty 50 index from the Yahoo! Finance website. The database starts on January 3, 1984. It also computes the returns (logarithmic returns) from closing prices.

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

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

Evolution of the Nifty 50 index

Figure 1 below gives the evolution of the Nifty 50 index from January 3, 1984 to December 30, 2022 on a daily basis.

Figure 1. Evolution of the Nifty 50 index.
Evolution of the Nifty 50 index
Source: computation by the author (data: Yahoo! Finance website).

Figure 2 below gives the evolution of the Nifty 50 index returns from January 3, 1984 to December 30, 2022 on a daily basis.

Figure 2. Evolution of the Nifty 50 index returns.
Evolution of the Nifty 50 index return
Source: computation by the author (data: Yahoo! Finance website).

Summary statistics for the Nifty 50 index

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

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

  • The mean
  • The standard deviation (the squared root of the variance)
  • The skewness
  • The kurtosis.

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

Table 4. Summary statistics for the Nifty 50 index.
Summary statistics for the Nifty 50 index
Source: computation by the author (data: Yahoo! Finance website).

Statistical distribution of the Nifty 50 index returns

Historical distribution

Figure 3 represents the historical distribution of the Nifty 50 index daily returns for the period from January 3, 1984 to December 30, 2022.

Figure 3. Historical distribution of the Nifty 50 index returns.
Historical distribution of the daily Nifty 50 index returns
Source: computation by the author (data: Yahoo! Finance website).

Gaussian distribution

The Gaussian distribution (also called the normal distribution) is a parametric distribution with two parameters: the mean and the standard deviation of returns. We estimated these two parameters over the period from January 3, 1984 to December 30, 2022. The mean of daily returns is equal to 0.02% and the standard deviation of daily returns is equal to 1.37% (or equivalently 3.94% for the annual mean and 28.02% for the annual standard deviation as shown in Table 3 above).

Figure 4 below represents the Gaussian distribution of the Nifty 50 index daily returns with parameters estimated over the period from January 3, 1984 to December 30, 2022.

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

Risk measures of the Nifty 50 index returns

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

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

  • The long-term volatility (the unconditional standard deviation estimated over the entire period)
  • The short-term volatility (the standard deviation estimated over the last three months)
  • The Value at Risk (VaR) for the left tail (the 5% quantile of the historical distribution)
  • The Value at Risk (VaR) for the right tail (the 95% quantile of the historical distribution)
  • The Expected Shortfall (ES) for the left tail (the average loss over the 5% quantile of the historical distribution)
  • The Expected Shortfall (ES) for the right tail (the average loss over the 95% quantile of the historical distribution)
  • The Stress Value (SV) for the left tail (the 1% quantile of the tail distribution estimated with a Generalized Pareto distribution)
  • The Stress Value (SV) for the right tail (the 99% quantile of the tail distribution estimated with a Generalized Pareto distribution)

Table 5. Risk measures for the Nifty 50 index.
Risk measures for the Nifty 50 index
Source: computation by the author (data: Yahoo! Finance website).

The volatility is a global measure of risk as it considers all the returns. The Value at Risk (VaR), Expected Shortfall (ES) and Stress Value (SV) are local measures of risk as they focus on the tails of the distribution. The study of the left tail is relevant for an investor holding a long position in the Nifty 50 index while the study of the right tail is relevant for an investor holding a short position in the Nifty 50 index.

Why should I be interested in this post?

For a number of reasons, management students (as future managers and individual investors) should learn about the Nifty 50 index. The Nifty 50 index is a key benchmark for the Indian equity market, which is a fast developing market. Understanding how the index is constructed, how it performs, and the companies that make up the index is important for anyone studying finance or business in India or interested in investing in Indian equities.

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

Related posts on the SimTrade blog

About financial indexes

   ▶ Nithisha CHALLA Financial indexes

   ▶ Nithisha CHALLA Calculation of financial indexes

   ▶ Nithisha CHALLA The business of financial indexes

   ▶ Nithisha CHALLA Float

Other financial indexes

   ▶ Nithisha CHALLA The S&P 500 index

   ▶ Nithisha CHALLA The FTSE 100 index

   ▶ Nithisha CHALLA The CSI 300 index

   ▶ Nithisha CHALLA The Nikkei 225 index

About portfolio management

   ▶ Youssef LOURAOUI Portfolio

   ▶ Jayati WALIA Returns

About statistics

   ▶ Shengyu ZHENG Moments de la distribution

   ▶ Shengyu ZHENG Mesures de risques

Useful resources

Academic research about risk

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

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

Business

CFI What is the NIFTY 50 Index?

Wikipedia An introduction to the NIFTY 50

NSE India 25 years journey of NSE

Data

Yahoo! Finance

Yahoo! Finance Nifty 50 index

About the author

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

The CSI 300 index

The CSI 300 index

Nithisha CHALLA

In this article, Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management, 2021-2023) presents the CSI 300 index and details its characteristics.

The CSI 300 index

The performance of 300 large-cap stocks traded on the Shanghai and Shenzhen stock exchanges in China is tracked by the capitalization-weighted stock market index known as the CSI 300 (China Securities Index 300). The China Securities Index Company, a joint venture between the Shanghai Stock Exchange and the Shenzhen Stock Exchange, introduced it in April 2005.

The CSI 300’s members are chosen based on their free float market capitalization, liquidity, as well as other aspects like profitability, potential for growth, and financial soundness. Companies from a wide range of industries, including finance, consumer goods, energy, and technology are included in the index.

The CSI 300 is frequently used by traders and investors as a benchmark for the Chinese stock market to gauge market trends and assess portfolio performance. As a measure of the health of China’s economy and of investor perception of the nation’s companies and financial markets, it is also closely watched by policymakers, economists, and analysts. The performance of the Chinese economy can be closely tracked by both domestic and foreign investors thanks to the CSI 300.

Through a range of financial products, including exchange-traded funds (ETFs), index funds, futures, and options contracts, investors can get exposure to the CSI 300 index.

The CSI 300 index has the ticker symbol “CSI300” in the financial sector.

Table 1 below gives the Top 10 stocks in the CSI 300 index in terms of market capitalization as of January 31, 2023.

Table 1. Top 10 stocks in the CSI 300 index.
Top 10 stocks in the CSI 300 index
Source: computation by the author (data: Yahoo Finance! financial website).

Table 2 below gives the sector representation of the CSI 300 index in terms of number of stocks and market capitalization as of January 31, 2023.

Table 2. Sector representation in the CSI 300 index.
Sector representation in the CSI 300 index
Source: computation by the author (data: Yahoo Finance! financial website).

Calculation of the CSI 300 index value

The China Securities Index Company, a joint venture between the Shanghai Stock Exchange and the Shenzhen Stock Exchange, is in charge of managing the index.

A free-float market-capitalization-weighted methodology is utilized to calculate the CSI 300 index, which means that each company’s weight in the index is determined by its market capitalization adjusted for the shares that are actually traded in the secondary market (float).

The formula to compute the CSI 300 index is given by

Float Adjusted Market Capitalization Index value

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

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

Float Adjusted Market Capitalization Weighted Index Weight

Use of the CSI 300 index in asset management

The performance of the biggest and most liquid stocks listed on the Shanghai and Shenzhen stock exchanges is frequently monitored by investors using the CSI 300 index, which serves as a benchmark for the Chinese equity market. Asset managers use the index to compare the returns on their portfolios to market returns and to decide which investments to make. The CSI 300 index, which is focused on China’s domestic A-share market, may not accurately reflect the entire Chinese market, it is important to note. To gain a deeper understanding of the Chinese equity market, investors should also take into account other indexes like the MSCI China index and the FTSE China index.

Benchmark for equity funds

We must take into account the index’s makeup in order to determine whether the CSI 300 index serves as a benchmark for equity funds in China. The top 300 companies listed on the Shanghai and Shenzhen stock exchanges, which together make up about 70% of the total market capitalization of the Chinese equity market, are represented by the CSI 300 index. The index provides a thorough representation of the Chinese economy by including businesses from a wide range of industries, including financial, industrial, consumer goods, and technology.

As a result, equity funds that invest in the Chinese equity market frequently use the CSI 300 index as a benchmark. Fund managers can assess their performance by comparing the returns on their investments to the returns produced by the index.

Financial products around the CSI 300 index

There are various financial products available to investors who wish to gain exposure to the Chinese stock market through the CSI 300 index.

  • ETFs are investment funds traded on stock exchanges that aim to track the performance of an index. There are several ETFs that track the CSI 300 index, such as the iShares CSI 300 Index ETF and the China AMC CSI 300 Index ETF.
  • Index funds are similar to ETFs in that they aim to track the performance of an index. Some examples of index funds that track the CSI 300 index include the E Fund CSI 300 Index Fund and the China Southern CSI 300 Index Fund.
  • Futures and options contracts based on the CSI 300 index allow investors to speculate on the future performance of the index. The China Financial Futures Exchange offers futures contracts based on the CSI 300 index.
  • Certificates linked to the CSI 300 index are investment products that offer exposure to the index. China Merchants Bank, for example, offers a range of certificates linked to the CSI 300 index.

Historical data for the CSI 300 index

How to get the data?

The CSI 300 index is the most common index used in finance, and historical data for the CSI 300 index can be easily downloaded from the internet.

For example, you can download data for the CSI 300 index from March 11, 2021 on Yahoo! Finance (the Yahoo! code for CSI 300 index is 000300.SS).

Yahoo! Finance
Source: Yahoo! Finance.

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

R program

The R program below written by Shengyu ZHENG allows you to download the data from Yahoo! Finance website and to compute summary statistics and risk measures about the CSI 300 index.

Download R file

Data file

The R program that you can download above allows you to download the data for the CSI 300 index from the Yahoo! Finance website. The database starts on March 11, 2021. It also computes the returns (logarithmic returns) from closing prices.

Table 3 below represents the top of the data file for the CSI 300 index downloaded from the Yahoo! Finance website with the R program.

Table 3. Top of the data file for the CSI 300 index.
Top of the file for the CSI 300 index data
Source: computation by the author (data: Yahoo! Finance website).

Evolution of the CSI 300 index

Figure 1 below gives the evolution of the CSI 300 index from March 11, 2021 to December 30, 2022 on a daily basis.

Figure 1. Evolution of the CSI 300 index.
Evolution of the CSI 300 index
Source: computation by the author (data: Yahoo! Finance website).

Figure 2 below gives the evolution of the CSI 300 index returns from March 11, 2021 to December 30, 2022 on a daily basis.

Figure 2. Evolution of the CSI 300 index returns.
Evolution of the CSI 300 index return
Source: computation by the author (data: Yahoo! Finance website).

Summary statistics for the CSI 300 index

The R program that you can download above also allows you to compute summary statistics about the returns of the CSI 300 index.

Table 4 below presents the following summary statistics estimated for the CSI 300 index:

  • The mean
  • The standard deviation (the squared root of the variance)
  • The skewness
  • The kurtosis.

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

Table 4. Summary statistics for the CSI 300 index.
Summary statistics for the CSI 300 index
Source: computation by the author (data: Yahoo! Finance website).

Statistical distribution of the CSI 300 index returns

Historical distribution

Figure 3 represents the historical distribution of the CSI 300 index daily returns for the period from March 11, 2021 to December 30, 2022.

Figure 3. Historical distribution of the CSI 300 index returns.
Historical distribution of the daily CSI 300 index returns
Source: computation by the author (data: Yahoo! Finance website).

Gaussian distribution

The Gaussian distribution (also called the normal distribution) is a parametric distribution with two parameters: the mean and the standard deviation of returns. We estimated these two parameters over the period from March 11, 2021 to December 30, 2022. The mean of daily returns is equal to 0.02% and the standard deviation of daily returns is equal to 1.37% (or equivalently 3.94% for the annual mean and 28.02% for the annual standard deviation as shown in Table 3 above).

Figure 4 below represents the Gaussian distribution of the CSI 300 index daily returns with parameters estimated over the period from March 11, 2021 to December 30, 2022.

Figure 4. Gaussian distribution of the CSI 300 index returns.
Gaussian distribution of the daily CSI 300 index returns
Source: computation by the author (data: Yahoo! Finance website).

Risk measures of the CSI 300 index returns

The R program that you can download above also allows you to compute risk measures about the returns of the CSI 300 index.

Table 5 below presents the following risk measures estimated for the CSI 300 index:

  • The long-term volatility (the unconditional standard deviation estimated over the entire period)
  • The short-term volatility (the standard deviation estimated over the last three months)
  • The Value at Risk (VaR) for the left tail (the 5% quantile of the historical distribution)
  • The Value at Risk (VaR) for the right tail (the 95% quantile of the historical distribution)
  • The Expected Shortfall (ES) for the left tail (the average loss over the 5% quantile of the historical distribution)
  • The Expected Shortfall (ES) for the right tail (the average loss over the 95% quantile of the historical distribution)
  • The Stress Value (SV) for the left tail (the 1% quantile of the tail distribution estimated with a Generalized Pareto distribution)
  • The Stress Value (SV) for the right tail (the 99% quantile of the tail distribution estimated with a Generalized Pareto distribution)

Table 5. Risk measures for the CSI 300 index.
Risk measures for the CSI 300 index
Source: computation by the author (data: Yahoo! Finance website).

The volatility is a global measure of risk as it considers all the returns. The Value at Risk (VaR), Expected Shortfall (ES) and Stress Value (SV) are local measures of risk as they focus on the tails of the distribution. The study of the left tail is relevant for an investor holding a long position in the CSI 300 index while the study of the right tail is relevant for an investor holding a short position in the CSI 300 index.

Why should I be interested in this post?

For a number of reasons, management students (as future managers and individual investors) should learn about the CSI 300 index. The CSI 300 index is a key benchmark for the Japanese equity market, which is one of the world’s largest market. Understanding how the index is constructed, how it performs, and the companies that make up the index is important for anyone studying finance or business in Japan or interested in investing in Japanese equities.

Individual investors can assess the performance of their own investments in the Japanese equity market with the CSI 300 index. Last but not least, a lot of asset management firms base their mutual funds and exchange-traded funds (ETFs) on the CSI 300 index which can considered as interesting assets to diversify a portfolio. Learning about these products and their portfolio and risk management applications can be valuable for management students.

Related posts on the SimTrade blog

About financial indexes

   ▶ Nithisha CHALLA Financial indexes

   ▶ Nithisha CHALLA Calculation of financial indexes

   ▶ Nithisha CHALLA The business of financial indexes

   ▶ Nithisha CHALLA Float

Other financial indexes

   ▶ Nithisha CHALLA The S&P 500 index

   ▶ Nithisha CHALLA The FTSE 100 index

   ▶ Nithisha CHALLA The KOSPI 50 index

   ▶ Nithisha CHALLA The Nikkei 225 index

About portfolio management

   ▶ Youssef LOURAOUI Portfolio

   ▶ Jayati WALIA Returns

About statistics

   ▶ Shengyu ZHENG Moments de la distribution

   ▶ Shengyu ZHENG Mesures de risques

Useful resources

Academic research about risk

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

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

Business

Wikipedia CSI 300 Index

Capital What is the CSI 300 Index?

CEI data China Index: CSI 300 Index: Financial

Data

Yahoo! Finance

Yahoo! Finance CSI 300 index

About the author

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

The Euro Stoxx 50 index

The Euro Stoxx 50 index

Nithisha CHALLA

In this article, Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management, 2021-2023) presents the Euro Stoxx 50 index and details its characteristics.

The Euro Stoxx 50 index

The performance of 50 large-capital companies with headquarters in Eurozone nations is reflected in the Euro Stoxx 50 stock market index. On February 26, 1998, Stoxx Ltd., a partnership between Deutsche Börse AG, Dow Jones & Company, and SIX Group AG, launched it. Companies from a wide range of industries, including the financial, consumer goods, healthcare, and industrial sectors are all included in the index.

Stocks for the Euro Stoxx 50 index are chosen based on market capitalization, liquidity, and sector representation, among other things. Every year in September, the index’s composition is reviewed, and adjustments are made as needed to reflect the state of the market and the performance of the companies.

The free-float market-capitalization-weighted index known as the Euro Stoxx 50. This means that rather than stock price, the index weights each company according to its market capitalization. The index is made available to the investors and traders worldwide and is disseminated in real-time by several financial news outlets.

The Euro Stoxx 50 index’s ticker symbol in the financial sector is “STOXX50E.”

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

Table 1. Top 10 stocks in the Euro Stoxx 50 index.
Top 10 stocks in the Euro Stoxx 50 index
Source: computation by the author (data: Yahoo! Finance website).

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

Table 2. Sector representation in the Euro Stoxx 50 index.
Sector representation in the Euro Stoxx 50 index
Source: computation by the author (data: Yahoo! Finance website).

Calculation of the Euro Stoxx 50 index value

The performance of 50 sizable, blue-chip companies from 12 Eurozone nations, including France, Germany, Italy, and Spain, is tracked by the free-floating market-capitalization-weighted Euro Stoxx 50 index. The index, that includes a wide range of industries including financial services, energy, healthcare, consumer goods, and information technology, is intended to represent the performance of the most liquid and actively traded companies in Eurozone.

A free-float market-capitalization-weighted methodology is utilized to calculate the Euro Stoxx 50 index, which means that each company’s weight in the index is determined by its market capitalization adjusted for the shares that are actually traded in the secondary market (float).

The formula to compute the Euro Stoxx 50 index is given by

Float Adjusted Market Capitalization Index value

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

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

Float Adjusted Market Capitalization Weighted Index Weight

Use of the Euro Stoxx 50 index in asset management

One of the significant indices in Europe, the Euro Stoxx 50 is quite famous and changes in it can have a big impact on market trends and investor sentiment. Investors and traders worldwide have access to index’s real-time values that are published and distributed by a number of financial news sources. The Euro Stoxx 50 is a crucial resource for investors putting efforts to understand the economic and political climate of the Eurozone and gain access to the equity market there. The index can be used by the asset managers as a benchmark to compare the performance of their portfolio to the overall market and to spot potential risk or opportunity areas.

Benchmark for equity funds

Investors and fund managers frequently use the Euro Stoxx 50 to track the health of the Eurozone economy and assess investment opportunities in the region. It is recognized as the top benchmark for the performance of the Eurozone equity market. It consists of businesses from a range of industries, including consumer goods, technology, and finance. The index is used by asset managers to monitor and assess performance of their portfolios in relation to the overall market.

Financial products around the Euro Stoxx 50 index

There are several financial products tracking performance of the Euro Stoxx 50 index. These products allow investors to get exposure to the European stock market.

  • ETFs are investment funds traded on stock exchanges that are designed to track the performance of an index. Several ETFs track the Euro Stoxx 50 index, such as the iShares EURO STOXX 50 UCITS and the Amundi ETF EURO STOXX 50 UCITS
  • Index funds based on the Euro Stoxx 50 index also allow investors to track performance of the index. Examples of index funds tracking Euro Stoxx 50 index include the DWS Invest Euro Stoxx 50 Fund and the BNP Paribas Easy Euro Stoxx 50 UCITS ETF.
  • Futures and options contracts based on Euro Stoxx 50 index provide investors with the ability to speculate on future performance of the index. For example, Eurex offers futures contracts based on the Euro Stoxx 50 index.
  • Certificates are investment products that allow investors to gain exposure to Euro Stoxx 50 index. Societe Generale offers range of certificates linked to the Euro Stoxx 50 index, such as the EURO STOXX 50 Tracker Certificate.

Investors and asset managers may use these financial products to gain exposure to the Euro Stoxx 50 index and manage their portfolios’ risk and return.

Historical data for the Euro Stoxx 50 index

How to get the data?

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

For example, you can download data for the Euro Stoxx 50 index from January 3, 1984 on Yahoo! Finance (the Yahoo! code for Euro Stoxx 50 index is ^STOXX50E).

Yahoo! Finance
Source: Yahoo! Finance.

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

R program

The R program below written by Shengyu ZHENG allows you to download the data from Yahoo! Finance website and to compute summary statistics and risk measures about the Euro Stoxx 50 index.

Download R file

Data file

The R program that you can download above allows you to download the data for the Euro Stoxx 50 index from the Yahoo! Finance website. The database starts on January 3, 1984. It also computes the returns (logarithmic returns) from closing prices.

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

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

Evolution of the Euro Stoxx 50 index

Figure 1 below gives the evolution of the Euro Stoxx 50 index from January 3, 1984 to December 30, 2022 on a daily basis.

Figure 1. Evolution of the Euro Stoxx 50 index.
Evolution of the Euro Stoxx 50 index
Source: computation by the author (data: Yahoo! Finance website).

Figure 2 below gives the evolution of the Euro Stoxx 50 index returns from January 3, 1984 to December 30, 2022 on a daily basis.

Figure 2. Evolution of the Euro Stoxx 50 index returns.
Evolution of the Euro Stoxx 50 index return
Source: computation by the author (data: Yahoo! Finance website).

Summary statistics for the Euro Stoxx 50 index

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

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

  • The mean
  • The standard deviation (the squared root of the variance)
  • The skewness
  • The kurtosis.

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

Table 4. Summary statistics for the Euro Stoxx 50 index.
Summary statistics for the Euro Stoxx 50 index
Source: computation by the author (data: Yahoo! Finance website).

Statistical distribution of the Euro Stoxx 50 index returns

Historical distribution

Figure 3 represents the historical distribution of the Euro Stoxx 50 index daily returns for the period from January 3, 1984 to December 30, 2022.

Figure 3. Historical distribution of the Euro Stoxx 50 index returns.
Historical distribution of the daily Euro Stoxx 50 index returns
Source: computation by the author (data: Yahoo! Finance website).

Gaussian distribution

The Gaussian distribution (also called the normal distribution) is a parametric distribution with two parameters: the mean and the standard deviation of returns. We estimated these two parameters over the period from January 3, 1984 to December 30, 2022. The mean of daily returns is equal to 0.02% and the standard deviation of daily returns is equal to 1.37% (or equivalently 3.94% for the annual mean and 28.02% for the annual standard deviation as shown in Table 3 above).

Figure 4 below represents the Gaussian distribution of the Euro Stoxx 50 index daily returns with parameters estimated over the period from January 3, 1984 to December 30, 2022.

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

Risk measures of the Euro Stoxx 50 index returns

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

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

  • The long-term volatility (the unconditional standard deviation estimated over the entire period)
  • The short-term volatility (the standard deviation estimated over the last three months)
  • The Value at Risk (VaR) for the left tail (the 5% quantile of the historical distribution)
  • The Value at Risk (VaR) for the right tail (the 95% quantile of the historical distribution)
  • The Expected Shortfall (ES) for the left tail (the average loss over the 5% quantile of the historical distribution)
  • The Expected Shortfall (ES) for the right tail (the average loss over the 95% quantile of the historical distribution)
  • The Stress Value (SV) for the left tail (the 1% quantile of the tail distribution estimated with a Generalized Pareto distribution)
  • The Stress Value (SV) for the right tail (the 99% quantile of the tail distribution estimated with a Generalized Pareto distribution)

Table 5. Risk measures for the Euro Stoxx 50 index.
Risk measures for the Euro Stoxx 50 index
Source: computation by the author (data: Yahoo! Finance website).

The volatility is a global measure of risk as it considers all the returns. The Value at Risk (VaR), Expected Shortfall (ES) and Stress Value (SV) are local measures of risk as they focus on the tails of the distribution. The study of the left tail is relevant for an investor holding a long position in the Euro Stoxx 50 index while the study of the right tail is relevant for an investor holding a short position in the Euro Stoxx 50 index.

Why should I be interested in this post?

For a number of reasons, management students (as future managers and individual investors) should learn about the Euro Stoxx 50 index. It is made up of businesses from 11 different Eurozone nations that operate in a variety of industries, including banking, technology, and healthcare. The Euro Stoxx 50 index is a key benchmark for the European equity market, which is one of the world’s largest market. Understanding how the index is constructed, how it performs, and the companies that make up the index is important for anyone studying finance or business in Europe or interested in investing in European equities. Students interested in careers in investment banking, asset management, or global business may find this information useful.

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

Related posts on the SimTrade blog

About financial indexes

   ▶ Nithisha CHALLA Financial indexes

   ▶ Nithisha CHALLA Calculation of financial indexes

   ▶ Nithisha CHALLA The business of financial indexes

   ▶ Nithisha CHALLA Float

Other financial indexes

   ▶ Nithisha CHALLA The S&P 500 index

   ▶ Nithisha CHALLA The FTSE 100 index

   ▶ Nithisha CHALLA The DAX 30 index

   ▶ Nithisha CHALLA The CAC 40 index

   ▶ Nithisha CHALLA The IBEX 35 index

About portfolio management

   ▶ Youssef LOURAOUI Portfolio

   ▶ Jayati WALIA Returns

About statistics

   ▶ Shengyu ZHENG Moments de la distribution

   ▶ Shengyu ZHENG Mesures de risques

Useful resources

Academic research about risk

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

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

Business

Wikipedia History of Euro Stoxx 50

Capital What is the Euro Stoxx Index Definition?

Deutsche Börse Xetra EURO STOXX 50® Index derivatives

Data

Yahoo! Finance

Yahoo Finance Euro Stoxx 50 index

About the author

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

The FTSE 100 index

The FTSE 100 index

Nithisha CHALLA

In this article, Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management, 2021-2023) presents the FTSE 100 index and details its characteristics.

The FTSE 100 index

The Financial Times and the London Stock Exchange established the FTSE 100 index in 1984. It is now run by FTSE Group, a partnership between the Financial Times and the London Stock Exchange. The index, which is regarded as the standard index for the UK equity market, includes the 100 largest companies by market capitalization that are listed on the London Stock Exchange.

Larger companies have a greater influence on the index’s movements than smaller ones because the index is market capitalization-weighted. HSBC, Royal Dutch Shell, BP, and Unilever are a few of the biggest companies that make up the FTSE 100 as of 2021. The FTSE 100 is a key metric for gauging the state of the UK economy because it serves as a benchmark for funds and investment portfolios with UK roots. Recent occurrences like Brexit, the COVID-19 pandemic, and adjustments to the global economy have all had an effect on the index.

The sectoral composition of the FTSE 100 is one of its distinctive features. The financial and resource sectors account for a significant portion of the index’s total market capitalization, which heavily favors these industries.

How is the FTSE 100 index represented in trading platforms and financial websites? The ticker symbol used in the financial industry for the FTSE 100 index is “UKX”.

Table 1 below gives the Top 10 stocks in the FTSE 100 index in terms of market capitalization as of January 31, 2023.

Table 1. Top 10 stocks in the FTSE 100 index.
Top 10 stocks in the FTSE 100 index
Source: computation by the author (data: Yahoo! Finance financial website).

Table 2 below gives the sector representation of the FTSE 100 index in terms of number of stocks and market capitalization as of January 31, 2023.

Table 2. Sector representation in the FTSE 100 index.
Sector representation in the FTSE 100 index
Source: computation by the author (data: Yahoo! Finance financial website).

Calculation of the FTSE 100 index value

The FTSE 100 is a market capitalization-weighted index, which means that each company’s weight in the index is determined by its market capitalization, i.e., the total value of all its outstanding shares. The index, which is regarded as the standard index for the UK equity market, includes the 100 largest companies by market capitalization that are listed on the London Stock Exchange.

The formula to compute the FTSE 100 index is given by

Market Capitalization Index value

Where I is the index value, k a given asset, K the number of assets in the index, Pk the market price of asset k, Nk the number of issued shares for asset k, and t the time of calculation of the index.

In a market capitalization-weighted index, the weight of asset k is given by formula can be rewritten as

Market Capitalization Weighted Index Weight

Which clearly shows that the weight of each asset in the index is its market capitalization of the asset divided by the sum of the market capitalizations of all assets.

Note that the divisor, whose calculation is based on the number of shares, is typically adjusted for events such as stock splits and dividends. The divisor is used to ensure that the value of the index remains consistent over time despite changes in the number of outstanding shares.

Use of the FTSE 100 index in asset management

The performance of large-cap companies listed on the London Stock Exchange is frequently measured against the FTSE 100. Investors can gain insight into the overall health of the UK economy and spot potential opportunities or risks in particular industries or regions by examining the sector weightings and geographic exposure of the index. It serves as a benchmark for asset managers to compare the performance of their equity portfolios to the overall market performance.

Benchmark for equity funds

One of the most popular metrics for assessing the performance of the UK stock market is the FTSE 100. It includes businesses from a wide range of sectors, including consumer goods, healthcare, energy, and finance. As a result, it is frequently used by investors and fund managers to monitor the UK economy’s performance and evaluate the country’s investment opportunities.

Financial products around the FTSE 100 index

There are several financial products that track the performance of the FTSE 100 index, allowing investors to gain exposure to the Japanese stock market.

  • ETFs are investment funds traded on stock exchanges, designed to track the performance of an index. There are several ETFs that track the FTSE 100 index, such as the iShares Core FTSE 100 ETF and the Vanguard FTSE 100 UCITS ETF.
  • index funds are also designed to track the performance of an index. index funds based on the FTSE 100 index include the HSBC FTSE 100 Index Fund and the Legal & General UK 100 Index Fund.
  • Futures and options contracts based on the FTSE 100 index provide investors with the ability to speculate on the future performance of the index. For example, the London International Financial Futures and Options Exchange (LIFFE) offers futures contracts based on the FTSE 100 index.
  • Certificates are investment products that allow investors to gain exposure to the FTSE 100 index. Société Générale offers a range of certificates linked to the FTSE 100 index, such as the FTSE 100 Tracker Certificate.

Historical data for the FTSE 100 index

How to get the data?

The FTSE 100 index is the most common index used in finance, and historical data for the FTSE 100 index can be easily downloaded from the internet.

For example, you can download data for the FTSE 100 index from January 3, 1984 on Yahoo! Finance (the Yahoo! code for FTSE 100 index is ^FTSE).

Yahoo! Finance
Source: Yahoo! Finance.

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

R program

The R program below written by Shengyu ZHENG allows you to download the data from Yahoo! Finance website and to compute summary statistics and risk measures about the FTSE 100 index.

Download R file

Data file

The R program that you can download above allows you to download the data for the FTSE 100 index from the Yahoo! Finance website. The database starts on January 3, 1984. It also computes the returns (logarithmic returns) from closing prices.

Table 3 below represents the top of the data file for the FTSE 100 index downloaded from the Yahoo! Finance website with the R program.

Table 3. Top of the data file for the FTSE 100 index.
Top of the file for the FTSE 100 index data
Source: computation by the author (data: Yahoo! Finance website).

Evolution of the FTSE 100 index

Figure 1 below gives the evolution of the FTSE 100 index from January 3, 1984 to December 30, 2022 on a daily basis.

Figure 1. Evolution of the FTSE 100 index.
Evolution of the FTSE 100 index
Source: computation by the author (data: Yahoo! Finance website).

Figure 2 below gives the evolution of the FTSE 100 index returns from January 3, 1984 to December 30, 2022 on a daily basis.

Figure 2. Evolution of the FTSE 100 index returns.
Evolution of the FTSE 100 index return
Source: computation by the author (data: Yahoo! Finance website).

Summary statistics for the FTSE 100 index

The R program that you can download above also allows you to compute summary statistics about the returns of the FTSE 100 index.

Table 4 below presents the following summary statistics estimated for the FTSE 100 index:

  • The mean
  • The standard deviation (the squared root of the variance)
  • The skewness
  • The kurtosis.

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

Table 4. Summary statistics for the FTSE 100 index.
Summary statistics for the FTSE 100 index
Source: computation by the author (data: Yahoo! Finance website).

Statistical distribution of the FTSE 100 index returns

Historical distribution

Figure 3 represents the historical distribution of the FTSE 100 index daily returns for the period from January 3, 1984 to December 30, 2022.

Figure 3. Historical distribution of the FTSE 100 index returns.
Historical distribution of the daily FTSE 100 index returns
Source: computation by the author (data: Yahoo! Finance website).

Gaussian distribution

The Gaussian distribution (also called the normal distribution) is a parametric distribution with two parameters: the mean and the standard deviation of returns. We estimated these two parameters over the period from January 3, 1984 to December 30, 2022. The mean of daily returns is equal to 0.02% and the standard deviation of daily returns is equal to 1.37% (or equivalently 3.94% for the annual mean and 28.02% for the annual standard deviation as shown in Table 3 above).

Figure 4 below represents the Gaussian distribution of the FTSE 100 index daily returns with parameters estimated over the period from January 3, 1984 to December 30, 2022.

Figure 4. Gaussian distribution of the FTSE 100 index returns.
Gaussian distribution of the daily FTSE 100 index returns
Source: computation by the author (data: Yahoo! Finance website).

Risk measures of the FTSE 100 index returns

The R program that you can download above also allows you to compute risk measures about the returns of the FTSE 100 index.

Table 5 below presents the following risk measures estimated for the FTSE 100 index:

  • The long-term volatility (the unconditional standard deviation estimated over the entire period)
  • The short-term volatility (the standard deviation estimated over the last three months)
  • The Value at Risk (VaR) for the left tail (the 5% quantile of the historical distribution)
  • The Value at Risk (VaR) for the right tail (the 95% quantile of the historical distribution)
  • The Expected Shortfall (ES) for the left tail (the average loss over the 5% quantile of the historical distribution)
  • The Expected Shortfall (ES) for the right tail (the average loss over the 95% quantile of the historical distribution)
  • The Stress Value (SV) for the left tail (the 1% quantile of the tail distribution estimated with a Generalized Pareto distribution)
  • The Stress Value (SV) for the right tail (the 99% quantile of the tail distribution estimated with a Generalized Pareto distribution)

Table 5. Risk measures for the FTSE 100 index.
Risk measures for the FTSE 100 index
Source: computation by the author (data: Yahoo! Finance website).

The volatility is a global measure of risk as it considers all the returns. The Value at Risk (VaR), Expected Shortfall (ES) and Stress Value (SV) are local measures of risk as they focus on the tails of the distribution. The study of the left tail is relevant for an investor holding a long position in the FTSE 100 index while the study of the right tail is relevant for an investor holding a short position in the FTSE 100 index.

Why should I be interested in this post?

For a number of reasons, management students (as future managers and individual investors) should learn about the FTSE 100 index. The FTSE 100 index is a key benchmark for the Japanese equity market, which is one of the world’s largest market. Understanding how the index is constructed, how it performs, and the companies that make up the index is important for anyone studying finance or business in Japan or interested in investing in Japanese equities.

Individual investors can assess the performance of their own investments in the Japanese equity market with the FTSE 100 index. Last but not least, a lot of asset management firms base their mutual funds and exchange-traded funds (ETFs) on the FTSE 100 index which can considered as interesting assets to diversify a portfolio. Learning about these products and their portfolio and risk management applications can be valuable for management students.

Related posts on the SimTrade blog

About financial indexes

   ▶ Nithisha CHALLA Financial indexes

   ▶ Nithisha CHALLA Calculation of financial indexes

   ▶ Nithisha CHALLA The business of financial indexes

   ▶ Nithisha CHALLA Float

Other financial indexes

   ▶ Nithisha CHALLA The S&P 500 index

   ▶ Nithisha CHALLA The CSI 300 index

   ▶ Nithisha CHALLA The Nikkei 225 index

   ▶ Nithisha CHALLA The DAX 30 index

About portfolio management

   ▶ Youssef LOURAOUI Portfolio

   ▶ Jayati WALIA Returns

About statistics

   ▶ Shengyu ZHENG Moments de la distribution

   ▶ Shengyu ZHENG Mesures de risques

Useful resources

Academic research about risk

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

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

Business

Axi What is the FTSE 100 index and how to trade it?

CMC markets An introduction to the FTSE 100

Nerd Wallet What is the FTSE 100?

Data

Yahoo! Finance

Yahoo Finance FTSE 100 index

About the author

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

My experiences as Fixed Income portfolio manager then Asset Liability Manager at Banque de France

My experiences as Fixed Income portfolio manager then Asset Liability Manager at Banque de France

William ARRATA

In this article, William ARRATA (Lecturer in advanced portfolio management at ESSEC Business School Master in Finance and Master in Management since 2014) shares his professional experience as Fixed Income Portfolio Manager then Asset Liability Manager at Banque de France.

About the company

Founded in 1800 by Napoléon Bonaparte, Banque de France began as a private institution for managing state debts and issuing notes. The first Basic Statutes of the Bank were established in 1808, where the Bank’s notes in French Franc became legal tender. In 1936 the Bank was nationalized. In 1993, a reform granted the Bank independence, in order to ensure price stability, regardless of domestic politics. This reform cleared the path for the European monetary union. In 1998, the Bank became a founding member of the European System of Central Banks which groups together the European Central Bank and the National Central Banks of all countries that have adopted the Euro. On 1st January 1999, France adopted the euro. Nowadays Banque de France’s three main missions, as defined by its statuses, are to drive the French monetary strategy, ensure financial stability and provide services to households, small and medium businesses and the French state. In particular, it manages the accounts and the facilitation of payments for the Treasury and some public companies. The Bank is a sui generis public entity governed by the French Monetary and Financial Code. The conditions whereby it conducts its missions on national territory are set out in its Public Service Contract. François Villeroy de Galhau has served as Governor of the Banque de France since 1 November 2015.

Logo of Banque de France.
Logo of  Banque de France
Source: the company.

Since 2019, I work as Asset Liability Manager at the Financial Directorate of the General Secretariat of Banque de France, having previously worked from 2013 to 2019 as Fixed Income portfolio manager in the Markets Directorate of the Directorate General Financial Stability and Operations.

The Markets Directorate of Banque de France encompasses the management of foreign exchange reserves and gold, foreign exchange operations, and the provision of investment services to foreign central banks and international organizations. The Directorate is fully integrated from front office to back office and custody. It is split into five divisions and totals 120 persons, based in Paris, Poitiers, New York and Singapore.

The Financial Directorate of Banque de France encompasses the accounting of Eurosystem monetary policy operations as well as BdF’s investment operations, the costing and budgeting of expenses, management control, Asset Liability Management modeling of the Balance sheet, as well as the investment and management of BdF’s Capital and pension funds, on which the Socially Responsible Investment strategy of BdF is also enforced. It is split into five divisions and totals around 100 persons.

My jobs

From 2013 to 2019, I was Fixed Income Portfolio Manager in the Reserves Management Division of the Markets Directorate, in charge of managing foreign exchange reserves. In essence, the job consists of managing a fixed income portfolio, with the objective of consistently outperforming its benchmark through time.

Since 2019, I am an Asset Liability Manager (modeling mainly) in the Financial Management Division of the Financial Directorate. It consists of balance sheet modeling and projection through time. It is a quantitative position, which requires knowledge in stochastic calculus and programming languages. In addition, it is also a special job in the sense that the central bank balance sheet is unique in its kind such that asset and liability management (ALM) modeling at the central bank also requires understanding monetary policy operations.

My missions

My position as a Fixed Income portfolio manager in the Reserves Management Division of the Markets Directorate started in 2013. Foreign exchange reserves are held in various currencies, and each currency is actively managed against a benchmark into a specific portfolio, which is daily marked-to-market. I have been responsible for the management of one of those portfolios for 6 years. As for all portfolios, it is invested in money market instruments (reverse repos, repos, deposits, fully hedged swaps, STIR futures) on the one hand, and bonds from different types of issuers on the other hand. It also makes use of derivatives such as bond futures, rates futures, and Interest Rate Swaps. Each portfolio is managed in reference to a benchmark, around which risk limits are defined. Those risk limits give leeway to the portfolio manager to do tactical asset allocation, in order to “beat” the benchmark. Tactical allocation can take many forms.

First, the portfolio manager (p.m.) has the possibility do “time the market”, which is named after “duration position” in the Fixed-Income universe. This translates into an increase or a decrease of the differential duration (duration in excess of the benchmark) of his portfolio. A duration position is implemented when expectations from the p.m. on the interest rate path differ from what is priced in the forward curve (i.e. the p.m. expects indeed rates to “reprice” in the future according to his expectations, e.g., to move up or down). To benefit from this expected variation, the p.m. adjusts the differential duration of his portfolio. For instance, he increases the differential duration if he expects rates to go down. Such positions can also be combined. Combining a long duration position with a short duration position on two different segments of the yield curve can be a relevant investment strategy when the p.m. expects the yield curve to steepen or to flatten. This creates a spread position, referred to as “butterfly position”.

Market timing bets can be set using different techniques. This can stem from a regular central bank watching, which allows to understand the central bank “reaction function“ and to take positions in advance of other market participants. It can also be done using quantitative tools such as rates models.

The benchmark can also be beaten using security selection. This consists in substituting a bond whose price is seen as deviating from its fair value with another bond. The p.m. sells the “richer” bond and buys the “cheaper” bond. Such a strategy should not embed a duration mismatch with the benchmark, i.e., the duration of the bond sold (the bond in the benchmark) should equal the one of the bond bought. For instance, the p.m. can choose to sell a bond whose yield is deemed below its estimated fair yield (whose price is too high) and buy a bond whose yield is deemed either fairly priced or above its estimated fair yield, with identical durations for the two bonds. There are many ways to estimate bonds’ fair yield. One can employ a model such as the Nelson Siegel Svensson (NSS) model. This model proposes a parametric form for the zero coupon rate curve of a given issuer. Observed market yields can then be compared to theoretical yields, to identify “cheap” and “rich” bonds.

Such tactical positions can be held over varying horizons, usually not more than 6 months.

The p.m. can also implement some “arbitrage” strategies, for instance on the repo market, by lending “special” securities against least expensive (“General Collateral”) security (see infra). When the risk framework allows it, he can manage the short-term portion of his portfolio by taking advantage of the basis between money market rates between his currency and another currency (“cross currency basis”), when the interest rate parity is not enforced. He can then build a “synthetic” money market position made out in his portfolio’s currency, by using a FX derivative and a foreign currency money market instrument, to benefit from the higher rate of return provided by the synthetic money market rate versus the “natural” one. At last, he can also substitute the purchase of a bond on a given segment by investing in a risk-free instrument and a future on that bond, to take advantage of a deviation in the “cash and carry relationship” (see infra).

My second experience started in 2019 at the Financial Directorate, as an Asset Liability manager in charge of modeling the balance sheet of Banque de France and proposing strategies for the investment portfolios of Banque de France.
The job starts with the modeling of the different assets and liabilities of a central bank balance sheet. The central bank balance sheet is unique and requires an understanding of the dynamics of monetary policy operations, but also on the drivers of banknotes issuances, target 2 positions, accounts of non-banking clients, etc… In an unconventional monetary policy environment such as the one experienced by the Euro System since 2014, the dynamics of the balance sheet have somewhat become more complex. What is crucial in this step is to provide with a joint modeling of all elements concerned as they interact with each other in specific ways.

Another important task lies on the projection of economic and financial market through time. It relies on modeling over a long-term horizon (usually a 10-year horizon) the evolution of the financial and economic variables to which the central bank is exposed. This requires the usage of stochastic calculus and programming skills, as projections models are implemented with programming languages such as R, Python or Matlab. For instance, one can take advantage of the existence of listed options on assets such as Euribor futures, French sovereign bonds futures, fed funds futures or US Treasuries futures. By making some assumptions about the price process of those assets, it is possible to retrieve their implied distributions at given horizons (so called “risk neutral densities”). Those distributions can then be used to build a large number of scenarios (say 1000) which are applied to the modeled balance sheet, to propose a distribution of future revenues through time.

The fact that the BdF belongs to the Euro System also requires understanding the rules for sharing the monetary revenues of the 20 national central banks of the Euro System. Analytical balance sheets have to be modeled, to compute monetary revenues for each national central bank.

At last, this ALM exercise can also serve as the basis for devising optimal investment strategies for investment portfolios of Banque de France non-monetary balance sheet.

Required skills and knowledge

A fixed income portfolio manager should be skilled in money markets, fixed income securities and derivatives, portfolio management (in particular tactical allocation and performance attribution tools) and fully understand the impact of macroeconomics and monetary policy on rates markets.

An Asset Liability Manager should be skilled in fixed income securities, financial accounting, probabilities and statistics, stochastic calculus, rates models and option pricing, programming languages such as R, Python or Matlab, and monetary policy when it comes to modeling the balance sheet of a central bank.

An Asset Liability Management position in an ideal position after a Fixed Income portfolio management position. Having explored the many facets of Fixed Income and monetary policy are indeed very helpful to start an Asset Liability Management position. It is very satisfactory to develop analytical skills on the aggregate balance sheet after having worked on a specific portfolio.

What I learned

I learned a lot in all the fields I mentioned, but in particular about some topics that are not extensively covered in masters in finance’s curricula, such as money markets and monetary policy. I learned a lot about unconventional monetary policy, as it has been enriched from the recent experiences of the Fed, the ECB or the BoE, which we not in textbooks when I graduated 15 years ago. At last, as time went by I gained capacities in programming languages (especially related to quantitative finance), which is a prerequisite for ALM modeling, and a “nice to have” for fixed income portfolio management.

Financial concepts related my internship

I develop below three financial concepts related to my activities: implied repo and basis, par-par asset swap and specialness on the repo market.

Implied repo and basis

The implied repo rate is the rate of return earned by a market participant who sells a bond future contract and buys the Cheapest to Deliver (CtD) bond in the basket of bonds available for delivery at contract maturity. The implied repo rate should be compared to the effective repo rate of the CtD, and the difference between the two is referred to as the “net basis”. An arbitrage profit can be captured by combining a position on the bond future, the CtD and a reverse repo, depending on the sign of the net basis.

Par-par asset swap

It is a position that consists in purchasing a bond and entering into an interest rate swap such that the combined position is a floating rate bond valued at par. Forcing the value of the bundled position to equal par implicitly requires the fixed rate of the swap to equal the bond’s coupon rate, and as a result, the swap’s initial value will differ from zero. As the obtained synthetic floating rate bond is trading at par, its discount rate is a par rate. As such, it is not distorted anymore by the discrepancy between the bond coupon rate and its current market yield (which is at the origin of the discount/premium). Thus it is a pure measure of the ytm of the issuer on the considered maturity.

Specialness on the repo market

A reverse repurchase agreements (“reverse repo”) is a transaction whereby cash is lent on the market against collateral, usually a bond, to mitigate counterparty default risk. Such an operation falls into the many possible money market instruments available to p.m. to earn a return on the short-term portion of their portfolios.

Conversely, a repo transaction implies lending a bond against cash. The counterparty of a repo trader is a reverse repo trader.

When a reverse repo trade is initiated to lend cash, the cash lender will require from his counterparty that the collateral posted fills some characteristics (for instance, Investment Grade sovereign bonds with a residual maturity below 10 years), but he will not require a particular bond. The collateral posted by his counterparty is referred to as “General Collateral” (GC). This is why the rate of return earned on the trade is named after the GC repo rate.

But in some instances, some bonds in the market are particularly looked after (for instance, newly issued bonds in the days surrounding their auction, or the Cheapest-to-Deliver Bond of a future contract). They are usually in high demand when they have been sold short by market makers or primary dealers, and they must borrowed to be delivered to the bond buyers in due time. As those bonds have to be delivered, they cannot be substituted by another bond as would be the case for GC collateral (the repo transaction is said to be “security driven”). Thus the demand from short sellers on those bonds is inelastic to price, and they will be inclined to pay a lower rate than the GC rate to borrow them on the repo market, as they are at risk of failing to deliver otherwise. Such bonds are referred to as “special” (spec) collateral in the repo market, as opposed to the GC.

The rate on special collateral is lower than on the GC, which means that the cash leg will receive a lower remuneration when the borrowed bond is spec. Thus looking for a special bond entails a cost for the borrower. Specialness on a bond is often measured by computing the spread between the GC repo rate and the special repo rate on that bond.

Related posts on the SimTrade blog

   ▶ All posts about Professional experiences

   ▶ Youssef LOURAOUI Yield curve calibration

   ▶ Youssef LOURAOUI Fixed Income arbitrage

   ▶ Youssef LOURAOUI Portfolio Management at the Central Bank of Morocco

Useful resources

Banque de France

About the author

The article was written in May 2023 by William ARRATA (Lecturer in Advanced Portfolio Management at ESSEC Business School’s MiF and MiM and Asset Liability Manager at Banque de France).

The Nikkei 225 index

The Nikkei 225 index

Nithisha CHALLA

In this article, Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management, 2021-2023) presents the Nikkei 225 index and details its characteristics.

The Nikkei 225 index

The Nikkei 225 index is considered as the primary benchmark index of the Tokyo Stock Exchange (TSE) and is the most widely quoted average of Japanese equities. One of Japan’s top newspapers, the Nihon Keizai Shimbun (Nikkei), first published the index in 1950. The index consists of 225 blue-chip companies listed on the TSE, which are considered to represent the overall health of the Japanese economy. These companies come from various industries such as finance, technology, automobile, and retail, among others.

The Financial Times, a preeminent global provider of financial news, was purchased by Nikkei Inc, the parent company of Nikkei, for $1.3 billion in 2015. This acquisition highlighted Nikkei’s growing global presence and ambition to diversify beyond the Japanese market. The Nikkei 225 index follows a price-weighted methodology. This means that the components of the index are weighted based on their stock price, with higher-priced stocks carrying a greater weight in the index.

In the past few years, the Nikkei 225 index has been affected by various economic and political events, such as the COVID-19 pandemic and the Tokyo Olympics. The pandemic caused the index to significantly decline in 2020, but it has since recovered and reached new highs in 2021.

How is the Nikkei 225 index represented in trading platforms and financial websites? The ticker symbol used in the financial industry for the Nikkei 225 index is “NI225”.

Table 1 below gives the Top 10 stocks in the Nikkei 225 index in terms of market capitalization as of January 31, 2023.

Table 1. Top 10 stocks in the Nikkei index.
Top 10 stocks in the Nikkei 225 index
Source: computation by the author (data: YahooFinance! financial website).

Table 2 below gives the sector representation of the Nikkei 225 index in terms of number of stocks and market capitalization as of January 31, 2023.

Table 2. Sector representation in the Nikkei 225 index.
Sector representation in the Nikkei 225 index
Source: computation by the author (data: YahooFinance! financial website).

Calculation of the Nikkei 225 index value

The Nikkei 225 index is calculated using a price-weighted methodology. This means that the price of each stock in the index is multiplied by the number of shares outstanding to determine the total market value of the company. The Nikkei 225 index is frequently used as a leading indicator of the state of the Japanese stock market, and economy, and as a gauge of trends in the world economy.

The formula to compute the Nikkei 225 is given by

A price-weighted index is calculated by summing the prices of all the assets in the index and dividing by a divisor equal to the number of assets.

The formula for a price-weighted index is given by

Price-weighted index value

where I is the index value, k a given asset, K the number of assets in the index, Pk the market price of asset k, and t the time of calculation of the index.

In a price-weighted index, the weight of asset k is given by formula can be rewritten as

Price-weighted index weight

which clearly shows that the weight of each asset in the index is its market price divided by the sum of the market prices of all assets.

Note that the divisor, which is equal to the number of shares, is typically adjusted for events such as stock splits and dividends. The divisor is used to ensure that the value of the index remains consistent over time despite changes in the number of outstanding shares. A more general formula may then be:

Index value

Where D is the divisor which is adjusted over time to account for events such as stock splits and dividends.

Use of the Nikkei 225 index in asset management

Asset managers have shifted their attention in recent years to including environmental, social, and governance (ESG) factors in their investment choices. A number of ESG-related initiatives, such as the development of an ESG index that tracks businesses with high ESG scores, have been introduced by the Nikkei 225 index. The Nikkei 225 index may also be used by asset managers as a component of a more comprehensive global asset allocation strategy. For example, they may use the index to gain exposure to the Asian equity markets while also investing in other regions such as Europe and the Americas. In addition, the Nikkei 225 index can also be used as a risk management tool. Asset managers can spot potential risks and take action to reduce them by comparing a portfolio’s performance to the index.

Benchmark for equity funds

Equity funds that invest in Japanese stocks frequently use the Nikkei 225 index as a benchmark. The index is used by investment managers and individual investors to assess and contrast the performance of their holdings of Japanese equities with the performance of the overall market. Japanese exchange-traded funds (ETFs) and other investment products that follow the Japanese equity market use the index as a benchmark as well. Additionally, derivatives like futures and options that enable investors to trade on the Japanese equity market are based on the Nikkei 225 index.

Financial products around the Nikkei 225 index

There are several financial products that track the performance of the Nikkei 225 index, allowing investors to gain exposure to the Japanese stock market.

  • Nikkei 225 ETFs are a popular way for investors to gain exposure to the Japanese equity market, as they offer a low-cost and convenient way to invest in a diversified basket of stocks. Some of the largest Nikkei 225 ETFs by assets under management include the iShares Nikkei 225 ETF (NKY), the Nomura Nikkei 225 ETF (1321), and the Daiwa ETF Nikkei 225 (1320).
  • There are also mutual funds and index funds that track the Nikkei 225 index. These funds typically have higher fees than ETFs but may offer different investment strategies or options for investors.
  • Certificates are structured products that allow investors to gain exposure to the Nikkei 225 index without actually owning the underlying assets.
  • Futures contracts based on the Nikkei 225 index are also available for investors who want to trade the index with leverage or for hedging purposes. These futures contracts trade on the Osaka Exchange, a subsidiary of the Japan Exchange Group.

Historical data for the Nikkei 225 index

How to get the data?

The Nikkei 225 index is the most common index used in finance, and historical data for the Nikkei 225 index can be easily downloaded from the internet.

For example, you can download data for the Nikkei 225 index from March 1, 1990 on Yahoo! Finance (the Yahoo! code for Nikkei 225 index is ^N225).

Yahoo! Finance
Source: Yahoo! Finance.

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

R program

The R program below written by Shengyu ZHENG allows you to download the data from Yahoo! Finance website and to compute summary statistics and risk measures about the Nikkei 225 index.

Download R file

Data file

The R program that you can download above allows you to download the data for the Nikkei 225 index from the Yahoo! Finance website. The database starts on March 1, 1990. It also computes the returns (logarithmic returns) from closing prices.

Table 3 below represents the top of the data file for the Nikkei 225 index downloaded from the Yahoo! Finance website with the R program.

Table 3. Top of the data file for the Nikkei 225 index.
Top of the file for the Nikkei 225 index data
Source: computation by the author (data: Yahoo! Finance website).

Evolution of the Nikkei 225 index

Figure 1 below gives the evolution of the Nikkei 225 index from March 1, 1990 to December 30, 2022 on a daily basis.

Figure 1. Evolution of the Nikkei 225 index.
Evolution of the Nikkei 225 index
Source: computation by the author (data: Yahoo! Finance website).

Figure 2 below gives the evolution of the Nikkei 225 index returns from March 1, 1990 to December 30, 2022 on a daily basis.

Figure 2. Evolution of the Nikkei 225 index returns.
Evolution of the Nikkei 225 index return
Source: computation by the author (data: Yahoo! Finance website).

Summary statistics for the Nikkei 225 index

The R program that you can download above also allows you to compute summary statistics about the returns of the Nikkei 225 index.

Table 4 below presents the following summary statistics estimated for the Nikkei 225 index:

  • The mean
  • The standard deviation (the squared root of the variance)
  • The skewness
  • The kurtosis.

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

Table 4. Summary statistics for the Nikkei 225 index.
Summary statistics for the Nikkei 225 index
Source: computation by the author (data: Yahoo! Finance website).

Statistical distribution of the Nikkei 225 index returns

Historical distribution

Figure 3 represents the historical distribution of the Nikkei 225 index daily returns for the period from March 1, 1990 to December 30, 2022.

Figure 3. Historical distribution of the Nikkei 225 index returns.
Historical distribution of the daily Nikkei 225 index returns
Source: computation by the author (data: Yahoo! Finance website).

Gaussian distribution

The Gaussian distribution (also called the normal distribution) is a parametric distribution with two parameters: the mean and the standard deviation of returns. We estimated these two parameters over the period from March 1, 1990 to December 30, 2022. The mean of daily returns is equal to 0.02% and the standard deviation of daily returns is equal to 1.37% (or equivalently 3.94% for the annual mean and 28.02% for the annual standard deviation as shown in Table 3 above).

Figure 4 below represents the Gaussian distribution of the Nikkei 225 index daily returns with parameters estimated over the period from March 1, 1990 to December 30, 2022.

Figure 4. Gaussian distribution of the Nikkei 225 index returns.
Gaussian distribution of the daily Nikkei 225 index returns
Source: computation by the author (data: Yahoo! Finance website).

Risk measures of the Nikkei 225 index returns

The R program that you can download above also allows you to compute risk measures about the returns of the Nikkei 225 index.

Table 5 below presents the following risk measures estimated for the Nikkei 225 index:

  • The long-term volatility (the unconditional standard deviation estimated over the entire period)
  • The short-term volatility (the standard deviation estimated over the last three months)
  • The Value at Risk (VaR) for the left tail (the 5% quantile of the historical distribution)
  • The Value at Risk (VaR) for the right tail (the 95% quantile of the historical distribution)
  • The Expected Shortfall (ES) for the left tail (the average loss over the 5% quantile of the historical distribution)
  • The Expected Shortfall (ES) for the right tail (the average loss over the 95% quantile of the historical distribution)
  • The Stress Value (SV) for the left tail (the 1% quantile of the tail distribution estimated with a Generalized Pareto distribution)
  • The Stress Value (SV) for the right tail (the 99% quantile of the tail distribution estimated with a Generalized Pareto distribution)

Table 5. Risk measures for the Nikkei 225 index.
Risk measures for the Nikkei 225 index
Source: computation by the author (data: Yahoo! Finance website).

The volatility is a global measure of risk as it considers all the returns. The Value at Risk (VaR), Expected Shortfall (ES) and Stress Value (SV) are local measures of risk as they focus on the tails of the distribution. The study of the left tail is relevant for an investor holding a long position in the Nikkei 225 index while the study of the right tail is relevant for an investor holding a short position in the Nikkei 225 index.

Financial maps

You can find financial world maps on the Extreme Events in Finance website. These maps represent the performance, risk and extreme risk in international equity markets.

Figure 5 below represents the world map for extreme risk estimated by the extreme value distribution (see Longin (2016 and 2000)).

Figure 5. Extreme risk map.
Extreme risk map
Source: Extreme Events in Finance.

Why should I be interested in this post?

For a number of reasons, management students (as future managers and individual investors) should learn about the Nikkei 225 index. The Nikkei 225 index is a key benchmark for the Japanese equity market, which is one of the world’s largest market. Understanding how the index is constructed, how it performs, and the companies that make up the index is important for anyone studying finance or business in Japan or interested in investing in Japanese equities.

Individual investors can assess the performance of their own investments in the Japanese equity market with the Nikkei 225 index. Last but not least, a lot of asset management firms base their mutual funds and exchange-traded funds (ETFs) on the Nikkei 225 index which can considered as interesting assets to diversify a portfolio. Learning about these products and their portfolio and risk management applications can be valuable for management students.

Related posts on the SimTrade blog

About financial indexes

   ▶ Nithisha CHALLA Financial indexes

   ▶ Nithisha CHALLA Calculation of financial indexes

   ▶ Nithisha CHALLA The business of financial indexes

   ▶ Nithisha CHALLA Float

Other financial indexes

   ▶ Nithisha CHALLA The S&P 500 index

   ▶ Nithisha CHALLA The FTSE 100 index

   ▶ Nithisha CHALLA The CSI 300 index

   ▶ Nithisha CHALLA The KOSPI 50 index

About portfolio management

   ▶ Youssef LOURAOUI Portfolio

   ▶ Jayati WALIA Returns

About statistics

   ▶ Shengyu ZHENG Moments de la distribution

   ▶ Shengyu ZHENG Mesures de risques

Useful resources

Academic research about risk

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

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

Data

Yahoo! Finance

Yahoo! Finance Nikkei 225 index

Other

Extreme Events in Finance

Extreme Events in Finance Risk maps

Wikipedia Nikkei 225

About the author

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

The CAC 40 index

The CAC 40 index

Nithisha CHALLA

In this article, Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management, 2021-2023) presents the CAC 40 index and details its characteristics.

The CAC 40 index

The CAC 40 index is one of the main indices of the Paris Bourse. It was launched on December 31, 1987. CAC is the abbreviation for Cotation Assistée en Continu which translates to “Continuous Assisted Quotation”. CAC 40 is a benchmark stock market index that tracks the performance of the 40 largest and most actively traded companies on the Euronext Paris exchange.

The companies in the CAC 40 index represent a variety of industries, including financial services, energy, consumer goods, and technology. Some of the largest and most well-known companies in the index include Total, L’Oréal, and Sanofi. Due to its extremely diverse portfolio, it enables investors to view a variety of French industries.

The CAC 40 index uses a free-float market-capitalization weighting methodology, which means that only the shares that are available for trading are used to determine the index’s weighting.

Given that France is the second-largest economy in the European Union (EU), and the CAC 40 index plays an important role in the French economy, it is a good benchmark for investors. The companies included in the index account for a significant portion of the country’s GDP and provide employment for a large number of people.

While the CAC 40 is a French stock market index, many of the companies included in the index have a global reach and operate in multiple countries. As a result, the index can serve as a gauge for the wider European and global economies in addition to the French economy.

How is the CAC 40 index represented in trading platforms and financial websites? The ticker symbol used in the financial industry for the CAC 40 index is “PX1”.

Table 1 gives the Top 10 stocks in the CAC 40 index in terms of market capitalization as of January 31, 2023.

Table 1. Top 10 stocks in the CAC 40 index.
Top 10 stocks in the CAC 40 index
Source: computation by the author (data: YahooFinance! financial website).

Table 2 gives the sector representation of the CAC 40 index in terms of number of stocks and market capitalization as of January 31, 2023.

Table 2. Sector representation in the CAC 40 index.
Sector representation in the CAC 40 index
Source: computation by the author (data: YahooFinance! financial website).

Calculation of the CAC 40 index value

The value of the CAC 40 index is determined using a market-capitalization-weighted formula that is float-adjusted, which means that only the shares that are available for trading in the secondary market are used to determine the index weighting. This helps to ensure that the index is representative of the companies that are actively traded in the market.

The formula to compute the CAC 40 index is given by

Float Adjusted Market Capitalization Index value

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

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

Float Adjusted Market Capitalization Weighted Index Weight

The index is reviewed quarterly to ensure that it remains representative of the French stock market and to add or remove companies based on their size, liquidity, and sector classification.

Use of the CAC 40 index in asset management

The CAC 40 index is a useful tool for asset managers to manage risk because it is quite diverse and represents the French economy across a variety of industries. While the CAC 40 index is primarily composed of French companies, many of these companies also have significant international exposure. The CAC 40 index is one of Europe’s most liquid stock market indices, with a high level of trading volume and relatively low bid-ask spreads. This can be particularly important for investors who are looking to trade in and out of positions quickly, or for those who are managing large portfolios and need to execute trades efficiently. Some index funds and ETFs based on the CAC 40 index have particular ESG standards for the businesses they invest in. This may be appealing to investors who want to match their investments with their values.

Benchmark for equity funds

Equity funds are types of investment funds that invest primarily in stocks or shares of companies that are publicly traded. These funds give investors exposure to equity markets and offer the potential growth for capital appreciation in the long term. Given that it gives a good enough picture of the French market, there are multiple financial products around the index. Using these products can help investors diversify their holdings and control risk. The CAC 40 index can also be used to create multi-asset portfolios, acting as a representative of the portfolio’s equity component. By including the CAC 40 index in a multi-asset portfolio, investors can potentially achieve diversification and reduce risk through exposure to a broad range of companies in the French economy.

Financial products around the CAC 40 index

Financial products around the CAC 40 index offer investors a range of options to gain exposure to the French equity market, including products with sustainability and ESG considerations.

  • Investment funds traded like stocks are called exchange-traded funds, or ETFs. The Lyxor ETF CAC 40 is the largest ETF that tracks the CAC 40 index, and other ETFs that do so include the Amundi ETF CAC 40, the BNP Paribas Easy CAC 40, and the Xtrackers CAC 40
  • Some mutual funds and investment trusts that make CAC 40 index investments have an environmental, social, and governance (ESG) or sustainability focus. For instance, the CAC 40 index and European businesses with strong ESG performance are among the investments made by the Mirova Europe Sustainable Equity Fund
  • The main stock exchange in France, Euronext Paris, offers futures and options on the CAC 40 index. Institutional investors and traders use these highly liquid financial contracts
  • Structured products linked to the CAC 40 index can have various features, such as capital protection, leverage, and participation rate

Historical data for the CAC 40 index

How to get the data?

The CAC 40 index is the most common index used in finance, and historical data for the CAC 40 index can be easily downloaded from the internet.

For example, you can download data for the CAC 40 index from March 1, 1990 on Yahoo! Finance (the Yahoo! code for CAC 40 index is ^FCHI).

Yahoo! Finance
Source: Yahoo! Finance.

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

R program

The R program below written by Shengyu ZHENG allows you to download the data from Yahoo! Finance website and to compute summary statistics and risk measures about the CAC 40 index.

Download R file

Data file

The R program that you can download above allows you to download the data for the CAC 40 index from the Yahoo! Finance website. The database starts on March 1, 1990. It also computes the returns (logarithmic returns) from closing prices.

Table 3 below represents the top of the data file for the CAC 40 index downloaded from the Yahoo! Finance website with the R program.

Table 3. Top of the data file for the CAC 40 index.
Top of the file for the CAC 40 index data
Source: computation by the author (data: Yahoo! Finance website).

Evolution of the CAC 40 index

Figure 1 below gives the evolution of the CAC 40 index from March 1, 1990 to December 30, 2022 on a daily basis.

Figure 1. Evolution of the CAC 40 index.
Evolution of the CAC 40 index
Source: computation by the author (data: Yahoo! Finance website).

Figure 2 below gives the evolution of the CAC 40 index returns from March 1, 1990 to December 30, 2022 on a daily basis.

Figure 2. Evolution of the CAC 40 index returns.
Evolution of the CAC 40 index return
Source: computation by the author (data: Yahoo! Finance website).

Summary statistics for the CAC 40 index

The R program that you can download above also allows you to compute summary statistics about the returns of the CAC 40 index.

Table 4 below presents the following summary statistics estimated for the CAC 40 index:

  • The mean
  • The standard deviation (the squared root of the variance)
  • The skewness
  • The kurtosis.

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

Table 4. Summary statistics for the CAC 40 index.
Summary statistics for the CAC 40 index
Source: computation by the author (data: Yahoo! Finance website).

Statistical distribution of the CAC 40 index returns

Historical distribution

Figure 3 represents the historical distribution of the CAC 40 index daily returns for the period from March 1, 1990 to December 30, 2022.

Figure 3. Historical distribution of the CAC 40 index returns.
Historical distribution of the daily CAC 40 index returns
Source: computation by the author (data: Yahoo! Finance website).

Gaussian distribution

The Gaussian distribution (also called the normal distribution) is a parametric distribution with two parameters: the mean and the standard deviation of returns. We estimated these two parameters over the period from March 1, 1990 to December 30, 2022. The mean of daily returns is equal to 0.02% and the standard deviation of daily returns is equal to 1.37% (or equivalently 3.94% for the annual mean and 28.02% for the annual standard deviation as shown in Table 3 above).

Figure 4 below represents the Gaussian distribution of the CAC 40 index daily returns with parameters estimated over the period from March 1, 1990 to December 30, 2022.

Figure 4. Gaussian distribution of the CAC 40 index returns.
Gaussian distribution of the daily CAC 40 index returns
Source: computation by the author (data: Yahoo! Finance website).

Risk measures of the CAC 40 index returns

The R program that you can download above also allows you to compute risk measures about the returns of the CAC 40 index.

Table 5 below presents the following risk measures estimated for the CAC 40 index:

  • The long-term volatility (the unconditional standard deviation estimated over the entire period)
  • The short-term volatility (the standard deviation estimated over the last three months)
  • The Value at Risk (VaR) for the left tail (the 5% quantile of the historical distribution)
  • The Value at Risk (VaR) for the right tail (the 95% quantile of the historical distribution)
  • The Expected Shortfall (ES) for the left tail (the average loss over the 5% quantile of the historical distribution)
  • The Expected Shortfall (ES) for the right tail (the average loss over the 95% quantile of the historical distribution)
  • The Stress Value (SV) for the left tail (the 1% quantile of the tail distribution estimated with a Generalized Pareto distribution)
  • The Stress Value (SV) for the right tail (the 99% quantile of the tail distribution estimated with a Generalized Pareto distribution)

Table 5. Risk measures for the CAC 40 index.
Risk measures for the CAC 40 index
Source: computation by the author (data: Yahoo! Finance website).

The volatility is a global measure of risk as it considers all the returns. The Value at Risk (VaR), Expected Shortfall (ES) and Stress Value (SV) are local measures of risk as they focus on the tails of the distribution. The study of the left tail is relevant for an investor holding a long position in the CAC 40 index while the study of the right tail is relevant for an investor holding a short position in the CAC 40 index.

Why should I be interested in this post?

For a number of reasons, management students (as future managers and individual investors) should learn about the CAC 40 index. The performance of large-cap listed French companies is tracked by this stock market index, which is first and foremost well-known and respected. Gaining a deeper understanding of the French large-cap stock market and the businesses that fuel its expansion requires knowledge of the CAC 40 index.

Individual investors can assess the performance of their own investments and those of their organization by comprehending the CAC 40 index and its components. Last but not least, a lot of businesses base their mutual funds and exchange-traded funds (ETFs) on the CAC 40 index which can considered as interesting assets to diversify a portfolio.

Related posts on the SimTrade blog

About financial indexes

   ▶ Nithisha CHALLA Financial indexes

   ▶ Nithisha CHALLA Calculation of financial indexes

   ▶ Nithisha CHALLA The business of financial indexes

   ▶ Nithisha CHALLA Float

Other financial indexes

   ▶ Nithisha CHALLA The S&P 500 index

   ▶ Nithisha CHALLA The FTSE 100 index

   ▶ Nithisha CHALLA The CSI 300 index

   ▶ Nithisha CHALLA The Nikkei 225 index

   ▶ Nithisha CHALLA The DAX 30 index

About portfolio management

   ▶ Youssef LOURAOUI Portfolio

   ▶ Jayati WALIA Returns

About statistics

   ▶ Shengyu ZHENG Moments de la distribution

   ▶ Shengyu ZHENG Mesures de risques

Useful resources

Academic research about risk

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

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

Other

Wikipedia CAC 40

FXCM Everything you need to know about the CAC 40 index

EFMAE The introduction of CAC40 Master unit

Data

Yahoo! Finance

Yahoo Finance CAC 40 index

About the author

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

Knowledge is power

Knowledge is power!

Jayna MELWANI

In this article, Jayna MELWANI (ESSEC Business School, Global BBA, 2019-2023) comments on a quote by Benjamin Franklin about the power of knowledge in finance.

“An investment in knowledge pays the best interest.” – Benjamin Franklin

Analysis of the quote

The quote suggests that investing in knowledge and education can be one of the most profitable investments a person can make. This is because knowledge and skills are assets that can appreciate over time, leading to greater personal and professional success. When people invest in themselves through education and self-improvement, they can develop skills and knowledge that can lead to better job opportunities, higher salaries, and more fulfilling careers. Additionally, by staying informed and up-to-date on trends and developments in their field, they can position themselves to be more successful over the long term.

In the context of personal finance, the quote implies that investing in one’s own education and skills can be more valuable than simply focusing on accumulating wealth through savings or investments. While it is important to save and invest wisely, the returns on those investments may be limited without the skills and knowledge needed to identify opportunities and make informed decisions.

About the author of the quote

Benjamin Franklin is one of the founding fathers of the United States and a prominent inventor, writer, and statesman.

Financial concepts related to the quote

The financial concepts related to this quote include the following:

Return on investment (ROI)

ROI refers to the amount of profit or benefit earned on an investment relative to the cost of the investment. In the context of the quote, the ROI on investing in knowledge is believed to be high, as the benefits of knowledge can be long-lasting and contribute to personal and professional success over time.

Time Value of Money

The time value of money refers to the idea that money received in the future is worth less than money received today due to the effects of inflation and the opportunity cost of not being able to invest that money today. Investing in knowledge can provide a long-term return on investment that can increase in value over time, potentially providing a higher return than other types of investments.

Risk and Return

The concept of risk and return refers to the idea that higher risk investments typically offer higher potential returns, while lower risk investments typically offer lower potential returns. Investing in knowledge can be considered a low-risk investment with potentially high returns, as knowledge gained can help individuals make better financial decisions, potentially leading to higher financial rewards in the long term.

Human Capital

Human capital refers to the skills, knowledge, and abilities that individuals possess that can increase their value in the job market and contribute to their earning potential. Investing in knowledge can increase an individual’s human capital, leading to higher income and financial stability in the long term.

Opportunity cost

Opportunity cost refers to the cost of choosing one option over another, including the potential benefits of the option that was not chosen. Investing in knowledge may require a time and financial investment, but the potential benefits of increased knowledge and skills can outweigh the opportunity cost of not investing in oneself.

Compound interest

Compound interest refers to the interest earned on both the principal and the accumulated interest from previous periods. Investing in knowledge can provide a similar effect, as the knowledge gained can be applied over time to further increase one’s earning potential and financial success.

Overall, the financial concepts related to the quote emphasize the value of investing in oneself through education and self-improvement. Just as investing in financial assets can yield returns, investing in knowledge can yield returns in the form of personal and professional growth, which can lead to increased financial stability and success.

My opinion about this quote

In my opinion, this quote highlights the importance of continuous learning and self-improvement as a means to achieve greater success and financial security. I believe that anyone can take your money from you, but no one can take your education away from you.

Why should I be interested in this post?

Business students and students in general are advised to make the most of their education and in fact, continue to educate themselves as having a good education can provide a solid foundation for future success.

Related posts on the SimTrade blog

   ▶ All posts about Quotes

   ▶ Pranay KUMAR Time is money

   ▶ Fatimata KANE Money is a terrible master but an excellent servant

   ▶ Federico MARTINETTO Money never sleeps

Useful resources

SimTrade course Discover SimTrade

About the author

The article was written in April 2023 by Jayna MELWANI (ESSEC Business School, Global BBA, 2019-2023).

My professional experience as a Global Development and Learning Intern at Danone

My professional experience as a Global Development and Learning Intern at Danone

Jayna MELWANI

In this article, Jayna MELWANI (ESSEC Business School, Global BBA, 2019-2023) shares her professional experience as a Global Development and Learning Intern at Danone, the world’s leading food company.

About Danone

Danone is a multinational food and beverage corporation that is headquartered in Paris, France. The company produces a wide range of dairy products, water and plant-based food and beverages. Some of the most popular brands owned by Danone include Activia, Evian, Actimel and Danette.

Danone operates in over 120 countries and has more than 100,000 employees worldwide. The company’s mission is to provide health-focused food and beverage products that contribute to the well-being of individuals and the environment.

In addition to its commercial activities, Danone is also committed to promoting sustainable practices and social responsibility. The company has made significant investments in sustainability initiatives such as reducing greenhouse gas emissions, improving water usage efficiency and investing in regenerative agriculture.

Danone is a leading food and beverage company with a strong commitment to health and sustainability. Its portfolio of popular brands and global reach make it a major player in the industry.

Logo of Danone.
Logo of Danone
Source: the company.

The Global Learning Team at Danone

I was part of the Global Learning team at Danone in its headquarters in Paris. It is a team of approximately 15 people who are responsible for launching and maximizing the global learning agenda for the various functions such as Sales & Marketing, Research & Innovation, IT & Data, etc. I was in charge of supporting the global learning agenda for General Secretary, IT & Data and Sustainability.

The global learning and development team at Danone is responsible for creating and implementing programs to support the professional development of employees throughout the company. The team’s mission is to provide employees with the knowledge and skills they need to excel in their roles, grow within the organization and contribute to the company’s overall success.

Some of the key responsibilities of the learning and development team at Danone include:

  • Developing training programs: The team designs training programs that are tailored to the specific needs of different departments and job functions. They can be on-the-job training, e-learning modules, and workshops. For example, I worked closely with the General Secretary team to develop Compliance e-learning modules to be done by all employees worldwide.
  • Managing learning technologies: The team is responsible for managing the learning management system (LMS) used by the company. This includes maintaining the system, monitoring its effectiveness and ensuring that employees have access to the resources they need.

My Experience at Danone

During my internship at Danone, my missions were to support the global learning agenda for the following functions: IT & Data, and General Secretary & Sustainability. My main responsibilities were supporting the implementation of the learning portfolio, liaising with local learning teams to ensure the proper local deployment of the learning activities, measuring and reporting worldwide completion, managing suppliers, and contracts with external learning providers.

It was a 6-month internship that went by very quickly. My day-to-day responsibilities were mainly dealing with the LMS and building reports and dashboards for stakeholders. Though, I was also leading a number of global projects at the same time. One notable project I led was the Compliance campaign. Danone trains its employees worldwide every year on compliance as part of its compliance obligations with external auditors. I led the communications, reporting and stakeholder engagement for this project.

I was also responsible for negotiating deals with external learning providers for upcoming projects. Because of this, I was able to negotiate prices, measuring costs and opportunity costs of learning initiatives.

What I learned during my internship

The main things I learned during my internship at Danone are:

  • I learned how to create powerful AI dashboards to analyze raw reporting data and quickly turn them into insightful analysis.
  • I gained many soft skills such as stakeholder management, interpersonal communication, and negotiation skills.
  • I discovered my passion for health and sustainability and my love for the food and beverage industry.
  • I learned about HR digitalization through innovative technology such as digital onboarding and people analytics.

Financial concepts related my internship

Return on investment (ROI)

ROI is a financial metric that measures the profitability of an investment. In the context of my internship, ROI was used to evaluate the effectiveness of training programs and other development initiatives.

Opportunity Cost

Opportunity cost is the cost of forgoing one option in favor of another. In the context of my internship, the learning team must consider the opportunity cost of investing in employee development vs other potential investments.

Cost-benefit analysis

Cost-benefit analysis is a financial tool that compares the costs and benefits of different options. In the context of learning and development, the learning team can use cost-benefit analysis to evaluate the potential return on investment of different training and development programs. By comparing the costs, the team can make informed decisions about which initiatives to prioritize.

Related posts on the SimTrade blog

   ▶ All posts about Professional experiences

   ▶ Alexandre VERLET Classic brain teasers from real-life interviews

Useful resources

Danone

About the author

The article was written in April 2023 by Jayna MELWANI (ESSEC Business School, Global BBA, 2019-2023).

The impact of market orders on market liquidity

The impact of market orders on market liquidity

Jayna MELWANI

In this article, Jayna MELWANI (ESSEC Business School, Global BBA, 2019-2023) explains about the financial concept of market liquidity and specifically the impact of market orders on market liquidity.

What is a market order?

A market order is a type of order used in trading that instructs the broker to buy or sell a security immediately at the prevailing market price. Market orders are used when the trader wants to execute the trade quickly and does not want to wait for a specific price.

What is market liquidity and how do market orders affect it?

The impact of a market order on market liquidity can be significant. Market liquidity refers to the ability of traders to buy and sell securities quickly and easily without causing significant changes in the price. When a large number of market orders are executed, it can impact the liquidity of the market by causing sharp changes in the supply and demand for the securities being traded.

For example, if a large number of market orders are executed to sell a particular stock, it can result an increase in supply of the stock in the market, which can cause the price to drop significantly. Similarly, if a large number of market orders are executed to buy a particular stock, it can result in an increase in demand for the stock, which can cause the price to rise sharply.

In addition to impacting the price of the security being traded, market orders can also impact the liquidity of the market as a whole. When market orders are executed, it can cause sudden changes in the supply and demand for securities, which can impact the ability of other traders to buy or sell securities at favorable prices. This can make it more difficult for traders to execute their trades quickly and efficiently, which can reduce overall market liquidity.

Overall, the impact of a market order on market liquidity depends on several factors, including the size of the order, the liquidity of the security being traded, and the overall market conditions. Traders who use market orders should be aware of the potential impact on market liquidity and consider using other types of orders, such as limit orders or stop orders, to minimize the impact of their trades on the market. By doing so, traders can help to ensure that the market remains liquid and efficient, which benefits all market participants.

Why should I be interested in this post?

Understanding market liquidity is important for making informed investment decisions. As business school students, understanding market liquidity can help to make more informed decisions as assets with high liquidity are generally easier to buy and sell quickly and at a fair price.

By understanding market liquidity, students can gain insight into how financial markets work and how liquidity affects asset prices. This knowledge can help students better analyze market trends, predict market movements and make informed investment decisions.

Furthermore, for students pursuing a career in finance, understanding market liquidity can be a valuable asset. Financial institutions and investment firms value employees who possess a deep understanding of market dynamics, including market liquidity.

Related posts on the SimTrade blog

▶ Federico DE ROSSI Understanding the Order Book: How It Impacts Trading

▶ Lokendra RATHORE Good-til-Cancelled (GTC) order and Immediate-or-Cancel (IOC) order

▶ Clara PINTO High-frequency trading and limit orders

Useful resources

SimTrade course Trade orders

About the author

The article was written in April 2023 by Jayna MELWANI (ESSEC Business School, Global BBA, 2019-2023).

The Wilshire 5000 index

The Wilshire 5000 index

Nithisha CHALLA

In this article, Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management, 2021-2023) presents the Wilshire 5000 index and details its characteristics.

The Wilshire 5000 index

The Wilshire 5000 index was launched in 1974 by Wilshire Associates, an investment management company based in California. It monitors the performance of almost all publicly traded stocks in the US. This index is still currently managed by Wilshire Associates. The index name came from the fact that it initially contained about 5,000 U.S. stocks; however, it has since grown to include over 3,500 more stocks, bringing the total to close to 8,500 stocks, which more or less comprehensively represents the majority of the US equity market.

The Wilshire 5000 index is a float-adjusted, market-capitalization weighted index. As a result, rather than using the total number of shares outstanding, the index weights of each stock are changed to reflect the number of shares that are currently trading on the market. This makes it possible for the index to accurately reflect each company’s market capitalization rather than just the theoretical value of all outstanding shares.

The Wilshire 5000 index is distinctive in that it includes small- and mid-cap stocks in addition to large-cap stocks. This distinguishes it from other well-known indices like the S&P 500 or the Dow Jones Industrial Average, which only include large-cap stocks, as a more complete indicator of the American stock market. With a few exceptions, such as penny stocks and stocks that trade on over-the-counter markets, the index was created to include almost all publicly traded stocks in the US equity market.

How is the Wilshire 5000 index represented in trading platforms and financial websites? The ticker symbol used in the financial industry for the Wilshire 5000 index is “W5000”.

Table 1 below gives the Top 10 stocks in the Wilshire 5000 index in terms of market capitalization as of January 31, 2023.

Table 1. Top 10 stocks in the Wilshire 5000 index.
Top 10 stocks in the Wilshire 5000 index
Source: computation by the author (data: Yahoo! Finance website).

Table 2 below gives the sector representation of the Wilshire 5000 index in terms of number of stocks and market capitalization as of January 31, 2023.

Table 2. Sector representation in the Wilshire 5000 index.
Sector representation in the Wilshire 5000 index
Source: computation by the author (data: Yahoo! Finance website).

Calculation of the Wilshire 5000 index value

The Wilshire 5000 index is determined using a market-capitalization-weighted formula that is float-adjusted, which means that only the shares that are available for trading in the secondary market are used to determine the index weighting. This helps to ensure that the index is representative of the companies that are actively traded in the market.

The formula to compute the Wilshire 5000 is given by

Float-adjusted market-capitalization-weighted index value

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

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

Float-adjusted market-capitalization-weighted index weight

To make sure the index remains a reliable representation of the US equity market, it is rebalanced every quarter. The stocks that are chosen for inclusion in the index are chosen by Wilshire Associates, the index’s creator. When deciding which stocks to include, the company takes into account a variety of variables, including market capitalization, liquidity, and additional fundamentals like earnings and revenue growth.

Use of the Wilshire 5000 index in asset management

By comparing the volatility of their portfolio to the market as a whole, asset managers can use the Wilshire 5000 index to manage portfolio risk. Asset managers can use the index to determine the best-performing industries and sectors before choosing specific stocks to build a portfolio that is well-balanced. They can determine whether their portfolio is more or less risky than the market by examining the correlation between their portfolio and the Wilshire 5000 index. This enables them to establish whether their superior performance is the result of their ability to select stocks or whether it is simply the result of taking on greater risk than the market.

The Wilshire 5000 index is also used in various types of investment strategies, such as sector rotation and tactical asset allocation. These strategies entail using the index to find investment opportunities in particular industries or to make tactical asset class switches based on market performance.

Benchmark for equity funds

The Wilshire 5000 index is commonly used as a benchmark for equity funds because it represents a broad measure of the US equity market. It is often used by investment managers as a tool for asset allocation and performance evaluation. The Wilshire 5000 index is further divided into a number of sub-indices according to market capitalization, style, and sector. With the help of these sub-indices, investors can monitor the performance of particular sectors of the US stock market and design investment plans that are unique to their needs.

Academic studies frequently use the Wilshire 5000 index to examine US equity market behavior and test theories regarding the effectiveness and predictability of stock prices. In financial and economic modeling, it is frequently used as a benchmark.

Financial products around the Wilshire 5000 index

A number of financial products, including mutual funds, exchange-traded funds (ETFs), and index funds, use the Wilshire 5000 index as a benchmark. These products use investments in a diverse portfolio of the underlying securities to track the performance of the index.

  • The Vanguard Total Stock Market Index Fund, which invests in all of the securities in the Wilshire 5000 index in the same proportion as the index and aims to replicate the performance of the index, is one of the mutual funds that tracks the Wilshire 5000 index.
  • The SPDR Wilshire 5000 ETF is one example of an ETF that tracks the Wilshire 5000 index. ETFs can be bought and sold at any time during the trading day, just like stocks.
  • Futures contracts based on the Wilshire 5000 index are available for trading on futures exchanges. Investors can use these contracts to hedge their existing positions or make predictions about the index’s future course.
  • Index funds that follow the Wilshire 5000 index are an alternative to mutual funds and ETFs. These funds are frequently used by passive investors who want exposure to the larger U.S. equity market because they aim to closely replicate the performance of the index.

Historical data for the Wilshire 5000 index

How to get the data?

The Wilshire 5000 index is the most common index used in finance, and historical data for the Wilshire 5000 index can be easily downloaded from the internet.

For example, you can download data for the Wilshire 5000 index from January 3, 1989 on Yahoo! Finance (the Yahoo! code for Wilshire 5000 index is ^W5000).

Yahoo! Finance
Source: Yahoo! Finance.

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

R program

The R program below written by Shengyu ZHENG allows you to download the data from Yahoo! Finance website and to compute summary statistics and risk measures about the Wilshire 5000 index.

Download R file

Data file

The R program that you can download above allows you to download the data for the Wilshire 5000 index from the Yahoo! Finance website. The database starts on January 3, 1989. It also computes the returns (logarithmic returns) from closing prices.

Table 3 below represents the top of the data file for the Wilshire 5000 index downloaded from the Yahoo! Finance website with the R program.

Table 3. Top of the data file for the Wilshire 5000 index.
Top of the file for the Wilshire 5000 index data
Source: computation by the author (data: Yahoo! Finance website).

Evolution of the Wilshire 5000 index

Figure 1 below gives the evolution of the Wilshire 5000 index from January 3, 1989 to December 30, 2022 on a daily basis.

Figure 1. Evolution of the Wilshire 5000 index.
Evolution of the Wilshire 5000 index
Source: computation by the author (data: Yahoo! Finance website).

Figure 2 below gives the evolution of the Wilshire 5000 index returns from January 3, 1989 to December 30, 2022 on a daily basis.

Figure 2. Evolution of the Wilshire 5000 index returns.
Evolution of the Wilshire 5000 index return
Source: computation by the author (data: Yahoo! Finance website).

Summary statistics for the Wilshire 5000 index

The R program that you can download above also allows you to compute summary statistics about the returns of the Wilshire 5000 index.

Table 4 below presents the following summary statistics estimated for the Wilshire 5000 index:

  • The mean
  • The standard deviation (the squared root of the variance)
  • The skewness
  • The kurtosis.

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

Table 4. Summary statistics for the Wilshire 5000 index.
Summary statistics for the Wilshire 5000 index
Source: computation by the author (data: Yahoo! Finance website).

Statistical distribution of the Wilshire 5000 index returns

Historical distribution

Figure 3 represents the historical distribution of the Wilshire 5000 index daily returns for the period from January 3, 1989 to December 30, 2022.

Figure 3. Historical distribution of the Wilshire 5000 index returns.
Historical distribution of the daily Wilshire 5000 index returns
Source: computation by the author (data: Yahoo! Finance website).

Gaussian distribution

The Gaussian distribution (also called the normal distribution) is a parametric distribution with two parameters: the mean and the standard deviation of returns. We estimated these two parameters over the period from January 3, 1989 to December 30, 2022. The mean of daily returns is equal to 0.02% and the standard deviation of daily returns is equal to 1.20% (or equivalently 5.88% for the annual mean and 19.38% for the annual standard deviation as shown in Table 3 above).

Figure 4 below represents the Gaussian distribution of the Wilshire 5000 index daily returns with parameters estimated over the period from January 3, 1989 to December 30, 2022.

Figure 4. Gaussian distribution of the Wilshire 5000 index returns.
Gaussian distribution of the daily Wilshire 5000 index returns
Source: computation by the author (data: Yahoo! Finance website).

Risk measures of the Wilshire 5000 index returns

The R program that you can download above also allows you to compute risk measures about the returns of the Wilshire 5000 index.

Table 5 below presents the following risk measures estimated for the Wilshire 5000 index:

  • The long-term volatility (the unconditional standard deviation estimated over the entire period)
  • The short-term volatility (the standard deviation estimated over the last three months)
  • The Value at Risk (VaR) for the left tail (the 5% quantile of the historical distribution)
  • The Value at Risk (VaR) for the right tail (the 95% quantile of the historical distribution)
  • The Expected Shortfall (ES) for the left tail (the average loss over the 5% quantile of the historical distribution)
  • The Expected Shortfall (ES) for the right tail (the average loss over the 95% quantile of the historical distribution)
  • The Stress Value (SV) for the left tail (the 1% quantile of the tail distribution estimated with a Generalized Pareto distribution)
  • The Stress Value (SV) for the right tail (the 99% quantile of the tail distribution estimated with a Generalized Pareto distribution)

Table 5. Risk measures for the Wilshire 5000 index.
Risk measures for the Wilshire 5000 index
Source: computation by the author (data: Yahoo! Finance website).

The volatility is a global measure of risk as it considers all the returns. The Value at Risk (VaR), Expected Shortfall (ES) and Stress Value (SV) are local measures of risk as they focus on the tails of the distribution. The study of the left tail is relevant for an investor holding a long position in the Wilshire 5000 index while the study of the right tail is relevant for an investor holding a short position in the Wilshire 5000 index.

Why should I be interested in this post?

For a number of reasons, management students (as future managers and individual investors) should learn about the Wilshire 5000 index. The performance of almost all listed American companies is tracked by this stock market index, which is first and foremost well-known and respected. Gaining a deeper understanding of the US small-cap stock market and the businesses that fuel its expansion requires knowledge of the Wilshire 5000 index. Individual investors can assess the performance of their own investments and those of their organization by comprehending the Wilshire 5000 index and its components. Last but not least, a lot of businesses base their mutual funds and exchange-traded funds (ETFs) on the Wilshire 5000 index which can considered as interesting assets to diversify a portfolio.

Related posts on the SimTrade blog

About financial indexes

   ▶ Nithisha CHALLA Financial indexes

   ▶ Nithisha CHALLA Calculation of financial indexes

Related posts on the SimTrade blog

About financial indexes

   ▶ Nithisha CHALLA Financial indexes

   ▶ Nithisha CHALLA Calculation of financial indexes

   ▶ Nithisha CHALLA The business of financial indexes

   ▶ Nithisha CHALLA Float

About other US financial indexes

   ▶ Nithisha CHALLA The DJIA index

   ▶ Nithisha CHALLA The S&P 500 index

   ▶ Nithisha CHALLA The NASDAQ index

   ▶ Nithisha CHALLA The Russell 2000 index

About portfolio management

   ▶ Youssef LOURAOUI Portfolio

   ▶ Jayati WALIA Returns

About statistics

   ▶ Shengyu ZHENG Moments de la distribution

   ▶ Shengyu ZHENG Mesures de risques

Useful resources

Yahoo! Finance Wilshire 5000 Total Market Index

Wikipedia Wilshire 5000

Forbes The Wilshire 5000: Invest In The Entire U.S. Stock Market

The Street What Is the Wilshire 5000 and Why Is It Important?

Academic research

Academic research about risk

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

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

Data

Yahoo! Finance

Yahoo! Finance Data for the Wilshire 5000 index

About the author

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

Time is money

Time is money

Pranay KUMAR

In this article, Pranay KUMAR (ESSEC Business School, Master in Strategy & Management of International Business (SMIB), 2022-2023) comments on a quote about the time value of money.

Quote

“Remember that time is money.” – Benjamin Franklin

Analysis of the quote

Time value of money is the concept that the value of money changes over time due to various factors, such as inflation, interest rates, and the opportunity cost of investing or borrowing money.

In the context of Franklin’s quote, he is suggesting that time is as valuable as money. This implies that every moment lost is an opportunity lost, just like losing money. This is because the time we spend on an activity or investment can have an impact on its potential future value.
For instance, if we invest money today, it will grow in value over time due to interest and compounding. Therefore, the longer we wait to invest, the less potential value we can derive from that investment. Similarly, if we delay taking action on an opportunity, we risk losing its potential value as time goes by.

In summary, Benjamin Franklin’s quote can be interpreted as a reminder to be mindful of the time value of money. We should strive to use our time effectively, just as we would with our money, in order to maximize its potential value.

About the author of the quote

Benjamin Franklin was a Founding Father of the United States and a polymath who excelled in many fields, including science, writing, and politics. He was also an inventor, diplomat, and one of the most influential figures of the American Enlightenment. Franklin was known for his wit, wisdom, and practical advice. This quote reflects his pragmatic approach to life and his belief in the value of hard work and frugality. Franklin was a self-made man who rose from humble beginnings to become one of the most respected and admired figures of his time.

Financial concepts related to the quote

Time Value of Money

The concept of time value of money suggests that the value of money today is worth more than the same amount of money in the future, due to the potential for earning interest or returns on investment.

Compounding

Compounding is the process of earning interest on interest. It occurs when interest is added to the principal amount, and the interest earned on the new total is calculated in the next period. This results in the investment growing at an accelerating rate over time.

Opportunity cost

Opportunity cost is the cost of forgoing an opportunity or the benefits that could have been gained from an alternative choice. In the context of the quote, the opportunity cost of not investing earlier is the potential returns that could have been earned if the investment had been made earlier.

My opinion about this quote

I believe this quote is a reminder that it is never too late to start investing or saving. While it is true that starting early provides an advantage in terms of the time value of money, it is better to start late than never. By taking action now, individuals can still benefit from the power of compounding and the potential for returns on their investments.

Why should I be interested in this post?

This post is relevant for ESSEC students interested in finance and investing. The concept of time value of money is fundamental to understanding financial decision-making, and this post provides a simple explanation of the concept and its relevance in real life.

Related posts on the SimTrade blog

Quotes

   ▶ All posts about Quotes

   ▶ Jianen HUANG It’s not whether you’re right or wrong

   ▶ Fatimata KANE Money is a terrible master but an excellent servant

Financial techniques

   ▶ William LONGIN How to compute the present value of an asset?

   ▶ Maite CARNICERO MARTINEZ How to compute the net present value of an investment in Excel

Useful resources

Time Value of Money

About the author

The article was written in April 2023 by Pranay KUMAR (ESSEC Business School, Master in Strategy & Management of International Business (SMIB), 2022-2023).

La Directive Solvabilité II

Shengyu ZHENG

Dans cet article, Shengyu ZHENG (ESSEC Business School, Grande Ecole – Master in Management, 2020-2023) présente la directive Solvabilité II pour les compagnies d’assurance.

Vue globale

Solvabilité II (surnom de la Directive 2009/138/CE du Parlement européen et du Conseil du 25 novembre 2009) est une réglementation européenne qui s’applique aux compagnies d’assurance. Elle a pour objectif de renforcer la solidité financière des assureurs et de garantir leur capacité à faire face à des situations imprévues. Pour atteindre ces objectifs, la directive Solvabilité II impose aux compagnies d’assurance des exigences en matière de solvabilité, de gouvernance et de communication. Elle exige également une gestion prudente des risques, notamment en imposant des normes strictes pour l’évaluation et la gestion des risques. La directive Solvabilité II a été conçue pour encourager les assureurs à améliorer leur gestion interne et en particulier à mieux gérer leurs fonds propres (capital), ce qui devrait leur permettre de mieux protéger les assurés et de garantir leur stabilité financière à long terme.

Histoire de mise en œuvre

La directive Solvabilité II a été mise en œuvre en réponse à la crise financière de 2008, pour remplacer la directive Solvabilité I, qui était en vigueur depuis les années 1970. Les exigences imposées par la directive Solvabilité I se sont avérées obsolètes et insuffisantes pour répondre aux défis des développements financiers et économiques, notamment mise en évidence par les survenances des crises financières au début du 21e siècle. Solvabilité II présente plusieurs avantages clés, notamment une harmonisation des exigences de solvabilité à travers l’Union Européenne (UE), une plus grande transparence et des méthodologies plus modernes en gestion des risques d’assurance. La directive a été adoptée par le Parlement Européen en 2009 et est entrée en vigueur en 2016.

En France, la directive Solvabilité II a été transposée en droit national par l’ordonnance n° 2015-378 du 2 avril 2015 et la loi n° 2016-1691 du 9 décembre 2016. Ces textes modifient le Code des assurances et mettent en place un nouveau régime de surveillance prudentielle des assureurs/réassureurs. Les assureurs/réassureurs sont désormais tenus de se conformer aux exigences de Solvabilité II transcrites en texte de droit.

Les trois piliers de Solvabilité II

Solvabilité II s’appuie sur trois piliers, chacun ayant un objectif spécifique.

Pilier I : Normes quantitatives

Le premier pilier de la directive Solvabilité II établit les normes quantitatives pour le calcul des provisions techniques et des fonds propres. Les compagnies d’assurance doivent déterminer les provisions techniques, qui sont les montants réservés pour payer les sinistres futurs. Les niveaux réglementaires pour les fonds propres sont également définis dans ce pilier. Les fonds propres constituent la base financière des compagnies d’assurance et leur permettent de faire face aux risques auxquels elles sont exposées. Les deux ratios clés constamment utilisés pour évaluer les niveaux de fonds propres sont le Minimum Capital Requirement (MCR) et le Solvency Capital Requirement (SCR).

Pilier II : Normes qualitatives

Le deuxième pilier a pour objectif de fixer des normes qualitatives pour la gestion interne des risques dans les entreprises, ainsi que pour l’exercice des pouvoirs de surveillance par les autorités de réglementation. Il accentue le système de gouvernance et l’évaluation interne des risques et de la solvabilité, notamment via l’application du dispositif “Own Risk and Solvency Assessment (ORSA)”. L’identification des entreprises les plus risquées est également un objectif clé de ce pilier, et les autorités de réglementation peuvent exiger que ces entreprises maintiennent un capital plus élevé que le montant recommandé par le calcul du SCR (capital add-on) et/ou qu’elles réduisent leur exposition aux risques.

Pilier III : Communication d’information

Le troisième pilier a pour objectif de définir les informations détaillées auxquelles le public peut accéder et celles destinées aux autorités de réglementation et de contrôle. Son objectif est de standardiser, au niveau européen, les informations publiées et remises aux superviseurs. Les informations peuvent être de nature qualitative ou quantitative, et la fréquence de publication peut varier en fonction des documents concernés.

Pourquoi devons-nous nous intéresser à ce sujet ?

En tant qu’étudiants qui aspirent à une carrière dans ce secteur, nous avons tout intérêt à comprendre les enjeux de Solvabilité II, car cette directive a un impact majeur sur l’industrie de l’assurance en Europe. En effet, elle impose des exigences strictes en matière de gestion des risques et de solvabilité des compagnies d’assurance, ce qui a des répercussions sur l’ensemble de l’industrie quel que soit la fonction (actuariat, investissement, trésorerie…). Les étudiants qui souhaitent se lancer dans une carrière dans le secteur de l’assurance doivent donc comprendre les tenants et les aboutissants de cette réglementation pour mieux appréhender les défis et les opportunités du marché.

De plus, les étudiants en économie, en finance ou en droit peuvent également bénéficier d’une meilleure compréhension de cette directive, qui est un exemple concret de la manière dont les réglementations financières sont mises en place pour garantir la stabilité du marché et la protection des consommateurs. Enfin, en se tenant informés des dernières évolutions de Solvabilité II, les étudiants peuvent développer des compétences clés telles que la compréhension des réglementations financières et l’analyse des risques, qui sont essentielles pour réussir dans une carrière dans le secteur de l’assurance ou dans des secteurs connexes.

Ressources utiles

EUR-Lex, Directive 2009/138/CE du Parlement européen et du Conseil du 25 novembre 2009 sur l’accès aux activités de l’assurance et de la réassurance et leur exercice (solvabilité II) (Texte présentant de l’intérêt pour l’EEE)

A propos de l’auteur

Cet article a été écrit en avril 2023 par Shengyu ZHENG (ESSEC Business School, Grande Ecole – Master in Management, 2020-2023).

The Russell 2000 index

The Russell 2000 index

Nithisha CHALLA

In this article, Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management, 2021-2023) presents the Russell 2000 index and details its characteristics.

The Russell 2000 index

As we can already notice in the name, Russell 2000 Index is a stock market index that tracks the performance of 2,000 small-cap companies in the United States. It was introduced by the Russell Investment Group in 1984 and is now created, managed, and distributed by FTSE Russell, a subsidiary of the London Stock Exchange Group. The Russell Index family has three indexes in it, Russell 1000, Russell 2000 and the Russell 3000.

The Russell 2000 has historically outperformed the larger-cap S&P 500 Index over the long term. According to data from FTSE Russell, the Russell 2000 has returned an average of 10.7% annually over the past 20 years, compared to an average return of 7.5% for the S&P 500 over the same period.

The Russell 2000 is widely used as a benchmark by active fund managers who specialize in small-cap stocks. As of March 2023, the largest sector in the Russell 2000 was healthcare, followed by technology and financials. The index is market-capitalization weighted, which means that larger companies have a greater impact on the index performance. The index is also used as the basis for exchange-traded funds (ETFs) and other financial products that allow investors to gain exposure to small-cap stocks.

FTSE Russell is known for its commitment to transparency and the accuracy of its index calculations. The company uses a rules-based methodology for selecting and weighting stocks in its indices, and it provides detailed documentation on its methodology and data sources to ensure that investors can make informed decisions about using its indices for benchmarking and investment purposes.

How is the Russell 2000 index represented in trading platforms and financial websites? The ticker symbol used in the financial industry for the Russell 2000 index is “RUT”.

Table 1 below gives the Top 10 stocks in the Russell 2000 index in terms of market capitalization as of January 31, 2023.

Table 1. Top 10 stocks in the Russell 2000 index.
Top 10 stocks in the Russell 2000 index
Source: computation by the author (data: YahooFinance! financial website).

Table 2 gives the sector representation of the Russell 2000 index in terms of number of stocks and market capitalization as of January 31, 2023.

Table 2. Sector representation in the Russell 2000 index.
Sector representation in the Russell 2000 index
Source: computation by the author (data: YahooFinance! financial website).

Calculation of the Russell 2000 index value

The value of the Russell 2000 Index is calculated using a formula that takes into account the market capitalization of the individual stocks that are included in the index. This means the larger companies have a greater impact on the index than the smaller companies.

The Russell 2000 is reconstituted annually, typically in June. During this process, the index is updated to include the most recent data on small-cap stocks, and companies are added or removed from the index based on their market capitalization.

The formula for a market capitalization-weighted index is given by

Market Capitalization Index value

where I is the index value, k a given asset, K the number of assets in the index, Pk the market price of asset k, Nk the number of issued shares for asset k, and t the time of calculation of the index.

In a market capitalization-weighted index, the weight of asset k is given by formula can be rewritten as

Market Capitalization Weighted Index Weight

which clearly shows that the weight of each asset in the index is its market capitalization of the asset divided by the sum of the market capitalizations of all assets.

Note that the divisor, whose calculation is based on the number of shares, is typically adjusted for events such as stock splits and dividends. The divisor is used to ensure that the value of the index remains consistent over time despite changes in the number of outstanding shares.

Use of the Russell 2000 index in asset management

The Russell 2000 index is widely used in asset management as a benchmark for small-cap stocks in the United States. Small-cap stock experts who run active funds frequently use the Russell 2000 as a benchmark for their performance. On the other hand, passive fund managers can create index funds or exchange-traded funds (ETFs) that follow the performance of the Russell 2000 using the Russell 2000 as a base. In addition to serving as a benchmark for active and passive fund managers, the Russell 2000 index is also used by individual investors who are interested in small-cap stocks. Overall, the Russell 2000 index is a valuable tool for asset managers, and it has a significant impact on the investment strategies and decisions made in this market segment.

Benchmark for equity funds

Equity funds are actively managed investment vehicles that pool capital from a number of investors to buy stocks from a variety of industries. The Russell 2000 index serves as a benchmark for fund managers when assessing the performance of their small-cap equity funds. Fund managers might use a variety of investment strategies, such as top-down sector allocation or bottom-up stock selection, to outperform the benchmark.

Investors can get a good idea of how well a small-cap equity fund is doing in relation to the overall market by comparing the fund’s performance to that of the Russell 2000 index. However, it’s crucial to keep in mind that there are additional elements, such as fees, expenses, and the expertise and experience of the fund manager, that can impact the performance of an equity fund.

Financial products around the Russell 2000 index

There are a number of financial products that either provide exposure to the index or use information from the index. Not just the index funds but there are numerous ETFs and other financial products such as mutual funds, futures and options etc.

  • Exchange-Traded Funds, Options Contracts, Futures Contracts, Index funds and Mutual funds.
  • ETFs are the investment funds that are traded like stocks. ETFs based on the Russell 2000 Index include the iShares Russell 2000 ETF and the Vanguard Russell 2000 ETF.
  • Index mutual funds that track the performance of the Russell 2000 Index typically have low expense ratios and are designed to provide returns that closely match the performance of the index.
  • Futures and options contracts based on the Russell 2000 Index are traded on several exchanges, including the Chicago Mercantile Exchange (CME) and the Intercontinental Exchange (ICE).

Historical data for the Russell 2000 index

How to get the data?

The Russell 2000 index is the most common index used in finance, and historical data for the Russell 2000 index can be easily downloaded from the internet.

For example, you can download data for the Russell 2000 index from September 10, 1987 on Yahoo! Finance (the Yahoo! code for Russell 2000 index is ^RUT).

Yahoo! Finance
Source: Yahoo! Finance.

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

R program

The R program below written by Shengyu ZHENG allows you to download the data from Yahoo! Finance website and to compute summary statistics and risk measures about the Russell 2000 index.

Download R file

Data file

The R program that you can download above allows you to download the data for the Russell 2000 index from the Yahoo! Finance website. The database starts on September 10, 1987. It also computes the returns (logarithmic returns) from closing prices.

Table 3 below represents the top of the data file for the Russell 2000 index downloaded from the Yahoo! Finance website with the R program.

Table 3. Top of the data file for the Russell 2000 index.
Top of the file for the Russell 2000 index data
Source: computation by the author (data: Yahoo! Finance website).

Evolution of the Russell 2000 index

Figure 1 below gives the evolution of the Russell 2000 index from September 10, 1987 to December 30, 2022 on a daily basis.

Figure 1. Evolution of the Russell 2000 index.
Evolution of the Russell 2000 index
Source: computation by the author (data: Yahoo! Finance website).

Figure 2 below gives the evolution of the Russell 2000 index returns from September 10, 1987 to December 30, 2022 on a daily basis.

Figure 2. Evolution of the Russell 2000 index returns.
Evolution of the Russell 2000 index return
Source: computation by the author (data: Yahoo! Finance website).

Summary statistics for the Russell 2000 index

The R program that you can download above also allows you to compute summary statistics about the returns of the Russell 2000 index.

Table 4 below presents the following summary statistics estimated for the Russell 2000 index:

  • The mean
  • The standard deviation (the squared root of the variance)
  • The skewness
  • The kurtosis.

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

Table 4. Summary statistics for the Russell 2000 index.
 Summary statistics for the Russell 2000 index
Source: computation by the author (data: Yahoo! Finance website).

Statistical distribution of the Russell 2000 index returns

Historical distribution

Figure 3 represents the historical distribution of the Russell 2000 index daily returns for the period from September 10, 1987 to December 30, 2022.

Figure 3. Historical distribution of the Russell 2000 index returns.
Historical distribution of the daily Russell 2000 index returns
Source: computation by the author (data: Yahoo! Finance website).

Gaussian distribution

The Gaussian distribution (also called the normal distribution) is a parametric distribution with two parameters: the mean and the standard deviation of returns. We estimated these two parameters over the period from September 10, 1987 to December 30, 2022. The mean of daily returns is equal to 0.02% and the standard deviation of daily returns is equal to 1.20% (or equivalently 5.88% for the annual mean and 19.38% for the annual standard deviation as shown in Table 3 above).

Figure 4 below represents the Gaussian distribution of the Russell 2000 index daily returns with parameters estimated over the period from September 10, 1987 to December 30, 2022.

Figure 4. Gaussian distribution of the Russell 2000 index returns.
Gaussian distribution of the daily Russell 2000 index returns
Source: computation by the author (data: Yahoo! Finance website).

Risk measures of the Russell 2000 index returns

The R program that you can download above also allows you to compute risk measures about the returns of the Russell 2000 index.

Table 5 below presents the following risk measures estimated for the Russell 2000 index:

  • The long-term volatility (the unconditional standard deviation estimated over the entire period)
  • The short-term volatility (the standard deviation estimated over the last three months)
  • The Value at Risk (VaR) for the left tail (the 5% quantile of the historical distribution)
  • The Value at Risk (VaR) for the right tail (the 95% quantile of the historical distribution)
  • The Expected Shortfall (ES) for the left tail (the average loss over the 5% quantile of the historical distribution)
  • The Expected Shortfall (ES) for the right tail (the average loss over the 95% quantile of the historical distribution)
  • The Stress Value (SV) for the left tail (the 1% quantile of the tail distribution estimated with a Generalized Pareto distribution)
  • The Stress Value (SV) for the right tail (the 99% quantile of the tail distribution estimated with a Generalized Pareto distribution)

Table 5. Risk measures for the Russell 2000 index.
Risk measures for the Russell 2000 index
Source: computation by the author (data: Yahoo! Finance website).

The volatility is a global measure of risk as it considers all the returns. The Value at Risk (VaR), Expected Shortfall (ES) and Stress Value (SV) are local measures of risk as they focus on the tails of the distribution. The study of the left tail is relevant for an investor holding a long position in the Russell 2000index while the study of the right tail is relevant for an investor holding a short position in the Russell 2000 index.

Why should I be interested in this post?

For a number of reasons, management students (as future managers and individual investors) should learn about the Russell 2000 index. The performance of 2000 small-cap American companies is tracked by this stock market index, which is first and foremost well-known and respected. Gaining a deeper understanding of the US small-cap stock market and the businesses that fuel its expansion requires knowledge of the Russell 2000 index. Individual investors can assess the performance of their own investments and those of their organization by comprehending the Russell 2000 index and its components. Last but not least, a lot of businesses base their mutual funds and exchange-traded funds (ETFs) on the Russell 2000 index which can considered as interesting assets to diversify a portfolio.

Related posts on the SimTrade blog

About financial indexes

   ▶ Nithisha CHALLA Financial indexes

   ▶ Nithisha CHALLA Calculation of financial indexes

   ▶ Nithisha CHALLA The business of financial indexes

   ▶ Nithisha CHALLA Float

About other US financial indexes

   ▶ Nithisha CHALLA The DJIA index

   ▶ Nithisha CHALLA The S&P 500 index

   ▶ Nithisha CHALLA The NASDAQ index

   ▶ Nithisha CHALLA The Wilshire 5000 index

About portfolio management

   ▶ Youssef LOURAOUI Portfolio

   ▶ Jayati WALIA Returns

About statistics

   ▶ Shengyu ZHENG Moments de la distribution

   ▶ Shengyu ZHENG Mesures de risques

Useful resources

Wikipedia Russell indexes

Finance Strategists Defining Russell 2000 Index

FTSE Russell The Russell 2000 Index: Small cap index of choice

Motley Fool 10 of the largest Russell 2000 companies

Academic research about risk

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

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

Data

Yahoo! Finance

Yahoo! Finance Data for the Russell 2000 index

About the author

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

My internship experience as a junior consultant at ZEBOX

My internship experience junior consultant at ZEBOX

Pranay KUMAR

In this article, Pranay KUMAR (ESSEC Business School, Master in Strategy & Management of International Business (SMIB), 2022-2023) shares his professional experience as junior consultant at ZEBOX.

About the company

ZEBOX is an innovation and start-up accelerator program launched by CMA CGM, one of the world’s leading shipping and logistics companies. ZEBOX’s mission is to support start-ups and entrepreneurs in developing new technologies and business models to improve the global supply chain.

Logo of ZEBOX.
Logo of ZEBOX
Source: the company.

As a department of CMA CGM, ZEBOX has access to vast resources and expertise in the shipping and logistics industry, which allows it to provide valuable guidance and support to start-ups in this sector. The program has a global reach and is headquartered in Marseille, France.

My internship

During my internship at ZEBOX, I worked a Junior Consultant

My missions

As a Junior Consultant at ZEBOX, my primary mission was to analyze economic and demographic data from over 10 Asia-Pacific countries to guide ZEBOX’s market expansion efforts. Specifically, I was tasked with developing a comprehensive 3-year plan for ZEBOX’s expansion in the APAC region, covering strategic planning, go-to-market approaches, and market positioning using tools such as Porter’s five forces.

Required skills and knowledge

To succeed in my internship, I needed to have a strong understanding of economics, finance, and strategic management. Additionally, I needed to have excellent analytical and communication skills, as I was responsible for gathering and analyzing data on market trends, the competitive landscape, and consumer behavior in various countries, and presenting my findings and recommendations to both the ZEBOX team and the ESSEC SMIB professor.

What I learned

During my time at ZEBOX, I learned a great deal about how to conduct market research and analysis, as well as how to develop a comprehensive strategic plan. I also gained a deeper understanding of the shipping and logistics industry and the challenges faced by start-ups looking to innovate within this sector. Finally, I developed valuable skills in project management, data analysis, and communication that will serve me well in my future career.

Financial concepts related my internship

Market Research and Analysis

Understanding market trends, competitive landscape, and consumer behavior is essential to making informed business decisions. This involves conducting thorough research, gathering relevant data, and analyzing it to gain insights into the market.

Strategic planning

A comprehensive strategic plan is critical to achieving long-term success and achieving organizational goals.

Porter’s Five Forces

This model helps analyze the competitive forces within an industry and determine the attractiveness of entering a new market.

Why should I be interested in this post?

ESSEC students interested in finding a job in finance may find this post useful as it highlights the importance of having a strong foundation in both hard and soft skills. It also demonstrates the practical application of financial concepts such as market research and analysis, strategic planning, and Porter’s five forces in a real-world business context.

Related posts on the SimTrade blog

   ▶ All posts about Professional experiences

   ▶ Federico DE ROSSI My Internship Experience at AlixPartners in London

Useful resources

Here are some useful resources related to my professional experience:

ZEBOX website: This website provides information about the accelerator program and its activities.

CMA CGM website: This website provides information about the shipping and logistics company that launched ZEBOX.

About the author

The article was written in April 2023 by Pranay KUMAR (ESSEC Business School, Master in Strategy & Management of International Business (SMIB), 2022-2023).

The Consumer Confidence Index

The Consumer Confidence Index

Jianen HUANG

In this article, Jianen HUANG (ESSEC Business School, Master in Strategy & Management of International Business (SMIB), 2021-2023) explains about the consumer confidence index.

What is CCI

The Consumer Confidence Index, or CCI, is a widely used economic indicator that measures the level of optimism or pessimism that consumers feel about the economy. It is a metric that is usually used by governments, businesses, and investors to gauge consumer sentiment and predict future economic activity. The CCI is an important tool for economists and policymakers because consumer spending accounts for a significant portion of economic activity in most countries. When consumers feel more confident about the economy, they are more likely to spend money, which results in boosting economic growth. Conversely, when consumers are feeling uncertain or pessimistic about the future, they are more likely to save their money, which can lead to a slowdown in economic activity.

The index is based on a survey of consumers, which includes questions about their current financial situation, their expectations for the future, and their spending intentions. And the Index is calculated by averaging the responses of a survey of consumers. Based on these responses, a composite index is created that reflects the level of consumer confidence. A high index reading suggests that consumers are optimistic about the economy, while a low index reading suggests that consumers are pessimistic.

The figure below shows the US Consumer Confidence Index on a yearly basis. In the figure, there is a significant decrease in CCI in 2020, and that is strongly due to the impact of the COVID-19 pandemic, and at the beginning of 2022, there is another decrease that is because of the Ukraine-Russian war. The Consumer Confidence Index is based on the confidence level of consumers in the economy, and disruptions like these can significantly influence the confidence of consumers, which will lead to a fall in the financial market.

Consumer Confidence Index in the US.
Consumer Confidence Index in the US
Source: The Conference Board.

Regional Differences

There are several different versions of the Consumer Confidence Index used around the world, and each of them has its own methodology and survey questions.

In the United States, the index is produced by the Conference Board, a nonprofit research organization. The survey used to calculate the index asks consumers about their feelings on business conditions, employment, and income. The index is then calculated based on the percentage of consumers who feel positive about these factors.

In China, the CCI is released monthly by the National Bureau of Statistics. It is based on a survey of urban households, and the index is calculated based on four components: consumers’ assessments of current economic conditions, their expectations for future economic conditions, their confidence in the job market, and their willingness to spend money.

In the European Union, the Consumer Confidence Index is calculated by the European Commission. The survey used to calculate the index asks consumers about their expectations for the economy, their personal finances, and their intentions to make major purchases. The index is then calculated based on the percentage of consumers who feel positive about these factors.

Limitations of CCI

Despite its importance, the Consumer Confidence Index has some limitations that we need to take into account. First, the index is based on a survey of consumers, which means that it may not accurately reflect the true state of the economy. Consumers may be overly optimistic or pessimistic based on factors that are not related to the economy, such as current events or personal experiences. Additionally, the index only measures consumer sentiment, which may not always translate into actual economic activity. Consumers may feel optimistic about the economy, and still choose to save their money instead of spending it.

Another limitation of the Consumer Confidence Index is that it may not be a good indicator of the economic outlook for all segments of the population. The index is based on a survey of consumers as a whole, which means that it may not accurately reflect the experiences of specific demographic groups. For example, consumers who are experiencing financial difficulties may have a more pessimistic outlook on the economy than consumers who are financially secure.

Conclusion

In conclusion, the Consumer Confidence Index is an important economic indicator that measures the level of optimism or pessimism that consumers feel about the economy. While the index has some limitations, it remains a useful tool for predicting future economic activity and understanding the sentiments of consumers. By keeping an eye on the Consumer Confidence Index, stakeholders can gain a better understanding of the economic climate and make informed decisions about the future.

Related posts on the SimTrade blog

   ▶ Bijal GANDHI Economic Indicators

   ▶ Bijal GANDHI Consumer Confidence Index

Useful resources

National Bureau of Statistics China Consumer Confidence Index

The Conference Board US Consumer Confidence Index

European Union EU Consumer Confidence Index

About the author

The article was written in April 2023 by Jianen HUANG (ESSEC Business School, Master in Strategy & Management of International Business (SMIB), 2021-2023).

My Internship Experience at Kearney

My Internship Experience at Kearney

Jianen HUANG

In this article, Jianen HUANG (ESSEC Business School, Master in Strategy & Management of International Business (SMIB), 2021-2023) shares his professional experience as a consulting intern at Kearney.

Kearney

Kearney is a global management consulting firm that specializes in helping clients achieve their strategic goals and solve complex business challenges. With over 95 years of experience, Kearney has built a reputation for delivering innovative solutions that drive lasting results. The firm operates in over 40 countries, serving clients in a range of industries, including consumer goods, healthcare, retail, technology, and transportation. Kearney’s team of experienced consultants bring deep industry knowledge, analytical rigor, and a collaborative approach to every engagement, working closely with clients to understand their unique needs and deliver tailored solutions. With a focus on delivering measurable impact and driving growth, Kearney has earned a trusted reputation as a strategic partner for businesses around the world.

Logo of the Kearney.
Logo of Kearney
Source: Kearney.

My internship

I worked as a part-time assistant and supported the Kearney consulting team based in Shanghai. During the six months internship, I worked on two main projects with clients from two different industries.

The Hainan Free Trade Port is a new special economic zone in China, established in 2020, with a focus on developing a globally competitive, free trade port, and a hub for international trade and investment. The Hainan Free Trade Port aims to promote trade liberalization and facilitation, open up the Chinese economy to international investors, and attract foreign investment. The Chinese government has announced a series of policies and measures to support the development of the Hainan Free Trade Port, including tax incentives, streamlined customs procedures, and relaxed visa policies, making it an attractive destination for international businesses looking to expand in the Asia-Pacific region. With this context, the first client is a state-owned company that was planning to enter the duty-free market. And we have been asked to plan the exhibition and the future expansion.

Quality management is important for businesses to ensure that their products or services consistently meet or exceed customer expectations. By implementing a quality management system, businesses can improve their processes, reduce waste, and increase efficiency, ultimately leading to higher customer satisfaction and increased profitability. Quality management involves establishing processes and procedures to ensure that products or services meet specific standards and requirements, reducing the likelihood of defects or errors that could negatively impact customer satisfaction. By focusing on quality management, businesses can also reduce costs by eliminating waste and inefficiencies in their processes, while building trust and a positive reputation for quality and reliability with their customers. The second project is related to a Chinese intelligence manufacturing player. With the trend of digitalization, the client is now planning to digitalize their quality management system, which includes the digitalization of all stages of the production process. Kearney’s team had been asked to build a QMS for the client and help them enhance their quality control ability.

Financial concepts related my internship

Cost-Benefit Analysis

Cost-benefit analysis is often used in consulting projects to make sound suggestions and convince management. Cost-benefit analysis is a way to evaluate the potential cost and benefit of a potential project. The process involves identifying and quantifying all relevant costs and benefits associated with the project, calculating the net present value of those costs and benefits, and comparing them to determine whether the project is financially viable.

The cost-benefit analysis process includes:

  • Identify the project scope: during this stage, the consultants need to not only determine the topic of the analysis, but also identify key stakeholders, key resources, and technics.
  • Determine the cost: the cost of a project can include direct and indirect costs, opportunity costs, and potential risks.
  • Determine the benefit: a project can bring revenue from the sales, intangible benefits, or advantages we can potentially gain.
  • Calculate the result

DCF

The discounted cash flow method (DCF) is an important financial valuation method that is often used in consulting jobs, and it is one of the most commonly used cost-benefit analysis. It is used to estimate the intrinsic value of an investment based on its series of cash flows. It involves projecting future cash flows, determining the appropriate discount rate, and calculating the net present value (NPV) of those cash flows.

The mathematical formula for the NPV:

 NPV formula

CFt = cash flows of each period (from t=0 to t=T)
T = terminal date and number of periods
r = discount rate or interest rate required of the investment (it is the rate of return that the investors expect on their investment).

In a classical project, the initial cash flow, CF0, is usually negative since it is usually the initial investment of the project. The following cash flows, CFt for t=1 to t=T, are usually the profit that generates by the project for each period. The NPV can be rewritten as

 NPV formula

In the end, we are comparing the NPV with the initial target we set to evaluate whether we should launch this project. On the other hand, in the case that we have enough resources, we can consider launching all the projects that have NPV greater than 0.

In the consulting project, the consultants usually have been asked to evaluate the value and to show a figure of the benefit of the project in order to convince the management.

Customer Due Diligence (CDD)

In consulting, CDD, or Customer Due Diligence, is a critical component of advisory services provided to clients in industries such as finance, banking, and insurance. Consultants use CDD to assess the risks associated with clients’ customers and to ensure regulatory compliance. CDD helps consultants identify potential financial crimes such as money laundering, terrorist financing, or other fraudulent activities that could pose a risk to their clients. By conducting thorough and systematic customer due diligence, consultants can help their clients mitigate risk, comply with anti-money laundering (AML) and counter-terrorism financing (CTF) regulations, and make informed business decisions. CDD is an essential tool for consultants providing advisory services to clients in highly regulated industries, helping them to build trust, maintain compliance, and protect their reputation.

Related posts on the SimTrade blog

   ▶ All posts about Professional experiences

   ▶ Federico DE ROSSI My Internship Experience at AlixPartners in London

Useful resources

Kearney

About the author

The article was written in April 2023 by Jianen HUANG (ESSEC Business School, Master in Strategy & Management of International Business (SMIB), 2021-2023).

It's not whether you're right or wrong

It’s not whether you’re right or wrong

Jianen HUANG

In this article, Jianen HUANG (ESSEC Business School, Master in Strategy & Management of International Business (SMIB), 2021-2023) comments on a quote by George Soros.

Quote

“It’s not whether you’re right or wrong, but how much money you make when you’re right and how much you lose when you’re wrong.” – George Soros

Analysis of the quote

With the development of the business world, the financial market nowadays becomes more and more unpredictable because of the fast evolving of innovation, more different business models, and shorter horizons of business plans. And the financial market is not only about stocks (or any asset), but also the collective behavior of the crowds, markets, and organizations. In this case, the decision can be right or wrong in every trade. As an investor, if we are not able to ensure the correctness of our decision, then we need to focus on what we can control, which is maximizing the gain from the correct decision and minimizing the loss from the wrong decision. Thus, a great investment strategy and risk management strategy are vital for investors to be in the financial market.

My opinion about this quote

This quote taught us that instead of focusing on personal pride, ego, and hesitation, what matters are the outcome and the rewards. We should enhance our knowledge, be result-oriented, and be prepared to fight any risks it might occur.

Practical Implementation

Suppose you are an investor in the stock market and you hold shares of a company that you believe will perform well in the near future. You bought the shares at $9 each and you have a target profit of 44%. However, you also want to minimize your potential loss in case the stock performs poorly.

To take profit, you could set a sell limit order at $13 per share, which means that if the stock price reaches that level, your shares will automatically be sold at that price, locking in your 44% profit.

To limit loss, you could set a sell stop-loss order at $8 per share, which means that if the stock price drops to that level, your shares will automatically be sold at that price, limiting your loss to 10%.

In this example, you are using two different types of orders to both maximize your potential profit and minimize your potential loss. By using a sell limit order, you are ensuring that you sell your shares at a profit, while the stop-loss order helps to protect your investment by limiting your potential loss.

Related posts on the SimTrade blog

   ▶ All posts about Quotes

   ▶ Akshit GUPTA Portrait of George Soros: a famous investor

Useful resources

George Soros

About the author

The article was written in April 2023 by Jianen HUANG (ESSEC Business School, Master in Strategy & Management of International Business (SMIB), 2021-2023).