Financial techniques

The “Financial techniques” category contains posts about asset pricing models (optimal portfolios, derivatives, trading and investment strategies, financial products, data, etc.) used in the financial industry.

The BOVESPA index

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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

by

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

by

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 FTSE 100 index

by

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).

The Nikkei 225 index

by

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

by

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).

The impact of market orders on market liquidity

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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

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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).

La Directive Solvabilité II

by

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

by

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).

The Consumer Confidence Index

by

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).

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

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

Lokendra RATHORE

In this article, Lokendra RATHORE (ESSEC Business School, Master in Strategy & Management of International Business (SMIB), 2022-2023) explains the Good-til-Cancelled (GTC) order and the Immediate-or-Cancel (IOC) used to trade in financial markets.

In addition to the types of orders that we discussed in Period1 of the SimTrade certificate (market orders, limit orders, best limit orders, stop loss orders and stop limit orders), I would like to elaborate on the following two other types or order that I have used in the past and found useful: Good-til-Cancelled (GTC) Order and Immediate-or-Cancel (IOC) Order.

What is Good-til-Cancelled (GTC) Order?

A Good-till-Cancelled (GTC) order is an order that remains in effect until it is either executed or cancelled by the investor. This type of order allows the investor to place a standing order that remains active until the investor cancels it or it is filled. For example, if an investor wants to purchase a stock when it reaches a certain price, they can place a GTC order, and the order will remain active until either the price is reached or the investor cancels it.

Significance

Flexibility: GTC orders provide investors with a high level of flexibility, as they remain active for an indefinite period of time. This allows investors to take advantage of market opportunities without having to send order every day.

Long-term Investment Strategy: GTC orders are particularly useful for investors who have a long-term investment strategy and are looking to accumulate shares over a period of time. The investor can place a GTC order at a specific price, and the order will remain active until the desired price is reached.

What is Immediate-or-Cancel (IOC) Order?

An Immediate-or-Cancel (IOC) order is a type of order that must be executed immediately, and any portion of the order that cannot be filled is cancelled. This type of order is used when an investor wants to ensure that an order is executed as quickly as possible, even if only part of the order can be filled. For example, if an investor wants to purchase a large number of shares of a stock, they may place an IOC order. If only a portion of the shares can be purchased immediately, the remainder of the order will be cancelled.

Significance

Time-sensitive: IOC orders are suitable for investors who need to execute a trade quickly, such as when they need to close a position or take advantage of a sudden market opportunity.

Partial Fills: The IOC order allows for partial fills, meaning that if only a portion of the order can be executed immediately, the remainder of the order is cancelled. This can be useful when an investor wants to limit their exposure to a particular stock.

What is the difference between Good-til-Cancelled (GTC) Order and Day order

Table 1. Comparison of GTC and IOC orders.
Comparison of GTC and IOC orders.
Source: production by the author.

In conclusion, both GTC and IOC orders are useful tools for investors who want to manage their trades and execute their investment strategies effectively. The choice of which type of order to use will depend on the specific needs and investment objectives of the investor.

Related posts on the SimTrade blog

▶ All posts about Orders

▶ Clara PINTO High-frequency trading and limit orders

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

Useful resources

SimTrade course Trade orders

U.S. Securities and Exchange Commission (SEC) investor.gov

Investor.gov (SEC) Good-til-cancelled order

Investor.gov (SEC) Understanding Order Types

About the author

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

The NASDAQ index

by

The NASDAQ index

Nithisha CHALLA

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

The NASDAQ index

NASDAQ was first founded in 1971 and it is an American stock exchange. By market capitalization of shares traded it is the second-largest stock exchange in the world after the New York Stock Exchange (NYSE). As many of the technology and growth companies are listed on the exchange it is a popular benchmark for them. It has around 3000 companies listed on it, including some of the world’s top technology companies like Microsoft, Amazon, Facebook and Google.

The NASDAQ index is a market capitalization-weighted index that tracks the performance of the stocks listed on the NASDAQ exchange. It is widely used by investors and financial analysts to gauge the performance of the technology sector and the broader US economy.

Interestingly, there is a sister index, the Nasdaq Financial 100 that consists only of financial stocks. Both indices debuted together in 1985. The Nasdaq Financial 100 index was given more attention in the early years. However, the Nasdaq-100 has gained popularity over time due to the expansion of tech companies.

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

Table 1 gives the Top 10 stocks in the NASDAQ index in terms of market capitalization as of August 26, 2022.

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

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

Table 2. Sector representation in the NASDAQ index.
Sector representation in the NASDAQ index
Source: computation by the author (data: ETmoney!).

Calculation of the NASDAQ index value

The NASDAQ index is a value-weighted index (also called a market-capitalization- weighted index). This means the larger companies have a greater impact on the index than the smaller companies.

At the end of each trading day the value of the NASDAQ index is determined in real-time and can be used as a benchmark for the performance of the index’s constituent companies’ current market prices.

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 NASDAQ index in asset management

Given that the index is used for performance measuring it is widely used for constructing and analyzing investment portfolios. This index’s primary use is to create investment strategies, mitigate risk, and assess portfolio performance. Investors and asset managers utilize this index as a useful index to measure the overall performance of the market. It is mainly used for benchmarking, passive investing, active management and risk management.

Benchmark for equity funds

There are several indices that are used as a benchmark for equity funds, but the NASDAQ index is notable for its emphasis on businesses that invest in the technology sector, growth stocks, or both. It is primarily used to compare their performance to the overall market or a particular industry. Additionally, it gives investors a way to contrast the performance of various equity funds with various investment strategies or objectives.

While there are many advantages to using indexes as benchmarks, there are also some disadvantages and restrictions. For instance, benchmarks may not always be indicative of the precise investment goals or risk profile of a fund. Furthermore, benchmarks may be distorted by elements like the size or makeup of the companies included in the index.

Financial products around the NASDAQ index

Investors of all levels can invest in the Nasdaq-100 in a variety of ways, including through ETFs, mutual funds, options, futures, and annuities. ETFs that track the Nasdaq-100 are the easiest way to invest in the index. The ETF gives you exposure to all the 100 largest non-financial companies through a single investment. One of the most well-known ETFs that tracks the Nasdaq-100 index is the Invesco QQQ ETF and the First Trust NASDAQ-100 Technology Sector ETF (QTEC). The Nasdaq-100 is regarded as the best way to invest in some of the top non-financial companies listed on the Nasdaq because of its track record of strong index performance.

The Nasdaq-100 includes foreign stocks as well, unlike the S&P 500. Again, unlike the S&P 500, the Nasdaq-100 only permits non-financial companies to list on it. As of April 2023, a few of the international stocks that are a part of the Nasdaq-100 are Baidu from China, Ryanair from Ireland, Garmin from Cayman Island, and Infosys from India.

Index funds that attempt to track the Nasdaq Composite include Fidelity Investments’ FNCMX mutual fund and ONEQ exchange-traded fund. For investors looking for broad exposure to the stock market with relatively low fees, index funds are a popular option.

Historical data for the NASDAQ index

How to get the data?

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

For example, you can download data for the NASDAQ index from January 5, 1972 on Yahoo! Finance (the Yahoo! code for NASDAQ index is ^IXIC).

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 Nasdaq index.

Download R file

Data file

The R program that you can download above allows you to download the data for the Nasdaq index from the Yahoo! Finance website. The database starts on January 2, 1992. It also computes the returns (logarithmic returns) from closing prices.

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

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

Summary statistics for the Nasdaq index

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

Table 4 below presents the following summary statistics estimated for the Nasdaq 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 Nasdaq index.
Summary statistics for the Nasdaq index
Source: computation by the author (data: Yahoo! Finance website).

Evolution of the Nasdaq index

Figure 1 below gives the evolution of the Nasdaq index from January 2, 1992 to December 30, 2022 on a daily basis.

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

Figure 2 below gives the evolution of the Nasdaq index returns from January 2, 1992 to December 30, 2022 on a daily basis.

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

Statistical distribution of the Nasdaq index returns

Historical distribution

Figure 3 represents the historical distribution of the Nasdaq index daily returns for the period from January 2, 1992 to December 30, 2022.

Figure 3. Historical distribution of the Nasdaq index returns.
Historical distribution of the daily Nasdaq 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 2, 1992 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 Nasdaq index daily returns with parameters estimated over the period from January 2, 1992 to December 30, 2022.

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

Risk measures of the Nasdaq index returns

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

Table 5 below presents the following risk measures estimated for the Nasdaq 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 Nasdaq index.
Risk measures for the Nasdaq 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 Nasdaq index while the study of the right tail is relevant for an investor holding a short position in the Nasdaq index.

Why should I be interested in this post?

For a number of reasons, ESSEC students should learn about the Nasdaq index. The performance of tech-oriented companies is tracked by this stock market index, which is first and foremost well-known and respected. Gaining a deeper understanding of the US stock market and the businesses that fuel its expansion requires knowledge of the Nasdaq index. Management students can assess the performance of their own investments and those of their organization by comprehending the Nasdaq index and its components. Last but not least, a lot of businesses base their mutual funds and exchange-traded funds (ETFs) on the Nasdaq index.

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 Russell 2000 index

   ▶ Nithisha CHALLA The Wilshire 5000 index

About portfolio management

   ▶ Jayati WALIA Returns

   ▶ Youssef LOURAOUI Portfolio

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

Yahoo! Finance Data for the Nasdaq index

Data: Bloomberg

Bloomberg

Bloomberg Data for the Nasdaq 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 DJIA index

by

The DJIA index

Nithisha CHALLA

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

The DJIA index

The Dow Jones Industrial Average (DJIA) index was created on May 26, 1896, by Charles Dow and Edward Jones, the co-founders of Dow Jones & Company. It is publicly known as the Dow Jones index or the Dow in general. The DJIA is currently owned and managed by The Wall Street Journal.

It is a stock market index in the United States which represents the performance of 30 large-capitalization publicly traded companies. Today, it is no longer limited to just industrial companies like how it was initially and includes stocks from a variety of sectors, such as technology, healthcare, and finance.

Who decides about the selection of stocks in the index? The Wall Street Journal, which owns the index, selects the stocks based on a variety of factors, such as the company’s size and reputation, and the representation of the industries.

The DJIA is a price-weighted index, which means that each stock’s weight in the index is determined by its price per share rather than its market capitalization such as the S&P 500 index (see below for the technical details). The DJIA is published and disseminated in real-time by various financial news outlets and can be accessed by investors and traders around the world.

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

Table 1 gives the Top 10 stocks in the DJIA index in terms of market capitalization as of January 19, 2023.

Table 1. Top 10 stocks in the DJIA index.
Top 10 stocks in the DJIA index
Source: computation by the author (data: Motley Fool financial website).

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

Table 2. Sector representation in the DJIA index.
Sector representation in the DJIA index
Source: computation by the author (data: Wikipedia).

Calculation of the DJIA index value

As a price-weighted index, the DJIA has a greater impact on the index value when the stock prices of companies are higher. The DJIA index value is determined solely based on stock prices, disregarding any dividends that the companies that make up the index have paid.

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 the following formula

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 the DJIA index in asset management

As we all know, investors frequently use the DJIA index as a benchmark. The DJIA index is used by asset managers to compare the returns on their investments to market returns. Given that it is an index that gauges market performance, it supports investors in carrying out key asset management tasks like passive investments, the capacity to assess corporate risk, asset allocation, portfolio management, etc. But we should always be aware that the DJIA does not encompass all markets and industries in the US. As a result, whenever we evaluate the performance of the US market, we should always take other indexes such as the S&P 500 index and the Russell 2000 into account.

Benchmark for equity funds

Now how do we decide if DJIA is a benchmark for equity funds in the US market? Precisely by seeing if the index indicates all the sectors and industries in the market. Since the DJIA is a price-weighted index and only takes the top 30 companies into account, it is not typically used as a benchmark for the entire US market. We should also take into account other diverse indexes, such as the S&P 500 or the Russell 2000, which offer a more complete representation of the market, if we need a benchmark for the entire US market.

Financial products around the DJIA index

There are a number of financial products centered around the DJIA index that can offer investors some insight, as we are aware that it measures the performance of sizable publicly traded companies listed on the New York Stock Exchange (NYSE) and the Nasdaq. I listed the main financial products associated with the DJIA index through which investors can access the index as below:

  • Exchange-Traded Funds, Options Contracts, Futures Contracts, Index funds and Mutual funds.
  • ETFs are the investment funds that are traded like stocks. The SPDR Dow Jones Industrial Average ETF (DIA) and the ProShares Ultra Dow30 ETF are two examples of ETFs that track the DJIA index (DDM)
  • Futures and Options Contracts allow investors to buy or sell the DJIA index at a specific price and date in the future. Primarily to combat market volatility, to generate income through trading strategies, or to make predictions about the index’s future course
  • Mutual funds and index funds tend to focus more on investing in firms that are included in the DJIA index or attempt to replicate the performance of the index by purchasing the same stocks that make up the index

Historical data for the DJIA index

How to get the data?

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

For example, you can download data for the DJIA index from January 2, 1992 on Yahoo! Finance (the Yahoo! code for DJIA index is ^DJI).

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 DJIA index.

Download R file

Data file

The R program that you can download above allows you to download the data for the DJIA index from the Yahoo! Finance website. The database starts on January 2, 1992. It also computes the returns (logarithmic returns) from closing prices.

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

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

Summary statistics for the Dow Jones index

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

Table 4 below presents the following summary statistics estimated for the Dow Jones 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 Dow Jones index.
Summary statistics for the Dow Jones index
Source: computation by the author (data: Yahoo! Finance website).

Evolution of the Dow Jones index

Figure 1 below gives the evolution of the Dow Jones index from January 2, 1992 to December 30, 2022 on a daily basis.

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

Figure 2 below gives the evolution of the Dow Jones index returns from January 2, 1992 to December 30, 2022 on a daily basis.

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

Statistical distribution of the Dow Jones index returns

Historical distribution

Figure 3 represents the historical distribution of the Dow Jones index daily returns for the period from January 2, 1992 to December 30, 2022.

Figure 3. Historical distribution of the Dow Jones index returns.
Historical distribution of the daily Dow Jones 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 2, 1992 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 DJIA index daily returns with parameters estimated over the period from January 2, 1992 to December 30, 2022.

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

Risk measures of the Dow Jones index returns

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

Table 5 below presents the following risk measures estimated for the Dow Jones 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 Dow Jones index.
Risk measures for the Dow Jones 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 S&P 500 index while the study of the right tail is relevant for an investor holding a short position in the S&P 500 index.

Why should I be interested in this post?

For a number of reasons, ESSEC students should learn about the Dow Jones index. The performance of 30 large-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 stock market and the businesses that fuel its expansion requires knowledge of the Dow Jones index. Management students can assess the performance of their own investments and those of their organization by comprehending the Dow Jones index and its components. Last but not least, a lot of businesses base their mutual funds and exchange-traded funds (ETFs) on the Dow Jones index.

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 S&P 500 index

   ▶ Nithisha CHALLA The NASDAQ index

   ▶ Nithisha CHALLA The Russell 2000 index

   ▶ Nithisha CHALLA The Wilshire 5000 index

About portfolio management

   ▶ Jayati WALIA Returns

   ▶ Youssef LOURAOUI Portfolio

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

Yahoo! Finance Data for the DJIA index

Data: Bloomberg

Bloomberg

Bloomberg Data for the DJIA 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).

Float

by

Float

Nithisha CHALLA

In this article, Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management, 2021-2023) explains float and its use in the construction financial indexes.

What is Float?

The term “float” (sometimes mentioned as “free float”) refers to the quantity of shares that are readily tradable in financial markets. The float is defined as

Float = Total outstanding shares – Closely held shares – Restricted shares

Outstanding shares are the total number of shares issued by the company.

Closely held shares are the shares of a company that are owned by a small number of shareholders and are not traded on a public stock exchange. These shareholders may include company founders, family members, or a small group of private investors.

Restricted shares are the shares that are not transferable until certain conditions are met and are typically held by corporate management, such as executives and directors. Restricted shares are a type of equity compensation that some employees receive.

The float is usually expressed as a percentage of the total number of shares issued by the company.

Float and IPO

When a company conducts an initial public offering (IPO) or a seasoned offering (SEO) to finance its operational activities and investments, it releases a certain number of shares onto the market that are available for purchase by anyone interested in acquiring a piece of the company. The number of shares issued by the company increases the float. Before the IPO, the float is equal to zero. After the IPO, the float increases but may be relatively small as the founder or top managers of the company may want or have to keep some of their shares.

Why is the float important?

The float is crucial for the calculation of market capitalization-weighted stock market indices. The weight of a company’s stock in the index and, consequently, its impact on the performance of the index as a whole, can change depending on whether shares are included in or excluded from the float. Because of this, a lot of indices base their values solely on the shares in the float, known as the float-adjusted market capitalization method.

Stock market liquidity increases as the float increases. As the number of shares that can be purchased and sold increases, it makes it simpler for an investor to enter and exit the market.

High-float stocks and low-float stocks

In the equity market, we often distinguish high-float stocks and low-float stocks according to the percentage of shares that are available for trading in the market. High-float stocks have more supply and more shares available for trading than low-float stocks.

High float stocks have greater liquidity and are less volatile. In a situation where there is extremely heavy demand, supply and demand will become imbalanced, which will lead to extreme price moves.

Example

The percentage of float shares in relation to all outstanding shares is known as the float percentage. Let us consider the case of Amazon. As of September 2021, Amazon had approximately 505 million shares outstanding. Of these shares, approximately 425 million were considered “float shares”. Float shares are the shares available for trading by the public and exclude shares held by insiders, institutional investors, and other long-term investors.

Therefore, Amazon’s float share percentage would be calculated as follows:
(425 million float shares / 505 million outstanding shares) x 100% = 84.16%

This indicates that the public had access to about 84.16% of Amazon’s outstanding shares for trading. Insiders, institutions, and other long-term investors held the remaining 15.84% of the stock.

Indexes using the float

Equity indices that track the performance of a particular group of companies, such as small-cap or mid-cap companies, are frequently created using float-based indexes. The market capitalization of each company, which is determined by multiplying the total number of outstanding shares by the current share market price, is considered in the calculation of these indices.

The Russell 2000 index, which tracks the performance of 2,000 small-cap companies in the US, and the MSCI World Small Cap index, which tracks the performance of small-cap companies in developed markets worldwide, are two of the many examples of indexes that make use of the float.

We present below the formula for a market-capitalization-weighted index and a float-adjusted market-capitalization-weighted index.

Market-capitalization-weighted index

A market capitalization-weighted index is calculated by multiplying the price of each asset in the index by its number of outstanding shares and summing the resulting values. The weighting of each asset in the index is determined by its market capitalization, so that the largest and most influential companies have the greatest impact on the overall performance of the index.

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.

Float-adjusted market-capitalization-weighted index

In a float-adjusted market-capitalization-weighted index, the market-capitalization weight of each asset is adjusted for its market float. It is also called a free float. Instead of taking into account shares held by insiders, governments, or other entities that might not be available for trading, the weight is adjusted based on the percentage of shares that are actually traded on the open market.

This differs from the market capitalization weighted index as it accounts for the shares outstanding of a company. A float-adjusted market capitalization-weighted index only takes into account shares that are freely available for trading, whereas a market capitalization-weighted index takes into account all outstanding shares, providing a more accurate picture of the performance of the market.

The formula for a float-adjusted market-capitalization-weighted 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

Why should I be interested in this post?

As a key idea in finance and investment, float should be covered by management students. Float has important effects on both managers and investors. Analyzing a company’s financial statements can also benefit from having a solid understanding of floats. When making a choice, a management student who is researching a company’s stock as a potential investment should keep this in mind.

Related posts on the SimTrade blog

   ▶ All posts about Financial techniques

   ▶ Nithisha CHALLA Financial indexes

   ▶ Nithisha CHALLA Calculation of financial indexes

   ▶ Nithisha CHALLA The DJIA index

Useful resources

Bankrate What is a stock float
Business Insider Floating stock: Why it’s important for investors to know a company’s float

CFI What is Floating Stock?

The Economic Times Float and IPO

Russel How are indexes weighted?

About the author

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

Automation in Audit

by

Automation in Audit

Federico MARTINETTO

In this article, Federico MARTINETTO (ESSEC Business School, Exchange Global BBA, 2021) explains about the importance of the data automation in the audit process.

Why is intelligent automation important for the audit processes?

Traditional auditing has the following problems, for which intelligent automation can provide a solution:

  • It relies on manual labor of intensive data collection and examination, which makes traditional auditing costly, time-consuming, and error-prone.
  • It relies on sampling, where a representative sample of the data is selected to identify risks. This is because examining the entire data is expensive and time-consuming. If the selected data is not representative of the population being tested, auditors may conclude that there are more or fewer problems than actually exist. This problem is referred to as sampling risk.

By leveraging RPA and AI, intelligent automation:

  • Reduces the time spent on repetitive and tedious auditing tasks such as data collection, data extraction, or reporting. Human intelligence and talent can then be deployed in more value-added processes.
  • Enables a more granular data analysis by reviewing all available data automatically instead of sampling. As a result, auditors will gain a better understanding of an organization’s risk and be able to focus on high-risk documents and anomalies.

PwC, one of the world’s leading providers of audit, consulting, tax and advisory services, created RPA bots to streamline report development for monthly management, accounts receivable and travel expense reports. Report development time was reduced from one week to minutes with a suite of IBM RPA bots.

How does intelligent automation improve the audit processes?

Faster and more comprehensive data collection and cleaning.

Whether it is an internal or external audit, auditors gather evidence about business processes from a variety of sources such as process documents, invoices, system logs, or reports. Gathering data from unstructured sources is burdensome when executed manually. Intelligent automation tools can read and understand the context of documents with NLP and intelligent document processing technologies. This enables intelligent bots to:

  • Automatically convert unstructured data to a structured format
  • Perform calculations with extracted data
  • Combine data from different sources and input it into a target file.

As a result, auditors can review the entire population instead of just a sample in a fraction of the time it would take to perform a manual audit.

In addition to statistical analysis and visualizations, intelligent bots can perform analyses on gathered data with machine learning algorithms and identify anomalies such as potential fraud or suspicious IT logs, according to predetermined rules. By flagging these anomalies, auditors can focus on high-risk areas throughout the population.

Moreover, AI-enabled bots can learn and adapt to datasets so they can improve the accuracy of anomaly detection over time.
For instance, researchers from Rutgers University implemented an RPA bot for a public accounting firm. While testing the deployed bot, the researchers overstated the loan amount balance of some transactions, and the bot could detect all the anomalies.

Reduction in manual work can allow auditors to conduct audits more often. This can help businesses to adapt to the ever-changing business environment and provide a higher level of assurance. Intelligent bots can also continuously monitor determined controls in real-time and flag issues for further examination by auditors.

Three steps for implementing intelligent automation in audit

Step 1: Identify processes suitable for automation

It is important to understand how different audit processes are carried out in order to determine which ones should be automated. By using event logs and other process-related data, auditors can leverage process mining to identify process patterns and deviations and create full visualizations of processes. Most major intelligent automation vendors also provide process mining capabilities.

This higher-level understanding enabled by process mining helps auditors to determine which audit processes:

  • are repetitive, rule-based, and time-consuming. These processes are low-hanging fruits for automation.
  • require human judgment and professional skepticism. Auditors can define the rules governing human judgment for these processes and have bots flag cases that deviate from them for further examination.

Step 2: Test your bots to ensure that they function as desired

After determining the processes for automation and building bots for them, auditors should test the bots in a controlled environment to ensure:

  • They carry out the tasks they are designed for without issues
  • They handle exceptions well and route the exception to relevant staff.

Step 3: Monitor your automated processes and identify areas for improvement

Auditors should monitor the deployed bots to ensure that they continue functioning as expected. This is because:

  • You may discover areas for improvement after deployment
  • Bots can encounter data or exceptions that were not included in the test phase
  • The business environment is constantly changing, so bots’ performance could degrade over time.

Why should I be interested in this post?

You should be fascinated in this post if the audit process and the analysis of data and their transformation into essential information fascinates you. Technology and all the most innovative tools are a puzzle to solve.

Related posts on the SimTrade blog

   ▶ Federico MARTINETTO My experience as a PwC Associate Auditor in the Digital Data Hub

   ▶ Louis DETALLE A quick review of the Audit job…

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

About the author

The article was written in April 2023 by Federico MARTINETTO (ESSEC Business School, Exchange Global BBA, 2021).

The investment ecosystem

by

The investment ecosystem

Nithisha CHALLA

In this article, Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management, 2021-2023) explains the investment ecosystem in financial markets.

Introduction

In the investment ecosystem, there are several blocks to understand: market participants, market products, and market organization.

Market participants

Market participants are individuals, companies, financial institutions, and governments. Some of these participants may issue assets like companies (stocks, commercial paper, and bonds) and governments (bonds). Some of these participants may invest in these assets like individuals or pension funds.

Based on the amount they invest, market participants are segregated as big players and small players. Big players are mostly institutional investors which collect the funds and then invest them. Few examples of institutional investors are mutual funds, pension funds, hedge funds, trusts, charities etc. Big players may also be wealthy individuals (high net worth individuals or HNWI) or family offices. Small players are other individual investors.

Corporates run businesses, including manufacturing, service, and technology firms, and they need capital to expand and maintain their operations. On the other side, we have institutions that consist of fund managers that could be institutional investors but also retail investors as well. These are the people that have capital so the capital flows from the institutions or investment managers who have the money to the corporations that need that money to grow and run their business. The cycle between the two parties is completed when the firms issue back to the investor’s bonds, which are classified as debt, or shares, which are classified as equity.

In the middle of these two groups sit the investment banks they are often referred to as the sell side and they have contacts on both sides of these players. They have corporate clients, and they have institutional investor clients, their job is to match up the institutional investors with the corporates based on risk and return assessments and expectations and investment style to get the deal done. In addition, we have public accounting firms which are the fourth player in the market.

Market Products

Assets

What are assets? In financial language, an asset is that which has some economic value. And assuming that its value increases in the future market participants buy them and that is how it is a part of the investment ecosystem. Few examples for assets are fixed deposit, land, gold, stock, etc.

Asset classes are made up of those investments or securities whose characteristics are the same. Few major asset classes are equity, bonds (fixed income), commodities, and real estate.

Instruments

What are Instruments? Instruments are the ways through which we can invest in different asset classes.

Some of the major instruments we see in markets are direct investing, mutual funds, and exchange-traded funds (ETFs).

  • Direct investing is nothing but investing cash physically in different asset classes or we can digitally buy assets through our accounts
  • Mutual funds are the funds collected by multiple investors and then those are invested in different asset classes. To manage these mutual funds, we have fund managers who will invest on behalf of investors.
  • ETFs are nothing but a basket of securities just like mutual funds, but the only difference is they are traded on stock exchanges.

Market organization

Primary and secondary markets

The primary markets: the initial issuance of assets

The primary market is where new securities, including stocks, bonds, and other financial assets, are first issued by governments or corporations. The primary market is also referred to as the market for new issues.

Companies and governments raise money in the primary market by offering their securities to retail or institutional investors. The securities may be sold through a private placement or an initial public offering (IPO).

There are four main players in the primary market mainly for issuance of securities.
1) Corporates
2) Investors: institutional investors and individual investors
3) Corporate banks
4) Public accounting firms

The secondary markets: the exchange of assets

In the secondary market, fund managers and banks collaborate to trade securities between investors after they have already been issued. On one side, a fund manager may want to purchase securities of a public company, while on the other, a different fund manager may wish to sell those same securities. Investment bankers come between these clients to help facilitate these trades, and this trade is facilitated over the stock exchange. They provide equity research coverage to help fund managers make decisions about buying and selling those securities. And this secondary market trading makes markets liquid. This is what allows you to get in and out of security very easily.

Market infrastructure

Infrastructure providers are the companies which enable the transactions and functioning of different instruments. It means all the digital and physical infrastructure required for the investor is provided by the infrastructure provider. The few common examples of an infrastructure provider are the stock exchange, depositories, and registrar and transfer of agents.

  • Stock exchange: It is the platform where you can sell and buy securities. Here, with the help of a broker and the stock exchange two investors can buy and sell stocks without knowing each other. For example, The TSE is the largest stock exchange in Asia by market capitalization. It is located in Tokyo, Japan and has over 3,500 listed companies.
  • Depositories: These are the companies that store the stocks we buy in electronic form. We can store these stocks through our demat accounts. Depositories help you transfer stock and various other functions like checking the statements, portfolio holdings and transaction information etc. Generally investors directly do not interact with depositories but they approach through a broker who would invest on their behalf. For example: The DTC is one of the largest depositories in the world. It is located in New York City and holds over 3.5 million securities worth trillions of dollars.
  • Registrar and Transfer of Agents (RTA): just like depositories in case of stocks, RTA’s in case of mutual funds. All trades of mutual funds like subscription, redemption, and transfer, are recorded by an RTA. An RTA also helps mutual fund investors in providing their portfolio and statements to them.

Why should I be interested in this post?

As a student and prospective business management graduate, I think it is important to know the investment ecosystem. Firstly, investments play a vital role in the growth and success of companies. Companies need investments to fund their operations, expand their businesses, and create value for their shareholders. Therefore, understanding the investment ecosystem will enable management students to make informed decisions regarding investments that can help drive the growth of the companies they work for or manage in the future.

Related posts on the SimTrade blog

▶ All posts about financial techniques

   ▶ Marie POFF Film analysis: The Wolf of Wall Street

Useful resources

McKinsey (2017) Capital Markets Infrastructure: An Industry Reinventing Itself

Black rock The Investment Stewardship Ecosystem

About the author

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

High-frequency trading and limit orders

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High-frequency trading and limit orders

Clara PINTO

In this article, Clara PINTO (ESSEC Business School, Master in Strategy & Management of International Business (SMIB), 2020-2023) explains about high frequency trading in a dynamic limit order market.

What is High-frequency trading (HFT)?

While the adage “time is money” applies to almost all economic operations, the rapid spread of computerized trading has carried this quote to its final extreme. High-frequency trading (HFT) is a type of algorithmic trading that relies on advanced computer programs to make trading decisions and execute trades in a matter of milliseconds. HFT has become increasingly popular in recent years, particularly in dynamic limit order markets (“A dynamic limit order market with fast and slow traders”, European Central Bank), where the bid and ask prices of securities are constantly changing. This allows them to take advantage of small price discrepancies in the market and generate profits on a large scale, this method known as statistical arbitrage, involves traders looking for temporary pricing inconsistencies across different exchanges and capitalize on it, using ultra-fast transactions.

What Exactly Is a Limit Order?

A limit order is an instruction to buy or sell a security at a specified price or better. For example, a trader may place a buy limit order for a stock at $50, meaning he or she is willing to buy the stock only if it is available at that price or lower. Similarly, a sell limit order may be placed at $60, meaning the trader will sell the stock only if the price is at that level or higher.

HTF and Limit Order

High-frequency trading (HFT) and limit orders are closely linked, as HFT traders often rely on limit orders to execute their trades. In fact, limit orders are a key component of many HFT trading strategies. HFT traders often use limit orders in conjunction with advanced algorithms to identify market trends and execute trades at lightning-fast speeds. They may place many limit orders at various prices to take advantage of small price movements in the market and use sophisticated algorithms to determine the best time to execute their trades.

However, the use of limit orders in HFT trading can also have downsides. For example, the large number of limit orders placed by HFT traders can lead to increased volatility in the market, as these orders can cause sudden price movements, for example flash crash when the prices of stocks or commodities suddenly plunges but then quickly recovers. Hence, the use of limit orders in HFT trading can also have downsides, and it is important for regulators to monitor HFT activity and ensure that it does not cause market instability or unfair trading practices.

Why should I be interested in this post?

For many business school students, finance and trading are part of the most preferred jobs. Understanding the trends in high-frequency trading is now a requirement for future institutional investors. Being quick allows traders to adjust outstanding limit orders in response to news arrivals when working with “slow” market players who experience a relative loss in bargaining power, leading them to strategically submit limit orders with a lower execution probability, limiting trade.

Related posts on the SimTrade blog

▶ Akshit GUPTA High-frequency trading

▶ Shruti CHAND High-frequency trading: pros and cons

▶ Akshit GUPTA Analysis of The Hummingbird Project movie

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

Useful resources

SimTrade course Trade orders

Hoffmann P. (2013) A dynamic limit order market with fast and slow traders European Central Bank Working Paper Series.

Lewis M. (2015) Flash boys Norton & Company.

About the author

The article was written in March 2023 by Clara PINTO (ESSEC Business School, Master in Strategy & Management of International Business (SMIB), 2020-2023).

Strategy and Tactics: From military to trading

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Strategy and Tactics: From military to trading

Clara PINTO

In this article, Clara PINTO (ESSEC Business School, Master in Strategy & Management of International Business (SMIB), 2020-2023) shares her insights as a former military analyst on strategy and tactics applied to trading.

IRSEM: The Institute for Strategic Research at the Military School

Created in 2009, IRSEM is the strategic research institute of the French Ministry of Armed Forces and operates under the supervision of the Directorate General for International Relations and Strategy (DGRIS) operating under the umbrella of the Ministry for the Armed Forces. IRSEM is home to a staff of about forty civilian and military permanent researchers. The Institute seeks to foster the emergence of a new generation of researchers specialized in security and defense issues.

Logo of IRSEM.
Logo of IRSEM
Source: IRSEM.

From military to Finance: Strategy and tactics applied to trading

My experience as an analyst in a military Think tank required me to learn the basics of military strategy and tactics. The distinction between strategy and tactics is frequently stated as “strategy is long-term, whereas tactics are short-term.” While the two terms may exhibit similar qualities at times, it is an erroneous and partial explanation of their definitions.

Chinese General Sun Tzu wrote the difference this way: “All the men can see the tactics I use to conquer, but what none can see is the strategy out of which great victory is evolved.”

However, even if strategy and tactics are also used in business, their principles still apply in the trading context. Indeed, successful trading requires a solid understanding of both strategy and tactics. In this article, we will explore the differences between these two concepts and how they can be applied to trading.

Strategy refers to a long-term plan that outlines how you will achieve your trading goals. It involves identifying your objectives, assessing the risks and opportunities in the market, and deciding on a plan of action. A good trading strategy should be flexible enough to adapt to changing market conditions, but also structured enough to provide a clear path forward. One key aspect of a trading strategy is risk management. This involves identifying the potential risks associated with a particular trade and taking steps to mitigate them. This might involve setting stop-loss orders to limit potential losses or diversifying your portfolio to reduce the overall risk. A good trading strategy should also take into account the amount of capital you have available to trade with, as well as your risk tolerance and investment goals.

Tactic, on the other hand, refers to the specific actions you take to implement your trading strategy. These might include analyzing technical indicators to identify trends and patterns to assess the value of a particular asset. A successful trading tactic will depend on a number of factors, including the specific asset you are trading, and the current market conditions.

Ultimately, the success of your trading will depend on how well you are able to combine strategy and tactics. A strong strategy will provide a clear framework for making decisions and managing risk, while effective tactics will allow you to execute that strategy in a way that maximizes your returns. In order to develop a successful trading strategy, it is important to conduct thorough research and analysis of the markets you are interested in. This might involve studying historical market trends, analyzing economic and political factors that could impact the markets, or keeping up to date with news and events that could affect the value of specific assets. It is also important to remember that trading involves a degree of risk, and no strategy or tactic can guarantee success. However, by developing a strong strategy and using effective tactics to execute that strategy, you can improve your chances of making profitable trades over the long term.

In conclusion, strategy and tactics are both essential components of successful trading. A strong trading strategy provides a clear framework for decision-making and risk management, while effective tactics allow you to execute that strategy in a way that maximizes your returns. By combining careful research and analysis with disciplined execution, you can increase your chances of success in the complex and ever-changing world of trading.

Why should I be interested in this post?

Unfortunately, the concepts of strategy and tactics are often mixed up and not entirely understood. However, they provide a good framework to trade in the long term and structure your choices in the decision-making process.

Related posts on the SimTrade blog

   ▶ Momentum Trading Strategy

Useful resources

IRSEM – The Institute for Strategic Research

About the author

The article was written in March 2023 by Clara PINTO (ESSEC Business School, Master in Strategy & Management of International Business (SMIB), 2022-2023).

The business of financial indexes

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The business of financial indexes

Nithisha CHALLA

In this article, Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management, 2021-2023) explains the business of financial indexes.

Introduction

Indexes are frequently used in the financial sector to measure the evolution of market prices for a set of financial assets over time. These sets of assets can be defined to represent an asset class, country or geographical zone, or sector of the economy, and provide a comprehensive and accurate overview of the market.

Financial indexes serve as a benchmark for assessing the performance of an investor’s asset portfolio and give investors a way to monitor the performance of a given set of assets. By using financial indexes, investors can gain knowledge of market trends and conditions and make informed investment decisions. Index providers are responsible for creating and maintaining financial indexes.

Financial indexes can be developed to track particular geographical areas or market segments and can be created for a variety of asset classes, including equities, bonds, commodities, and currencies. Financial indexes are primarily provided by specialized companies with experience in data compilation and index value calculation, such as S&P Dow Jones Indices, MSCI, and FTSE Russell. Overall, the business of financial indexes is a critical component of the financial industry, providing valuable data and insights to investors.

Key Players

Index providers

An index provider is a specialized business that specializes in developing and computing market indices as well as licensing its intellectual property to be used as the foundation of passive products. The index providers are essential to the investment professionals in charge of looking after these assets because they provide reliable data distribution, sound index construction, and strict index maintenance. The primary activities of an index provider are product development, licensing, distribution, and related service and support.

Index Industry Association (IIA)

The production of indexes has become an industry! And every industry has a professional association. The index industry is no exception. The Index Industry Association (IIA) was founded in 2012. Some of the founding members are MSCI and S&P Dow Jones Indexes.

As stated on the IIA website, the association mandate is “to educate investors on the attributes and role of indexes within the investment process, to advocate for the interests of index users and providers worldwide, and to push for industry standards of best practice, independence and transparency”.

Business models

Index providers typically employ one of the following business models to make money from their indexes: licensing, creating index-linked products, getting charged for index inclusion, and selling data for index-related research and analysis.

Licensing

Index providers make money by licensing financial institutions like asset managers, banks, and insurance companies to use their indexes. These financial institutions pay a fee to the index provider for the right to use the indexes as a benchmark for their investment products, such as exchange-traded funds (ETFs) and index funds.

Creation of index-linked products

Index providers make money by developing their own index-linked products, such as index funds and ETFs. The investors that are invested in the product pay a management fee to the index provider.

Selling data

By selling the data that has been produced from the history, research, and analysis, the index providers make money.

Regulation of indexes

Index providers build and maintain indexes. In order to ensure that the index accurately reflects the performance of the market or sector it is meant to represent, they are in charge of defining the methodology used to construct the index, choosing the stocks or bonds included in the index, and performing routine index rebalancing.

Beyond the activity of index providers, financial authorities play a role to authorize indexes. The main objective of authorization is to safeguard investors who use the index as a benchmark for their investment decisions and to make sure that the index accurately reflects the performance of the market or sector it is meant to represent. In the United States, the US Securities and Exchange Commission (SEC) has the power to approve specific indexes that serve as the foundation for exchange-traded funds (ETFs) and other investment products. This is done to make sure that these products operate in the best interests of investors and are compliant with SEC regulations.

Why should I be interested in this post?

A wide range of professionals, including portfolio managers, investment advisors, and financial analysts, use financial indexes, which are a crucial part of the financial sector. Financial indexes change over time to take into account adjustments to the economy and market conditions.

You can stay on top of the curve and adjust to changes in the industry by staying informed of the most recent financial index developments. So, in my opinion, studying the business of financial indexes can give business students useful skills and knowledge that they can use in a variety of fields and jobs.

Related posts on the SimTrade blog

About financial indexes

   ▶ Nithisha CHALLA Financial indexes

   ▶ Nithisha CHALLA Calculation of financial indexes

Examples of financial indexes

   ▶ Nithisha CHALLA The S&P 500 index

   ▶ Nithisha CHALLA The Euro Stoxx 50 index

   ▶ Nithisha CHALLA The FTSE 100 index

   ▶ Nithisha CHALLA The CSI 300 index

   ▶ Nithisha CHALLA The Nikkei 225 index

Useful resources

Index Industry Association (IIA)

S&P Global Who’s Behind the Index?

Committee for Economic Development of The Conference Board (CED) The Financial Index Industry

K&L Gates SEC solicits comments on whether index providers, model portfolio providers, and pricing services are investment advisers: seeking a problem for a “solution”

About the author

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