Money & Finance

Stock market participation in the aftermath of an accounting scandal

  • Blog Post Date30 August, 2017
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Renuka Sane

National Institute of Public Finance and Policy

renuka.sane@nipfp.org.in

An emerging literature shows that exposure of fraud in the corporate sector leads to a fall in trust on part of households and decline in their stock market participation. Analysing data on daily investor account holdings from India, this column finds that contrary to international experience, an event such as the Satyam scandal did not have a big impact on investor activity.

It is often argued that low trust is detrimental to stock market participation: if households don't trust markets, they won't participate in them. An emerging literature seeks to evaluate whether fall in trust as a consequence of fraud revelation leads to decline in participation. The argument is that occurrence of fraud damages trust, and this can further have an adverse impact on participation. Two studies are of particular interest:

  1. Gurun, Stoffman and Yanker (2015): study the response to the collapse of the multi-billion dollar Ponzi scheme orchestrated by Bernard Madoff. They find that residents of communities in the US that were more exposed to the fraud subsequently withdrew assets from investment advisers and increased deposits at banks.
  2. Giannetti and Wang (2016): find evidence that a one-standard-deviation1 increase in a household’s lifetime exposure to local fraud decreases the household’s probability of holding stocks by 4%. They find evidence that the decrease in stock market participation is a result of the lowering of trust.

These are important results, as withdrawals from stock markets can have huge implications for the cost of capital. The type of fraud, and the cultural and institutional settings in which fraud takes place, may vary across locations. In order to understand the impact of fraud revelation, and the channels through which it manifests, it is useful to build up a literature that analyses such events across multiple settings.

Understanding the impact of fraud on investor behaviour in India

In recent research, I focus on the impact of fraud in the Indian setting (Sane 2017). Participation is measured on the intensive margin, that is, in terms of the net traded value by investors. I examine the following questions:

  1. Are investors with direct exposure to stock market fraud more likely to decrease their participation (take cash out of their portfolios) in the stock market than investors with no direct exposure to fraud?
  2. Is this behaviour restricted to the stock in question, or is there an effect on other stocks?
  3. Is the reaction to fraud only an immediate response or does it persist over longer horizons?

The Satyam event

The setting for fraud used is the Satyam scandal – the biggest, and most unexpected accounting fraud in the Indian stock market, also known as the “Enron of India''. On 7 January 2009, Ramalinga Raju, the chairman of Satyam, confessed to an accounting fraud to the tune of US$1.47 billion. While Satyam had been in news previously for its failed takeover of Maytas Infrastructure and Maytas Properties, the scale of accounting fraud was entirely unexpected (Wharton, 2009).

The scandal was mostly a result of an accounting fraud and is said to have had serious ramifications on investor confidence. It was believed that the promoter of Satyam had betrayed the trust of his employees, the IT industry, and the whole nation. Both Satyam's internal as well as statutory auditors had not brought this discrepancy to light. Satyam was seen as a failure of the system – auditors, the board, the regulator – leading to a loss of trust in the system itself.

Data

The data on daily investor account holdings comes from the National Securities Depository Limited (NSDL), the largest depository in India in terms of total assets tracked (roughly 80%). I am thus able to capture trading behaviour immediately before and after the event, and on a daily basis for an extended period of time. This is unlike other studies that base their analysis on household survey data, or observe investors at a monthly or yearly frequency. While daily holdings are available, there is no access to demographic information. It is not possible to identify actual age, gender, or any other household information from this data.

I take a stratified random sample of about 400,000 investors from the NSDL universe. In this sample, investors who held Satyam one day prior to the event are the ‘treated investors’, while those that did not hold Satyam are the ‘control investors’. Treated investors are found to be a little more experienced than control investors – the average number of years they have been in the market is 4.5 as opposed to 3.7. Treated investors also have higher portfolio values prior to the crisis than control investors, and they trade larger quantities. The former had been making net purchases into the portfolio over the 30-day period prior to the crisis. They had a lower portfolio beta2 than the other group.

Matching on observable characteristics

Given the differences between Satyam and non-Satyam investors, I conduct a matching exercise based on the following four variables:

  1. The number of years the investor has been in the market
  2. The traded value by investors in the last 30 days prior to the event
  3. Portfolio beta prior to the event
  4. Portfolio value prior the event

These variables are selected because they capture trading behaviour of investors prior to the crisis. The balance statistics suggest that the Satyam and non-Satyam investors are not too different from each other based on observable characteristics. This allows for a comparison between the two groups post the event.

I analyse the difference in trading behaviour between the two groups, across the pre- and post-crisis periods. I restrict my analysis to seven days pre and post the event for short-term effects. For longer term effects I study a period of one month pre and post the event.

Results

The core findings of the analysis can be summarised as follows:

  1. Investors with direct exposure to Satyam traded more intensely immediately, that is, over seven days after the Satyam event, relative to control investors. This trading was largely driven by cashing out of the portfolio. Treated investors cashed out almost 10.6 percentage points of their overall portfolio relative to control investors post the crisis.
  2. The cashing out was largely restricted to the ‘bad stock’'. If anything, treated investors made net purchases of related stocks during the same period.
  3. Over the period of a month, there was no difference in the trading behaviour of the treated and control investors.

The results are robust to comparison with days of similar portfolio losses in the past, and dealing with the Maytas event a few weeks prior to the scandal. This is made possible by a comparison between those who never held Satyam, those who held Satyam but gave up before the Maytas event, and those who gave up Satyam after the Maytas event.

Thus, it seems that the effects of the Satyam scandal were weak. While investors did decline their participation on the intensive margin at the time of the event, this was a short-term effect and largely restricted to the Satyam stock. There does not appear to have been a contagion effect on the market.

Conclusion

The results are contrary to what has been found internationally, and raise questions on the importance of cultural and institutional settings for investor behaviour. For example, portfolios of Indian households are dominated by real assets such as gold and real estate. Barely 2% of the country participates in the stock market. And while India does well on corporate governance metrics such as the World Bank ease-of-doing-business indicators, on the ground there is general skepticism about corporate governance standards.

It is in this context of limited stock market participation, and high mistrust of accounting standards that the Satyam fraud needs to be considered. In such a setting, it is possible that an accounting fraud, even as big as Satyam, does not damage trust perceptions of those already in the market – relative to mature market settings with higher participation rates and higher expectations of governance standards. It is also possible that swift government action, as was taken after Satyam, has a larger pacifying effect in India, than in more mature economies.

Instances of fraud may deter participation on the extensive margin, and cause fewer people to enter the market. This question is left for the future, when survey data on household participation and overall portfolio allocation become available.

Notes:

  1. Standard Deviation is a measure that is used to quantify the amount of variation or dispersion of a set of values from the mean value (average) of that set.
  2. Beta is a measure of the volatility, or systematic risk, of a security or a portfolio in comparison to the market as a whole. A beta of 1 indicates that the security's price moves with the market; less than 1 means that the security is theoretically less volatile than the market; and greater than 1 indicates that the security's price is theoretically more volatile than the market.

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