The Russell 2000 index

The Russell 2000 index

Nithisha CHALLA

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

The Russell 2000 index

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

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

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

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

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

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

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

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

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

Calculation of the Russell 2000 index value

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

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

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

Market Capitalization Index value

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

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

Market Capitalization Weighted Index Weight

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

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

Use of the Russell 2000 index in asset management

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

Benchmark for equity funds

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

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

Financial products around the Russell 2000 index

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

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

Historical data for the Russell 2000 index

How to get the data?

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

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

Yahoo! Finance
Source: Yahoo! Finance.

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

R program

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

Download R file

Data file

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

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

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

Evolution of the Russell 2000 index

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

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

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

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

Summary statistics for the Russell 2000 index

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

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

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

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

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

Statistical distribution of the Russell 2000 index returns

Historical distribution

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

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

Gaussian distribution

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

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

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

Risk measures of the Russell 2000 index returns

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

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

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

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

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

Why should I be interested in this post?

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

Related posts on the SimTrade blog

About financial indexes

   ▶ Nithisha CHALLA Financial indexes

   ▶ Nithisha CHALLA Calculation of financial indexes

   ▶ Nithisha CHALLA The business of financial indexes

   ▶ Nithisha CHALLA Float

About other US financial indexes

   ▶ Nithisha CHALLA The DJIA index

   ▶ Nithisha CHALLA The S&P 500 index

   ▶ Nithisha CHALLA The NASDAQ index

   ▶ Nithisha CHALLA The Wilshire 5000 index

About portfolio management

   ▶ Youssef LOURAOUI Portfolio

   ▶ Jayati WALIA Returns

About statistics

   ▶ Shengyu ZHENG Moments de la distribution

   ▶ Shengyu ZHENG Mesures de risques

Useful resources

Wikipedia Russell indexes

Finance Strategists Defining Russell 2000 Index

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

Motley Fool 10 of the largest Russell 2000 companies

Academic research about risk

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

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

Data

Yahoo! Finance

Yahoo! Finance Data for the Russell 2000 index

About the author

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

The Consumer Confidence Index

The Consumer Confidence Index

Jianen HUANG

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

What is CCI

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

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

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

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

Regional Differences

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

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

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

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

Limitations of CCI

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

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

Conclusion

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

Related posts on the SimTrade blog

   ▶ Bijal GANDHI Economic Indicators

   ▶ Bijal GANDHI Consumer Confidence Index

Useful resources

National Bureau of Statistics China Consumer Confidence Index

The Conference Board US Consumer Confidence Index

European Union EU Consumer Confidence Index

About the author

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

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

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

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

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

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

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

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

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

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

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).

The S&P 500 index

The S&P 500 index

Nithisha CHALLA

In this article, Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management, 2021-2023) presents the S&P 500 index and details its characteristics.

The S&P 500 index

The performance of 500 major capital companies listed on the US stock exchange is summarized by a financial index called the S&P 500 index. The stocks of the S&P 500 index are traded on the New York Stock Exchange and NASDAQ, which are the two major stock exchanges in the United States of America. This index serves as a benchmark for the American stock market and investors use it to monitor the performance of the market. The selection of 500 stocks only is deemed enough to represent the stock market (in terms of market capitalization).

The S&P 500 index was first established by Standard & Poor’s, a provider of financial services, on March 4, 1957. In order to provide a comprehensive assessment of the U.S. stock market, the index consists of a range of large-capital businesses from various industries and sectors. The S&P 500 index is currently managed by the index provider S&P Dow Jones Indices (a division of S&P Global).

Who makes the shortlist of the index and how the field is narrowed down? The S&P Dow Jones Indices oversees the selection procedure for index inclusion. The public float, financial viability, market capitalization, and a diverse representation of the US stock market—including technology, healthcare, financials, consumer goods, etc.—are some of the key criteria used to define the composition of the index.

How is the S&P 500 index represented in trading platforms and financial websites? The ticker symbol used in the financial industry for the S&P 500 index is “SPX”.

Table 1 gives the Top 10 stocks in the S&P 500 index in terms of market capitalization as of January 31, 2023.

Table 1. Top 10 stocks in the S&P 500 index.
Top 10 stocks in the S&P 500 index
Source: computation by the author (data: YahooFinance! financial website).

Table 2 gives the sector representation of the S&P 500 index in terms of number of stocks and market capitalization as of January 31, 2023.

Table 2. Sector representation in the S&P 500 index.
Sector representation in the S&P 500 index
Source: computation by the author (data: YahooFinance! financial website).

Calculation of the S&P 500 index value

The S&P 500 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 S&P 500 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 to compute the S&P 500 index is given by

SP500 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 S&P 500 index, the weight of asset k is given by formula can be rewritten as

SP500 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.

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.

Note that there are two versions of the S&P 500 index: one which includes the performance of the company as well as the dividends the companies pay (so it is a dividend included index), and another one which only considers the performance of the company but does not consider the dividends.

Use of the S&P 500 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 an useful index to measure the overall performance of the market.

Benchmark for equity funds

There are a number of indices used as a benchmark for equity funds but the S&P 500 index particularly focuses on the large capped companies in the US market. It is mainly differentiated by the asset class the index is focusing on and the investment strategies followed by the companies. For Example: DJIA uses price weighted stock strategy for the top 30 blue chip companies, whereas the NASDAQ Composite Index uses market capitalization-weighted index of more than 3,000 stocks in the NASDAQ Composite.

Financial products around the S&P 500 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 specific sector related indices which provide exposure to the S&P 500 index. Other financial products would be mutual funds, futures and options etc.

Historical data for the S&P 500 index

How to get the data?

The S&P 500 index is the most common index used in finance, and historical data for the S&P 500 index can be easily downloaded from the internet.

For example, you can download historical data for the S&P 500 index from December 30, 1927 on Yahoo! Finance (the Yahoo! code for S&P 500 index is ^GSPC).

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 S&P 500 index.

Download R file

Data file

The R program that you can download above allows you to download the data for the S&P 500 index from the Yahoo! Finance website. The database starts on December 30, 1927. It also computes the returns (logarithmic returns) from closing prices.

Table 3 below represents the top of the data file for the S&P 500 index downloaded from the Yahoo! Finance website with the R program.

Table 3. Top of the data file for the S&P 500 index.
Top of the file for the S&P 500 index data
Source: computation by the author (data: Yahoo! Finance website).

Summary statistics for the S&P 500 index

The R program that you can download above also allows you to compute summary statistics about the returns of the S&P 500 index.

Table 4 below presents the following summary statistics estimated for the S&P 500 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 S&P 500 index.
 Summary statistics for the S&P 500 index
Source: computation by the author (data: Yahoo! Finance website).

Evolution of the S&P 500 index

Figure 1 below gives the evolution of the S&P 500 index from December 30, 1927 to December 30, 2022 on a daily basis.

Figure 1. Evolution of the S&P 500 index.
Evolution of the S&P 500 index
Source: computation by the author (data: Yahoo! Finance website).

Figure 2 below gives the evolution of the S&P 500 index returns from December 30, 1927 to December 30, 2022 on a daily basis.

Figure 2. Evolution of the S&P 500 index returns.
Evolution of the S&P 500 index return
Source: computation by the author (data: Yahoo! Finance website).

Statistical distribution of the S&P 500 index returns

Historical distribution

Figure 3 represents the historical distribution of the S&P 500 index daily returns for the period from December 30, 1927 to December 30, 2022.

Figure 3. Historical distribution of the S&P 500 index returns.
Historical distribution of the daily S&P 500 index returns
Source: computation by the author (data: Yahoo! Finance website).

Gaussian distribution

The Gaussian distribution (also called the normal distribution) is a parametric distribution with two parameters: the mean and the standard deviation of returns. We estimated these two parameters over the period from December 30, 1927 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 S&P 500 index daily returns with parameters estimated over the period from December 30, 1927 to December 30, 2022.

Figure 4. Gaussian distribution of the S&P 500 index returns.
Gaussian distribution of the daily S&P 500 index returns
Source: computation by the author (data: Yahoo! Finance website).

Risk measures of the S&P 500 index returns

The R program that you can download above also allows you to compute risk measures about the returns of the S&P 500 index.

Table 5 below presents the following risk measures estimated for the S&P 500 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 S&P 500 index.
Risk measures for the S&P 500 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 S&P 500 index. The performance of 500 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 S&P 500 index. Management students can assess the performance of their own investments and those of their organization by comprehending the S&P 500 index and its components. Last but not least, a lot of businesses base their mutual funds and exchange-traded funds (ETFs) on the S&P 500 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 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 Historical data for the S&P 500 index

Data: Bloomberg

Bloomberg

Bloomberg Data for the S&P 500 index

About the author

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

Calculation of financial indexes

Calculation of financial indexes

Nithisha CHALLA

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

Introduction

A stock market index keeps tabs on the gains and losses made by a specific selection of stocks or other assets. In other words, the index determines how share prices for various companies have changed. The performance of a market index can be quickly evaluated to ascertain the state of the stock market. It also serves as a template for financial institutions to use when creating index funds and exchange-traded funds (ETFs).

Definition

What is an index? In financial markets, there are many sectors, segments and business lines, and if you have to statistically measure the performance of these sectors we need a reference which is called an index. Simply, it is a group of securities or financial instruments which represents the performance of a specific segment of the market.

Calculation

Then the index value has to be calculated with a specific formula. There are different calculation methods for financial indexes: price-weighted index, market-capitalization-weighted index, equal-weighted index and fundamentals-weighted index.

The general formula for a financial index is given by

Index value

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

Note: the index It at time t is divided by the value of the index at the beginning I0 and multiplied by 100.

Price-Weighted Index

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.

In a price-weighted index, the higher-priced stocks move the index more than the lower-priced stocks.

The most popular price-weighted index in the world is likely the Dow Jones Industrial Average (DJIA). It consists of 30 different stocks in the US market.

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

Fundamental-weighted Index

A fundamental-weighted index is calculated based on specific financial metrics, such as revenue or earnings, rather than market capitalization or price. The weightings of each asset in the index are determined by its financial metrics, so that the companies with the strongest financial performance have the greatest impact on the overall performance of the index.

The formula for a fundamental-weighted index is given by

Fundamental 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, Fk the financial metric of asset k, and t the time of calculation of the index.

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

Fundamental Weighted Index Weight

which clearly shows that the weight of each asset in the index is the value of the fundamental variable of the asset divided by the sum of the values of the fundamental variable of all assets.

Equal-weighted Index

An equal-weighted index is calculated by dividing the total value of the index by the number of securities in the index, and then allocating the same weighting to each security. This method gives each security an equal influence on the overall performance of the index, regardless of its market capitalization.

The formula for an equal-weighted index is given by

Equal Weighted Index value

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

Equal Weighted Index Weight

Which clearly shows that the weight of each asset in the index, one divided by the number of assets, is constant over time.

Examples of financial indexes

The Dow Jones Industrial Average: an equal-weighted index

The Dow Jones Industrial Average, or DJIA (Dow), was the first index, appearing in 1896. The 30 largest and most prosperous American companies make up the Dow. The experts have carefully chosen these businesses to represent a wide range of industries. Companies with higher prices are given more weight in the Dow. Even though it is the most established and performs similarly to the S&P 500, it is occasionally thought to be less indicative of the entire market.

The S&P 500 index: a market-capitalization-weighted index

S&P 500 – The performance of 500 of the biggest American publicly traded companies is measured. Some people think the S&P 500, which is weighted by market capitalization and has a wider scope, is the best indicator of the American stock market. Because of this, the S&P 500’s average is most significantly impacted by the companies with the highest total market value.

Why should I be interested in this post?

Learning about the calculation of financial indices is important to understand the behavior of an index. It can assist you in managing risk in your portfolio, understanding the overall performance of various markets, and making wise investment decisions. Financial indices can offer insightful data on how various markets, sectors, and economies are performing. Investors can determine whether their investments are outperforming or underperforming the overall market by comparing the returns to the returns of a relevant financial index.

Related posts on the SimTrade blog

   ▶ All posts about Financial techniques

   ▶ Nithisha CHALLA Financial indexes

   ▶ Youssef LOURAOUI Smart Beta strategies: between active and passive allocation

Useful resources

Weight priced index Indice

Equity Indexes Indice

Security market index Indice

Value weighted index Indice

Evolution of indexes Indice

About the author

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

Financial indexes

Financial indexes

Nithisha CHALLA

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

Definition

What is an index? An index can be defined as a measure of a quantity.

An index is a measure of quantity that can be defined as the ratio between the value of the quantity during a current period and its value during a base period. The use of a ration makes it easy to calculate and compare changes in one or more quantities between two given periods. This ratio is often multiplied by 100 or 1,000. 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.

History

The Dow Jones Industrial Average was first created in 1896 by Charles Dow, a co-founder of the Dow Jones Company, and is widely regarded as the first index. Who is creating the index? The Dow Jones Industrial Average, which included 12 companies at the time that were emblematic of the US Market. Currently, there are 30 companies that make it up even though none of the original 12 companies are still included. As interest in indices increased, financial publications like the Financial Times or exchange owners like the Deutsche Borse in Germany developed their own equity indices, while investment banks took the lead in developing indices for bonds. Since then, numerous other financial indexes have been developed, including the NASDAQ Composite, FTSE 100, Nikkei 225, S&P 500, and others.

Evolution over time

Stock market indexes were initially just simple arithmetic averages of the prices of a small number of chosen stocks; they did not take the entire market into account. The daily averages were first published in the newspapers in the 1800s. Later, they began to use market capitalization weighting, which was well-liked because it assigned weights based on the size of the company. Following that, various indexes based on sectors, nationalities, etc. were assigned. A significant trend recently has been the use of passive index funds and the addition of ESG criteria to the indexes.

Providers of financial indexes

Financial indexes are typically provided by financial data and research firms. As mentioned earlier, though there are several providers in the financial services industry, there are few most prominent index providers – S&P Global, MSCI, FTSE Russell, Dow Jones Indices and Nasdaq. With a combined market share of about 90% for equity indexes, these firms are thought to dominate the world index market.

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 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”.

Composition of an index

The composition of an index is a crucial factor in determining its representation, and it is important for investors to understand the criteria used by the index provider to select the assets included in the index, as well as the weightings assigned to each asset. The composition of an index is designed to represent a specific market or sector, and the index provider selects the assets to be included based on specific criteria, such as market capitalization, liquidity (float), and sector representation.

There are several steps in the process of creating an index. As we all know, index providers use a variety of companies to create the index, but how are they selected? Specific eligibility requirements must be met, such as the size of the business and the industry it belongs to, etc. After the eligible companies have been narrowed down, they are properly evaluated before being included in the index. This evaluation includes looking at the company’s earnings, market capitalization, and other factors. Additionally, they conduct index balancing with regard to various industries, segments, etc. Last but not least the index’s potential market impact is cross-checked as the index stands as a benchmark for the investors to make decisions. Different index providers may have different selection criteria and processes.

The index provider regularly reviews and updates the composition of the index to ensure that it remains representative of the market or sector it is tracking.

For example, the S&P 500 index is designed to represent the performance of the U.S. stock market, and the securities included in the index are chosen based on market capitalization, liquidity, and sector representation. Since each security’s weight in the index is based on its market capitalization, the largest and most powerful corporations have the biggest effects on the index’s overall performance.

Calculation of financial indexes

Once the index provider has chosen the assets to be included in the index based on predetermined criteria, such as market capitalization, liquidity, and sector representation. Then the index value has to be calculated with a specific formula. There are different calculation methods for financial indexes: price-weighted index, market-capitalization-weighted index, equal-weighted index and fundamentals-weighted index.

Classifications of financial indexes

By having a solid understanding of the various classifications of financial indexes, investors can select the most suitable indexes for their investment goals and strategies. Market coverage, calculation method, geographic region, asset class, investment approach, and security type are used to categorize financial indexes.

The criteria for classifying financial indexes include:

  • Asset class: equity, bond, crypto, etc.
  • Geography: US, Asia-Pacific, Europe
  • Sector: Information Technology, Health Care, Financials, Consumer Discretionary, Communication Services, Industrials, Consumer Staples, Energy, Utilities, Real Estate, and Materials.
  • Weighting methodology: price-weighted, market-capitalization-weighted, float-adjusted market-capitalization-weighted, fundamental-weighted
  • Objectives: market representation, risk factor representation

Most popular financial indexes

The Dow Jones Industrial Average

The Dow Jones Industrial Average (DJIA) was established in 1896, is the country’s first stock market index. Thirty large-cap companies that are leaders in their fields are included in this price-weighted index. The index is frequently used as a gauge for the American stock market and the overall economy.    ▶ More about the DJIA index

S&P 500

The S&P 500 index is a market capitalization-weighted index that monitors the progress of 500 large-cap U.S. businesses operating in various industries. It was established in 1957, and many people consider it to be one of the most significant benchmarks for the American stock market. The index is widely used as a benchmark by fund managers and investors and is frequently used as a stand-in for the overall health of the American economy.    ▶ More about the S&P 500 index

Nasdaq Composite

Composed of all the companies listed on the Nasdaq stock market, the Nasdaq Composite is a market capitalization-weighted index. It was founded in 1971 and is renowned for the prominence of technology firms, even though it also includes businesses from the consumer goods, healthcare, and finance sectors. The index is frequently used as a yardstick for growth and technology stock performance.    ▶ More about the Nasdaq Composite index

FTSE 100

The performance of the top 100 companies listed on the London Stock Exchange is tracked by the FTSE 100, a market capitalization-weighted index. Since its creation in 1984, it has gained widespread recognition as the top benchmark for the UK stock market. Companies from the financial, energy, and mining sectors make up the majority of the index, and each company is weighted according to its market capitalization.    ▶ More about the FTSE 100 index

MSCI World

The MSCI World Index tracks the performance of businesses in 23 developed markets around the world, including the United States, Canada, Japan, and Europe. It is a market capitalization-weighted index. It was developed in 1969 and is frequently used as a yardstick for performance in the global equity market. The weighting of each company in the index, which consists of more than 1,600 large- and mid-cap stocks, is determined by its market capitalization.

Health Care Select Sector Index

The Health Care Select Sector Index is based on the companies of the S&P 500’s health care sector. It was established in 1998 with the purpose of monitoring the performance of businesses involved in the health care sector, such as those producing pharmaceuticals, biotechnology, medical devices, and healthcare providers.

Use of indexes in finance

Financial indexes play an important role for market participants like investors, traders, and asset managers. Some of the ways indexes are used in finance include:

Gauges of the market evolution

Indexes can offer insightful information about the state of the financial markets. An index helps to measure the market returns of a given set of securities.

The best part of the stock index is that just by tracking the simple indicator we get a general idea of how the stock market is performing. A stock index clearly shows how the market is performing, or at least the market that it represents, despite the fact that individual stocks may perform differently, making it challenging to determine whether the market is strong or weak.

Benchmarks

Indexes are frequently used as a benchmark to assess the performance of investment portfolios, especially actively managed portfolios.

Proxies for modeling

In academic studies, indexes are used as proxies for the market portfolio to capture systematic risk and to compute risk-adjusted performance.

Portfolio Asset allocation

Because they offer a way to gain exposure to particular asset classes, industries, or geographic areas, indices serve as the foundation for asset allocation strategies.

Risk management

Indexes can assist investors in comprehending the risks related to particular asset classes or geographical areas.

Building of investment vehicles

Exchange-traded funds (ETFs), mutual funds, options and structured products, among others, use indexes as their underlying assets. These investment vehicles make it easy and affordable for investors to become exposed to the index’s performance.

Rebalancing

Some indexes imply frequent and even continuous rebalancing (buying and selling assets). For example, for a fund tracking an equally-weighted index, the fund manager will have to sell assets whose price increased and buy assets whose price decreased.

Change in index composition and impact on asset prices

When an asset is included in an index, its price usually increases as fund managers need to buy it to include it in their portfolio. Conversely, when an asset is excluded from an index, its price usually decreases as fund managers need to sell it to exclude it from their portfolio.

Empirical results confirming these propositions can be found in a study by McKinsey (2004). The prices of the assets included in a financial index may change as a result of changes in the composition of the index over time.

It is crucial to remember that depending on the specifics of the change, the effect of a change in index composition on asset prices may be either short-lived or long-lasting. The effect of a change in index composition on asset prices can also be challenging to forecast because it depends on a variety of variables, such as investor sentiment, fund flows, and market sentiment.

Link with academic research

The performance of a particular sector of the stock market, such as large-cap stocks, small-cap stocks, or a specific sector or industry, is measured by an equity index, a type of financial index.

On the other hand, market factors are factors that account for a significant amount of the variation in stock prices. Market variables include both macroeconomic ones like interest rates and GDP and market-specific ones like market volatility and liquidity.

The relationship between equity indexes and market factors is that changes in market factors can have an impact on equity index performance, and equity index performance can be influenced by market factor changes. For instance, adjustments in interest rates may have an effect on the performance of the stock market as a whole and, consequently, on the performance of an equity index that monitors the stock market. Factor-based indexes that seek to capture the performance of particular market factors, such as value, growth, and momentum, have been developed as a result of research into the effects of market factors on equity indexes. These factor-based indexes can be employed to examine the effects of market factors on the performance of equity indexes and to base investment choices on the exposure to market factors.

Why should I be interested in this post?

I frequently come across news-related stocks, bonds, and indices in publications like newspapers, financial journals, and business magazines. We require a fundamental understanding of indices in order to even understand what is happening in the business world. It’s also crucial to have a thorough understanding of markets and financial indices because we need to comprehend these financial indices in order to assess a company’s performance and compare it to previous years.

Related posts on the SimTrade blog

   ▶ All posts about Financial techniques

About financial indexes

   ▶ Nithisha CHALLA Calculation of financial indexes

   ▶ Nithisha CHALLA The business of financial indexes

   ▶ Nithisha CHALLA Float

Examples of financial indexes

   ▶ Nithisha CHALLA The DJIA index

   ▶ Nithisha CHALLA The S&P 500 index

   ▶ Nithisha CHALLA The Nasdaq index

Useful resources

Insee Indice

Russel How are indexes weighted?

Financial Index Industry Presentation of the association

Index Industry Association Presentation of the association

Marc H. Goedhart and Regis Huc (2004) What is stock index membership worth? McKinsey & Company.

About the author

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

Capital Guaranteed Products

Capital Guaranteed Products

Shengyu ZHENG

In this article, Shengyu ZHENG (ESSEC Business School, Grande Ecole Program – Master in Management, 2020-2023) explains how capital guaranteed products are built.

Motivation for investing in capital-guaranteed products

In order to invest the surplus of the firm liquid assets, corporate treasurers take into account the following characteristics of the financial instruments: performance, risk and liquidity. It is a common practice that some corporate investment strategies require that the investment capital should at least be guaranteed. The sacrifice of this no-loss guarantee is limited return in case of appreciation of the underlying asset price.

Capital-guaranteed (or capital-protected) products are one of the most secure forms of investment, usually in the form of certificates. They provide a guarantee that a specified minimum amount (usually 100 per cent of the issuance price) will be repaid at maturity. They are suitable particularly for risk-averse investors who wish to hold the products through to maturity and are not prepared to bear any loss that might exceed the level of the guaranteed repayment.

Performance

Let us consider a capital-guaranteed product with the following characteristics:

Table 1. Characteristics of the capital-guaranteed products

Notional amount EUR 1,000,000.00
Underlying asset CAC40 index
Participation rate 40%
Minimum amount guarantee 100% of the initial level
Effective date February 01, 2022
Maturity date July 30, 2022

We also have the following information about the market:

Table 2. Market information

Risk-free rate (annual rate) 8%
Implied volatility (annualized) 10%

In case of depreciation of the underlying index, the return of the product remains zero, which means the original capital invested is guaranteed (or protected). In case of appreciation of the underlying index, the product only yields 40% of the return of the underlying index. The following chart is a straightforward illustration of the performance structure of this product.

Performance of the capital guaranteed product

Construction of a capital guaranteed product

We can decompose a capital-guaranteed product into three parts:

  • Investment in the risk-free asset that would yield the guaranteed capital at maturity
  • Investment in a call option that guarantees participation in the appreciation of the underlying asset
  • Margin of the bank

Decomposition of the capital guaranteed product

Investment in the risk-free asset

The essence of the capital guarantee is realized by investing a part of the initial capital in the risk-free asset and obtaining the amount of the guaranteed capital at maturity. Given the amount of the capital to be guaranteed and the risk-free rate, we can calculate the amount to be invested in risk-free asset: 1,000,000/(1+0.08)^0.5 =962,250.45 €

Investment in the call option

To realize the upside exposure, call options are a perfect vehicle. With a notional amount of 1,000,000 € and a maturity of 6 months, an at-the-money call option would cost 41,922.70 € (calculated with the Black-Scholes-Merton formula). Since the participation rate is 40%, the amount to be invested in the call option would be 16,769.08 € (= 40% * 41,922.70 €).

Margin of the bank

The margin of the bank is equal to the difference between the original capital and the two parts of the investment. In this case, the margin is 20,980.47 € (= 1,000,000.00 € – 962,250.45 € – 16,769.08 €)
If we compress the margin, there would be more capital available to invest in the call option, thus increasing the participation rate. In the case of zero margin, we obtain the maximum participation rate. In this scenario, the maximum participation rate would be 90.05% (= (1,000,000.00 € – 962,250.45 €) / 41,922.70 €).

Sensitivity to variations of the marketplace

Considering the two parts of the investment constituting the capital-guaranteed product, we can see that the risk-free rate and the volatility of the underlying asset are the two major factors influencing the pricing of this product. Here let us focus on the maximum participation rate as a proxy of the value of the product to the buyer of the product.

The effect of the risk-free rate could be ambiguous at the first glance. On one hand, if the risk-free rate rises, there needs to be less capital invested in the risk-free asset and there would be therefore more capital to be placed in purchasing the call options. On the other hand, if the risk-free rate rises, the call option value rises as well. With the same amount of capital, fewer call options could be purchased. However, the largest portion of the original capital is invested in the risk-free asset and the impact on this regard is more important. Overall, a rising risk-free rate has a positive impact on the participation rate.

The effect of the volatility of the underlying asset, however, is clear. Rising volatility has no impact on the risk-free investment in the framework of our hypotheses. It, however, raises the value of the call options, which means that fewer options could be purchased with the same amount of capital. Overall, rising volatility has a negative impact on the participation rate.

Statistical distribution of the return

The statistical distribution of the return of the instrument is mixed by two parts: the discrete part equal to 0 corresponding to the case of depreciation of the underlying asset; and the continuous part of positive return. Based on a Gaussian assumption for the statistical distribution, we can calculate the probability mass of the depreciation of the underlying asset is 33.70%. In the continuous part, the return follows a Gaussian statistical distribution, with a mean equal to the periodic return over the participation rate and a standard deviation equal to periodic implied volatility over the participation rate, if the Gaussian assumption prevails.

Statistical distribution of the return of the capital guaranteed product

Risks and constraints

Liquidity risk

Being exotic financial instruments, capital-guaranteed products are not traded in standard exchanges. By construction, these products can normally only be redeemed at maturity and therefore are less liquid. There could be, however, early redemption clauses involved to mitigate the long-term liquidity risks. Investors should be aware of their liquidity needs before entering into a position in this product.

Counterparty risk

Similar to all other over-the-counter (OTC) transactions, there is no mechanism such as a central clearing counterparty (CCP) to ensure the timeliness and integrity of due payments. In case of financial difficulty including the bankruptcy of the issuer, the capital guarantee would be rendered worthless. It is therefore highly recommended to enter into such transactions with issuers of higher ratings.

Limited return

It is worth noting that capital-guaranteed products have weak exposure to the appreciation of the underlying asset. In this case, for a probability of 33.70%, there would be a return of zero, which is lower than investing directly in the risk-free security.

In order to mitigate this limit, the issuer could modify the level of guarantee to a lower level than 100%. This allows the product to have more exposure to the upside movement of the underlying asset with a relatively low risk of capital loss. To realize this involves entering positions of out-of-the-money call options.

Taxation and fees

In many countries, the return of capital-guaranteed products is considered as ordinary income, instead of capital gains or tax-advantaged dividends. For example, in Switzerland, it is not recommended to buy such a product with a long maturity, since the tax burden, in this case, could be higher than the “impaired” return of the product.

Moreover, fees for such products could be higher than exchange-traded funds (ETFs) or mutual funds. This part of investment cost should also be taken into account in making investment decisions.

Download the Excel file to analyze capital-guaranteed products

You can find below an Excel file to analyze capital-guaranteed products.

Download Excel file to analyze capital guaranteed products

Why should I be interested in this post?

As a family of investments that is often used in corporate treasury management, it is important to understand the mechanism and structure of capital-guaranteed products. It would be conducive for future asset managers, treasurer managers, or structurers to make the appropriate and optimal investment decisions.

Related posts on the SimTrade blog

   ▶ All posts about Options

   ▶ Shengyu ZHENG Barrier options

   ▶ Shengyu ZHENG Reverse convertibles

Resources

Books

Cox J. C. & M. Rubinstein (1985) “Options Markets” Prentice Hall.

Hull J. C. (2005) “Options, Futures and Other Derivatives” Prentice Hall, 6th edition.

Articles

Black F. and M. Scholes (1973) The Pricing of Options and Corporate Liabilities Journal of Political Economy, 81(3): 637-654.

Lacoste V. and Longin F. (2003) Term guaranteed fund management: the option method and the cushion method Proceeding of the French Finance Association, Lyon, France.

Merton R. (1974) On the Pricing of Corporate Debt Journal of Finance, 29(2): 449-470.

Websites

longin.fr Pricer for standard equity options – Call and put

Euronext www.euronext.com: website of the Euronext exchange where the historical data of the CAC 40 index can be downloaded

Euronext CAC 40 Index Option: website of the Euronext exchange where the option prices of the CAC 40 index are available

Six General information about capital protection without a cap: website of the Swiss stock exchange where information of various financial products are available.

About the author

The article was written in February 2023 by Shengyu ZHENG (ESSEC Business School, Grande Ecole Program – Master in Management, 2020-2023).

Understanding the Order Book: How It Impacts Trading

Understanding the Order Book: How It Impacts Trading

Federico De ROSSI

In this article, Federico DE ROSSI (ESSEC Business School, Master in Strategy & Management of International Business (SMIB), 2020-2023) talks about the order book and explains its role in financial markets.

Introduction

Understanding the order book is critical when it comes to trading in financial markets. In this article, we’ll go over what an order book is and how it affects trading.

What is an order book?

An order book for a stock, currency, or cryptocurrency is a list of buy and sell limit orders for that asset. It shows the pricing at which buyers and sellers are willing to negotiate, as well as the total number of orders available at each price. The order book is a necessary component of every trading platform since it gives a snapshot of the current market situation, of the price of the assets, and of the liquidity of the market. Thus, it is a crucial tool for traders who want to make informed decisions when entering or exiting deals.

How does an order book work?

The order book is a constantly updated record of buy and sell orders. When a trader puts a limit order, it is placed in the order book at the stated price. As a result, there is a two-sided market with distinct prices for buyers and sellers.

The order book is divided into two sections: bid (buy) and ask (sell). All open buy orders are displayed on the bid side, while all open sell orders are displayed on the ask side. The order book also shows the total volume of buy and sell orders at each price level.

In Tables 1 and 2 below, we give below two examples of order book from online brokers. We can see the two parts of the order book side by side: the “Buy” part and the “Sell” part. Every line of the order book corresponds to a buy or sell proposition for a give price (“Buy” or “Sell” columns) and a given quantity (“Volume” columns). For a given line there may be one or more orders for the same price. When there are several orders, the quantity in the “Volume” column is equal to the sum of the quantities of the different orders. Associated to the order book, there is often a chart which indicates the cumulative quantity of the orders in the order book at a given price. This chart gives an indication of the liquidity of the market in terms of market spread, market breadth, and market depth (see below for more explanations about theses concepts).

The “Buy” and “Sell” parts of the order book can be presented side by side (Table 1) or above each other (Tables 2 and 3) with the “Sell” part (in red) above the “Buy” part (in green) as the price limits of the sell limit orders are always higher than the price limits of the buy limit orders.

Table 1. Example of an order book (buy and sell parts presented side by side).
Order book
Source: online broker (Fortuneo).

Table 2. Example of an order book (buy and sell parts presented above each other).
Order book
Source: online broker (Cryptowatch).

Table 3. Example of an order book (buy and sell parts presented next to each other).
Order book
Source: online broker (Binance).

In a typical order book, the buy side is organized in descending order, meaning that the highest buy orders (i.e., the orders with the highest bid prices) are listed first, followed by the lower buy orders in descending order of price. The highest buy order in the book represents the best bid price, which is the highest price that any buyer is currently willing to pay for the asset.

On the other side of the order book, the sell side is organized in ascending order, with the lowest sell orders (i.e., the orders with the lowest ask prices) listed first, followed by the higher sell orders in ascending order of price. The lowest sell order in the book represents the best ask price, which is the lowest price that any seller is currently willing to accept for the asset.

This organization of the order book makes it easy for traders to see the current market depth and the best available bid and ask prices for an asset. When a buy order is executed at the best ask price or a sell order is executed at the best bid price, the order book is updated in real-time to reflect the new market depth and the new best bid and ask prices.

Table 4 below represents how the order book (limit order book) in trading simulations the SimTrade application.

Table 4. Order book in the SimTrade application.
Order book in the SimTrade application

You can understand how the order book works by launching a trading simulation on the SimTrade application.

The role of the order book in trading

As mentioned before, the order book is incredibly significant in trading. It acts as a market barometer, delivering real-time information about the supply and demand for an asset. Traders can also use the order book to determine market sentiment. If the bid side of the order book is strongly occupied, for example, it could imply that traders are optimistic on the asset. Thanks to the data in the order book, traders can get different information out of it.

Three characteristics of the order book

Market spread

The market spread, also known as the bid-ask spread, is the difference between the highest price a buyer is willing to pay for an asset (the bid price) and the lowest price a seller is willing to accept (the ask price) at a particular point in time.

The market spread is a reflection of the supply and demand for the asset in the market, and it represents the transaction cost of buying or selling the asset. In general, a narrow or tight spread indicates a liquid market with a high level of trading activity and a small transaction cost, while a wider spread suggests a less liquid market with lower trading activity and a higher transaction cost.

Market breadth

Market breadth is a measure of the overall health or direction of a market, sector, or index. It refers to the number of individual stocks that are participating in a market’s movement or trend, and can provide insight into the underlying strength or weakness of the market.

Market breadth is typically measured by comparing the number of advancing stocks (stocks that have increased in price) to the number of declining stocks (stocks that have decreased in price) over a given time period. This ratio is often expressed as a percentage or a ratio, with a higher percentage or ratio indicating a stronger market breadth and a lower percentage or ratio indicating weaker breadth.

For example, if there are 1,000 stocks in an index and 800 of them are increasing in price while 200 are decreasing, the market breadth ratio would be 4:1 or 80%. This would suggest that the market is broadly advancing, with a high number of stocks participating in the upward trend.

Market depth

Finally, market depth is a measure of the supply and demand of a security or financial instrument at different prices. It refers to the quantity of buy and sell orders that exist at different price levels in the market. Market depth is typically displayed in a market depth chart or order book.

It can provide valuable information to traders and investors about the current state of the market. A deep market with large quantities of buy and sell orders at various price levels can indicate a liquid market where trades can be executed quickly and with minimal impact on the market price. On the other hand, a shallow market with few orders at different price levels can indicate a less liquid market where trades may be more difficult to execute without significantly affecting the market price.

Analyzing order book data

Data from order books can be used to gain insight into market sentiment and trading opportunities. For example, traders can use the bid-ask spread to determine an asset’s liquidity. They can also examine the depth of the order book to determine the level of buying and selling interest in the asset. Traders can also use order book data to identify potential trading signals. For example, if the bid side of the order book is heavily populated at a certain price level, this could indicate that the asset’s price is likely to rise. On the other hand, if the ask side is heavily populated at a certain price level, it could indicate that the asset’s price is likely to fall.

Benefits of using order book data for trading

Using order book data can provide traders with a number of advantages.

For starters, it can be used to gauge market sentiment and identify potential trading opportunities.

Second, it can assist traders in more effectively managing risk. Traders can identify areas of support and resistance in order book data, which can then be used to set stop losses and take profits.

Finally, it can aid traders in the identification of potential trading signals. Traders can identify areas of potential buying and selling pressure in order book data, which can then be used to enter and exit trades.

How to use order book data for trading

Traders can use order book data to gain a competitive advantage in the markets. To accomplish this, they must first identify areas of support and resistance that can be used to set stop losses and profit targets.

Traders should also look for indications of buying and selling pressure in the order book. If the bid side of the order book is heavily populated at a certain price level, it could indicate that the asset’s price is likely to rise. On the other hand, if the ask side is heavily populated at a certain price level, it could indicate that the asset’s price is likely to fall.

Finally, traders should use trading software to automate their strategies. Trading bots can be set up to monitor order book data and execute trades based on it. This allows traders to capitalize on trading opportunities more quickly and efficiently.

Conclusion

To summarize, the order book is a vital instrument for financial market traders. It gives real-time information about an asset’s supply and demand, which can be used to gauge market mood and find potential trading opportunities. Traders can also utilize order book data to create stop losses and take profits and to automate their trading techniques. Traders might obtain an advantage in the markets by utilizing the power of the order book.

Related posts on the SimTrade blog

▶ Jayna MELWANI The impact of market orders on market liquidity

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

▶ Clara PINTO High-frequency trading and limit orders

▶ Akshit GUPTA Analysis of The Hummingbird Project movie

Useful resources

SimTrade course Trade orders

SimTrade course Market making

SimTrade simulations Market orders   Limit orders

About the author

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

Mesures de risques

Mesures de risques

Shengyu ZHENG

Dans cet article, Shengyu ZHENG (ESSEC Business School, Grande Ecole Program – Master in Management, 2020-2023) présente les mesures de risques basées sur la distribution statistique des rentabilités d’une position de marché, ce qui est une approche possible pour mesurer les risques (comme expliqué dans mon article Catégorie de mesures de risques).

Les mesures de risques basées sur la distribution statistique sont des outils largement utilisés pour la gestion des risques par de nombreux de participants du marché, dont les traders, les teneurs de marché, les gestionnaires d’actifs, les assureurs, les institutions réglementaires et les investisseurs.

Ecart-type / Variance

La variance (moment d’ordre deux de la distribution statistique) est une mesure de la dispersion des valeurs par rapport à la moyenne. La variance est définie par

Var(X) = σ 2 = 𝔼[(X-μ)2]

Par construction, la variance est toujours positive (ou nulle pour une variable aléatoire constante).

En finance, l’écart-type (racine carrée de la variance) mesure la volatilité des actifs financiers. Un écart-type (ou une variance élevée) indique une dispersion plus importante, et donc un risque plus important, ce n’est pas apprécié par les investisseurs qui ont de l’aversion au risque. L’écart-type (ou la variance) est un paramètre clef dans la théorie moderne du portefeuille de Markowitz.

La variance a un estimateur non biaisé donné par

Ŝ2 = (∑ni=1(xi – X̄)2)/(n-1)

Value at Risque (VaR)

La Value at Risque (VaR, parfois traduite comme valeur en enjeu) est une notion classique pour mesurer les risques de perte d’un actif. Elle correspond au montant de perte d’une position qui ne devrait être dépassé qu’avec une probabilité donnée sur un horizon précisé, ou autrement dit, au montant de la pire perte attendue sur un horizon de temps pour un certain niveau de confiance. Elle est essentiellement le quantile de la probabilité donnée de la distribution de perte (rendement négatif).

Dans le langage mathématique, la VaR est définie comme :

VaRα = inf{y ∈ : ℙ[L>y] ≤ 1 – α} = inf{ y ∈ : ℙ[L ≤ y] ≥ α }

VaRα = qα(F) ≔ F(α)

α est la probabilité donnée ; L est une variable aléatoire de montant de perte ; F est la distribution cumulative de perte (rendement négatif), ce qui est continue et strictement croissante ; F est l’inverse de F.

Les organismes financiers se servent assez souvent de cette mesure pour la rapidité et la simplicité des calculs. Toutefois, elle présente certaines lacunes. Elle n’est pas une mesure cohérente. Cela dit, l’addition des VaRs de 2 portefeuilles aurait aucun sens. À part cela, basée sur une hypothèse gaussienne, elle ne tient pas compte de la gravité et la possibilité des évènements extrêmes, tant que les distributions du marché financier sont, pour la plupart, leptokurtiques.

Expected Shortfall (ES)

L’Expected shortfall (ES) est la perte espérée pendant N jours conditionnellement au fait de se situer dans la queue (1 – α) de la distribution des gains ou des pertes (N est l’horizon temporel et α est le niveau de confiance). Autrement dit, elle est la moyenne des pertes lors d’un choc qui est pire que α% cas. L’ES est donc toujours supérieure à la VaR. Elle est souvent appelée VaR conditionnelle (CVaR).

ESα = ∫ 1α (VaRβ(L) dβ)/(1 – α)

En comparaison de la VaR, ES est capable de montrer la gravité de perte dans des cas extrêmes. Ce point est primordial pour la gestion moderne de risques qui souligne la résilience surtout en cas d’extrême.

La VaR a été préférée par les participants du marché financier depuis longtemps, mais les défauts importants présentés ci-dessus ont occasionné des reproches, notamment face aux souvenances des crises majeures. L’ES, rendant compte des évènements extrêmes, tend désormais à s’imposer.

Stress Value (SV)

La Stress Value (SV) est un concept similaire à la VaR. Comme la VaR, la SV est définie comme un quantile. Pour la SV, la probabilité associée au quantile est proche de 1 (par exemple, un quantile de 99.5% pour la SV, en comparaison d’un quantile de 95% pour la VaR habituelle). La SV décrit plus précisément les pertes extrêmes.

L’estimation paramétrique de SV normalement s’appuie sur la théorie de valeurs extrêmes (EVT), alors que celle de VaR est basée sur une distribution gaussienne.

Programme R pour calculer les mesures de risques

Vous pouvez télécharger ci-dessous un programme R qui permet de calculer les mesures de risques d’une position de marché (construite à partir d’indices d’actions ou d’autres actifs).

Mesures_de_risque

Voici est une liste des symboles d’actif (“tickers”) que nous pouvons intégrer dans le programme R.
Download the ticker list to calculate risk measures

Example de calcul des mesures de risque de l’indice S&P 500

Ce programme nous permet de calculer rapidement des mesures de risque pour des actifs financiers dont les données historiques peuvent être téléchargées sur le site Yahoo! Finance. Je vous présente une analyse de risque pour l’indice S&P 500.

En saisissant la date de début comme 01/01/2012 et la date d’arrêté comme 01/01/2022, ce programme est en mesure de calculer les mesures de risque pour toute la période considérée.

Vous trouverez ci-dessous les mesures de risque calculées pour toute la période : la volatilité historique, la volatilité conditionnelle sur les 3 derniers mois, VaR, ES et SV.

risk mesures S&P 500

Autres articles sur le blog SimTrade

   ▶ Shengyu ZHENG Catégories de mesures de risques

   ▶ Shengyu ZHENG Moments de la distribution

   ▶ Shengyu ZHENG Extreme Value Theory: the Block-Maxima approach and the Peak-Over-Threshold approach

   ▶ Youssef LOURAOUI Markowitz Modern Portfolio Theory

Ressources

Articles académiques

Merton R.C. (1980) On estimating the expected return on the market: An exploratory investigation, Journal of Financial Economics, 8:4, 323-361.

Hull J. (2010) Gestion des risques et institutions financières, Pearson, Glossaire français-anglais.

Données

Yahoo! Finance

A propos de l’auteur

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

Market Making

Market Making

Martin VAN DER BORGHT

In this article, Martin VAN DER BORGHT (ESSEC Business School, Master in Finance, 2022-2024) explains the activity of market making which is key to bring liquidity in financial markets.

Market Making: What is It and How Does It Work?

Market making is a trading strategy that involves creating liquidity in a security by simultaneously being ready to buy and sell amount of that security. Market makers provide an essential service to the market by providing liquidity to buyers and sellers, which helps to keep stock prices stable (by limiting the price impact of incoming orders). This type of trading is often done by large institutional investors such as banks. In this article, I will explore what market making is, how it works, and provide some real-life examples of market makers in action.

What is Market Making?

Market making is a trading strategy that involves simultaneously being ready to buy and sell amounts of a security in order to create or improve market liquidity for other participants. Market makers are also known as “specialists” or “primary dealers” on the stock market. They act as intermediaries between buyers and sellers, providing liquidity to the market by always being willing to buy and sell a security at a certain price (or more precisely at two prices: a price to buy and a price to sell). The remuneration of a market maker is obtained by making a profit by taking the spread between the bid and ask prices of a security.

How Does Market Making Work?

Market makers create liquidity by always having an inventory of securities that they can buy and sell. They are willing to buy and sell a security at any given time, and they do so at a certain price. The price they buy and sell at may be different from the current market price, as market makers may be trying to influence the price of a security in order to make a profit.

Market makers buy and sell large amounts of a security in order to maintain an inventory, and they use a variety of techniques to do so. For example, they may buy large amounts of a security when the price is low and sell it when the price is high. They may also use algorithms to quickly buy and sell a security in order to take advantage of small price movements.

By providing liquidity to the market, market makers help to keep stock prices stable. They are able to do this by quickly buying and selling large amounts of a security in order to absorb excess demand or supply. This helps to prevent large price fluctuations and helps to keep the price of a security within a certain range.

Market making nowadays

One of the most well-known examples of market making is the role played by Wall Street banks. These banks act as market makers for many large stocks on the NYSE and NASDAQ. They buy and sell large amounts of a security in order to maintain an inventory, and they use algorithms to quickly buy and sell a security in order to take advantage of small price movements.

Another example of market making is the practice of high-frequency trading. In his book Flash Boys, author Michael Lewis examines the impact of high frequency trading (HFT) on market making. HFT uses powerful computers and sophisticated algorithms to rapidly analyze large amounts of data, allowing traders to make trades in milliseconds. This has led to an increased use of HFT for market making activities, which has caused some to argue that it may be harming market liquidity and efficiency. Market makers have begun using HFT strategies to gain an edge over traditional market makers, allowing them to make markets faster and at narrower spreads. This has resulted in tighter spreads and higher trading volumes, but it has also been argued that it has led to increased volatility and decreased liquidity. As a result, some investors have argued that HFT strategies have created an uneven playing field, where HFT firms have an advantage over traditional market makers.

The use of HFT has also raised concerns about the fairness of markets. HFT firms have access to large amounts of data, which they can use to gain an informational advantage over other market participants. This has raised questions about how well these firms are able to price securities accurately, and whether they are engaging in manipulative practices such as front running. Additionally, some argue that HFT firms are able to take advantage of slower traders by trading ahead of them and profiting from their trades.

These concerns have led regulators to take a closer look at HFT and market making activities. The SEC and other regulators have implemented a number of rules designed to protect investors from unfair or manipulative practices. These include Regulation NMS, which requires market makers to post their best bid and ask prices for securities, as well as Regulation SHO, which prohibits naked short selling and other manipulative practices. Additionally, the SEC has proposed rules that would require exchanges to establish circuit breakers and limit the amount of order cancellations that can be done in a certain period of time. These rules are intended to ensure that markets remain fair and efficient for all investors.

Conclusion

In conclusion, market making is a trading strategy that involves creating liquidity in a security by simultaneously being ready to buy and sell large amounts of that security. Market makers provide an essential service to the market by providing liquidity to buyers and sellers, which helps to keep stock prices stable. Wall Street banks and high-frequency traders are two of the most common examples of market makers.

Related posts on the SimTrade blog

   ▶ Akshit GUPTA Market maker – Job Description

Useful resources

SimTrade course Market making

Michael Lewis (2015) Flash boys.

U.S. Securities and Exchange Commission (SEC) Specialists

About the author

The article was written in January 2023 by Martin VAN DER BORGHT (ESSEC Business School, Master in Finance, 2022-2024).

Evidence of underpricing during IPOs

Evidence of underpricing during IPOs

Martin VAN DER BORGHT

In this article, Martin VAN DER BORGHT (ESSEC Business School, Master in Finance, 2022-2024) exposes the results of various studies concerning IPO underpricing.

What is IPO Underpricing?

Underpricing is estimated as the percentage difference between the price at which the IPO shares were sold to investors (the offer price) and the price at which the shares subsequently trade in the market. As an example, imagine an IPO for which the shares were sold at $20 and that the first day of trading shows shares trading at $23.5, thus the associated underpricing induced is (23.5 / 20) -1 = 17.5%.

In well-developed capital markets and in the absence of restrictions on how much prices are allowed to fluctuate by from day to day, the full extent of underpricing is evident fairly quickly, certainly by the end of the first day of trading as investor jump on an occasion to reflect the fair value of the asset entering the market, and so most studies use the first-day closing price when computing initial underpricing returns. Using later prices, say at the end of the first week of trading, is useful in less developed capital markets, or in the presence of ‘daily volatility limits’ restricting price fluctuations, because aftermarket prices may take some time before they equilibrate supply and demand.

In the U.S. and increasingly in Europe, the offer price is set just days (or even more typically, hours) before trading on the stock market begins. This means that market movements between pricing and trading are negligible and so usually ignored. But in some countries (for instance, Taiwan and Finland), there are substantial delays between pricing and trading, and so it makes sense to adjust the estimate of underpricing for interim market movements.

As an alternative to computing percentage initial returns, underpricing can also be measured as the (dollar) amount of ‘money left on the table’. This is defined as the difference between the aftermarket trading price and the offer price, multiplied by the number of shares sold at the IPO. The implicit assumption in this calculation is that shares sold at the offer price could have been sold at the aftermarket trading price instead—that is, that aftermarket demand is price-inelastic. As an example, imagine an IPO for which the shares were sold at $20 and that the first day of trading shows shares trading at $23.5, with 20 million shares sold. The initial IPO in dollars was $400,000,000 and at the end of the first trading day this amount goes down to $470,000,000, inducing an amount of money left on the table of $70,000,000.

The U.S. probably has the most active IPO market in the world, by number of companies going public and by the aggregate amount of capital raised. Over long periods of time, underpricing in the U.S. averages between 10 and 20 percent, but there is a substantial degree of variation over time. There are occasional periods when the average IPO is overpriced, and there are periods when companies go public at quite substantial discounts to their aftermarket trading value. In 1999 and 2000, for instance, the average IPO was underpriced by 71% and 57%, respectively. In dollar terms, U.S. issuers left an aggregate of $62 billion on the table in those two years alone. Such periods are often called “hot issue markets”. Given these vast amounts of money left on the table, it is surprising that issuers appear to put so little pressure on underwriters to change the way IPOs are priced. A recent counterexample, however, is Google’s IPO which unusually for a U.S. IPO, was priced using an auction.

Why Has IPO Underpricing Changed over Time?

Underpricing is the difference between the price of a stock when it is first offered on the public market (the offer price) and the price at which it trades after it has been publicly traded (the first-day return). Various authors note that underpricing has traditionally been seen as a way for firms to signal quality to potential investors, which helps them to attract more investors and raise more capital.

In their study “Why Has IPO Underpricing Changed over Time? “, authors Tim Loughran and Jay Ritter discuss how the magnitude of underpricing has varied over time. They note that the average underpricing was particularly high in the 1970s and 1980s, with average first-day returns of around 45%. However, they also find that underpricing has declined significantly since then, with average first-day returns now hovering around 10%.

They then analyze the reasons for this decline in underpricing. They argue that the increased availability of information has made it easier for potential investors to assess a company’s quality prior to investing, thus reducing the need for firms to signal quality through underpricing. Additionally, they suggest that increased transparency and reduced costs of capital have also contributed to the decline in underpricing. Finally, they suggest that improved liquidity has made it easier for firms to raise capital without relying on underpricing.

These changes in underpricing have affected both existing and potential investors. Main arguments are that existing shareholders may benefit from reduced underpricing because it reduces the amount of money that is taken out of their pockets when a company goes public. On the other hand, potential investors may be disadvantaged by reduced underpricing because it reduces the return they can expect from investing in an IPO.

In conclusion we can note that while underpricing has declined significantly over time, there is still some evidence of underpricing in today’s markets. It suggests that further research is needed to understand why this is the case and how it affects investors. Many argue that research should focus on how different types of IPOs are affected by changes in underpricing, as well as on how different industries are affected by these changes. Additionally, they suggest that researchers should investigate how different investor groups are affected by these changes, such as institutional investors versus retail investors.

Overall, studies provide valuable insight into why IPO underpricing has changed so dramatically over the past four decades and how these changes have affected both existing shareholders and potential investors. It provides convincing evidence that increased access to information, greater transparency, reduced costs of capital, and improved liquidity have all contributed to the decline in underpricing. While it is clear that underpricing has declined significantly over time, further research is needed to understand why some IPOs still exhibit underpricing today and what effect this may have on different investor groups.

Related posts on the SimTrade blog

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

▶ Marie POFF Film analysis: The Wolf of Wall Street

Useful resources

Ljungqvist A. (2004) IPO Underpricing: A Survey, Handbook in corporate finance: empirical corporate finance, Edited by B. Espen Eckbo.

Loughran T. and J. Ritter (2004) Why Has IPO Underpricing Changed over Time? Financial Management, 33(3), 5-37.

Ellul A. and M. Pagano (2006) IPO Underpricing and After-Market Liquidity The Review of Financial Studies, 19(2), 381-421.

About the author

The article was written in January 2023 by Martin VAN DER BORGHT (ESSEC Business School, Master in Finance, 2022-2024).

Market efficiency

Market efficiency

Martin VAN DER BORGHT

In this article, Martin VAN DER BORGHT (ESSEC Business School, Master in Finance, 2022-2024) explains the key financial concept of market efficiency.

What is Market Efficiency?

Market efficiency is an economic concept that states that financial markets are efficient when all relevant information is accurately reflected in the prices of assets. This means that the prices of assts reflect all available information and that no one can consistently outperform the market by trading on the basis of this information. Market efficiency is often measured by the degree to which prices accurately reflect all available information.

The efficient market hypothesis (EMH) states that markets are efficient and that it is impossible to consistently outperform the market by utilizing available information. This means that any attempt to do so will be futile and that all investors can expect to earn the same expected return over time. The EMH is based on the idea that prices are quickly and accurately adjusted to reflect new information, which means that no one can consistently make money by trading on the basis of this information.

Types of Market Efficiency

Following Fama’s academic works, there are three different types of market efficiency: weak, semi-strong, and strong.

Weak form of market efficiency

The weak form of market efficiency states that asset prices reflect all information from past prices and trading volumes. This implies that technical analysis, which is the analysis of past price and volume data to predict future prices, is not an effective way to outperform the market.

Semi-strong form of market efficiency

The semi-strong form of market efficiency states that asset prices reflect all publicly available information, including financial statements, research reports, and news. This implies that fundamental analysis, which is the analysis of a company’s financial statements and other publicly available information to predict future prices, is also not an effective way to outperform the market.

Strong form of market efficiency

Finally, the strong form of market efficiency states that prices reflect all available information, including private information. This means that even insider trading, which is the use of private information to make profitable trades, is not an effective way to outperform the market.

The Grossman-Stiglitz paradox

If financial markets are informationally efficient in the sense they incorporate all relevant information available, then considering this information is useless when making investment decisions in the sense that this information cannot be used to beat the market on the long term. We may wonder how this information can be incorporate in the market prices if no market participants look at information. This is the Grossman-Stiglitz paradox.

Real-Life Examples of Market Efficiency

The efficient market hypothesis has been extensively studied and there are numerous examples of market efficiency in action.

NASDAQ IXIC 1994 – 2005

One of the most famous examples is the dot-com bubble of the late 1990s. During this time, the prices of tech stocks skyrocketed to levels that were far higher than their fundamental values. This irrational exuberance was quickly corrected as the prices of these stocks were quickly adjusted to reflect the true value of the companies.

NASDAQ IXIC Index, 1994-2005

Source: Wikimedia.

The figure “NASDAQ IXIC Index, 1994-2005” shows the Nasdaq Composite Index (IXIC) from 1994 to 2005. During this time period, the IXIC experienced an incredible surge in value, peaking in 2000 before its subsequent decline. This was part of the so-called “dot-com bubble” of the late 1990s and early 2000s, when investors were optimistic about the potential for internet-based companies to revolutionize the global economy.

The IXIC rose from around 400 in 1994 to a record high of almost 5000 in March 2000. This was largely due to the rapid growth of tech companies such as Amazon and eBay, which attracted huge amounts of investment from venture capitalists. These investments drove up stock prices and created a huge market for initial public offerings (IPOs).

However, this rapid growth was not sustainable, and by the end of 2002 the IXIC had fallen back to around 1300. This was partly due to the bursting of the dot-com bubble, as investors began to realize that many of the companies they had invested in were unprofitable and overvalued. Many of these companies went bankrupt, leading to large losses for their investors.

Overall, the figure “Indice IXIC du NASDAQ, 1994-2005” illustrates the boom and bust cycle of the dot-com bubble, with investors experiencing both incredible gains and huge losses during this period. It serves as a stark reminder of the risks associated with investing in tech stocks. During this period, investors were eager to pour money into internet-based companies in the hopes of achieving huge returns. However, many of these companies were unprofitable, and their stock prices eventually plummeted as investors realized their mistake. This led to large losses for investors, and the bursting of the dot-com bubble.

In addition, this period serves as a reminder of the importance of proper risk management when it comes to investing. While it can be tempting to chase high returns, it is important to remember that investments can go up as well as down. By diversifying your portfolio and taking a long-term approach, you can reduce your risk profile and maximize your chances of achieving successful returns.

U.S. Subprime lending expanded dramatically 2004–2006.

Another example of market efficiency is the global financial crisis of 2008. During this time, the prices of many securities dropped dramatically as the market quickly priced in the risks associated with rising defaults and falling asset values. The market was able to quickly adjust to the new information and the prices of securities were quickly adjusted to reflect the new reality.

U.S. Subprime Lending Expanded Significantly 2004-2006

Source: US Census Bureau.

The figure “U.S. Subprime lending expanded dramatically 2004–2006” illustrates the extent to which subprime mortgage lending in the United States increased during this period. It shows a dramatic rise in the number of subprime mortgages issued from 2004 to 2006. In 2004, less than $500 billion worth of mortgages were issued that were either subprime or Alt-A loans. By 2006, that figure had risen to over $1 trillion, an increase of more than 100%.

This increase in the number of subprime mortgages being issued was largely driven by lenders taking advantage of relaxed standards and government policies that encouraged home ownership. Lenders began offering mortgages with lower down payments, looser credit checks, and higher loan-to-value ratios. This allowed more people to qualify for mortgages, even if they had poor credit or limited income.

At the same time, low interest rates and a strong economy made it easier for people to take on these loans and still be able to make their payments. As a result, many people took out larger mortgages than they could actually afford, leading to an unsustainable increase in housing prices and eventually a housing bubble.

When the bubble burst, millions of people found themselves unable to make their mortgage payments, and the global financial crisis followed. The dramatic increase in subprime lending seen in this figure is one of the primary factors that led to the 2008 financial crisis and is an illustration of how easily irresponsible lending can lead to devastating consequences.

Impact of FTX crash on FTT

Finally, the recent rise (and fall) of the cryptocurrency market is another example of market efficiency. The prices of cryptocurrencies have been highly volatile and have been quickly adjusted to reflect new information. This is due to the fact that the market is highly efficient and is able to quickly adjust to new information.

Price and Volume of FTT

Source: CoinDesk.

FTT price and volume is a chart that shows the impact of the FTX exchange crash on the FTT token price and trading volume. The chart reflects the dramatic drop in FTT’s price and the extreme increase in trading volume that occurred in the days leading up to and following the crash. The FTT price began to decline rapidly several days before the crash, dropping from around $3.60 to around $2.20 in the hours leading up to the crash. Following the crash, the price of FTT fell even further, reaching a low of just under $1.50. This sharp drop can be seen clearly in the chart, which shows the steep downward trajectory of FTT’s price.

The chart also reveals an increase in trading volume prior to and following the crash. This is likely due to traders attempting to buy low and sell high in response to the crash. The trading volume increased dramatically, reaching a peak of almost 20 million FTT tokens traded within 24 hours of the crash. This is significantly higher than the usual daily trading volume of around 1 million FTT tokens.

Overall, this chart provides a clear visual representation of the dramatic impact that the FTX exchange crash had on the FTT token price and trading volume. It serves as a reminder of how quickly markets can move and how volatile they can be, even in seemingly stable assets like cryptocurrencies.

Today, the FTT token price has recovered somewhat since the crash, and currently stands at around $2.50. However, this is still significantly lower than it was prior to the crash. The trading volume of FTT is also much higher than it was before the crash, averaging around 10 million tokens traded per day. This suggests that investors are still wary of the FTT token, and that the market remains volatile.

Conclusion

Market efficiency is an important concept in economics and finance and is based on the idea that prices accurately reflect all available information. There are three types of market efficiency, weak, semi-strong, and strong, and numerous examples of market efficiency in action, such as the dot-com bubble, the global financial crisis, and the recent rise of the cryptocurrency market. As such, it is clear that markets are generally efficient and that it is difficult, if not impossible, to consistently outperform the market.

Related posts on the SimTrade blog

   ▶ All posts related to market efficiency

   ▶ William ANTHONY Peloton’s uphill battle with the world’s return to order

   ▶ Aamey MEHTA Market efficiency: the case study of Yes bank in India

   ▶ Aastha DAS Why is Apple’s new iPhone 14 release line failing in the first few months?

Useful resources

SimTrade course Market information

Academic research

Fama E. (1970) Efficient Capital Markets: A Review of Theory and Empirical Work, Journal of Finance, 25, 383-417.

Fama E. (1991) Efficient Capital Markets: II Journal of Finance, 46, 1575-617.

Grossman S.J. and J.E. Stiglitz (1980) On the Impossibility of Informationally Efficient Markets The American Economic Review, 70, 393-408.

Chicago Booth Review (30/06/2016) Are markets efficient? Debate between Eugene Fama and Richard Thaler (YouTube video)

Business resources

CoinDesk These Four Key Charts Shed Light on the FTX Exchange’s Spectacular Collapse

Bloomberg Crypto Prices Fall Most in Two Weeks Amid FTT and Macro Risks

About the author

The article was written in January 2023 by Martin VAN DER BORGHT (ESSEC Business School, Master in Finance, 2022-2024).