When index dissemination goes wrong: How fast can traders add and multiply?

This paper studies an episode of dissemination of wrong stock index values in real time due to a software bug in the Indian Nifty index futures market on the morning of January 18, 2006. The episode provides an opportunity to test various models of cognitive biases and bounded rationality highlighted in behavioural finance. The paper provides strong evidence against cognitive biases like “anchoring and adjustment” (Tversky and Kahneman, 1974) that one might expect under such situations even though the cognitive task involved is quite simple. The futures market tracked the true Nifty index which it could not see while completely ignoring the wrong Nifty index that it could see. However, the paper demonstrates that market efficiency failed in more subtle ways. There is evidence of a partial breakdown of price discovery in the futures markets and a weakening of the bonds linking futures and cash markets. This evidence is consistent with the centrality of “market devices” as argued in “actor network theory” in economic sociology (Muniesa, Millo and Callon, 2007 and Preda, 2006). Well functioning markets today depend critically on a whole set of information and communication technologies. Any failures in these material, socio-technical aspects of markets can make markets quite fragile even if behavioural biases are largely absent.

Rupee-Dollar Option Pricing and Risk Measurement: Jump Processes, Changing Volatility and Kurtosis Shifts

Exchange rate movements in the Indian rupee (and many other emerging market currencies) are characterised by long periods of placidity punctuated by abrupt and sharp changes. Many, but by no means all, of these sharp changes are currency depreciations. This paper shows that econometric models of changing volatility like Generalised AutoRegressive Conditional Heteroscedasticity (GARCH) with non normal residuals which perform quite well in other financial markets fail quite miserably in the case of the INR-USD process because they do not allow for such jumps in the exchange rate. The empirical results very convincingly demonstrate the need to model the exchange rate process as a mixed jump-diffusion (or normal mixture) process. Equally importantly, the empirical results provide strong evidence that the jump probabilities are not constant over time. From a statistical point of view, changes in the jump probabilities induce large shifts in the kurtosis of the process. The failure of GARCH processes arises because they allow for changes in volatility but not for changes in kurtosis. The time varying mixture models are able to accommodate regime shifts by allowing both volatility and kurtosis (not to mention skewness) to change. This also shows that the periods of calm in the exchange rate are extremely deceptive; in these periods, the variance of rate changes is quite low, but the kurtosis is so high (in the triple digit range) that the probability of large rate changes is non trivial. The empirical results also show that the Black-Scholes-Garman-Kohlhagen model for valuation of currency options is quite inappropriate for valuing rupee-dollar options and that the Merton jump-diffusion model is the model of choice for this purpose.

Risk Management Lessons from the Global Financial Crisis for Derivative Exchanges

During the global financial turmoil of 2007 and 2008, no major derivative clearing house in the world encountered distress while many banks were pushed to the brink and beyond. An important reason for this is that derivative exchanges have avoided using value at risk, normal distributions and linear correlations. This is an important lesson. The global financial crisis has also taught us that in risk management, robustness is more important than sophistication and that it is dangerous to use models that are over calibrated to short time series of market prices. The paper applies these lessons to the important exchange traded derivatives in India and recommends major changes to the current margining systems to improve their robustness. It also discusses directions in which global best practices in exchange risk management could be improved to take advantage of recent advances in computing power and finance theory. The paper argues that risk management should evolve towards explicit models based on coherent risk measures (like expected shortfall), fat tailed distributions and non linear dependence structures (copulas).

A Valuation Model for Indeterminate Convertibles

Many issues of convertible debentures in India in recent years provide for a mandatory conversion of the debentures into an unspecified number of shares at an unspecified time; the conversion ratio (i.e., the number of shares per debenture) is to be determined by the Controller of Capital Issues (CCI). There are serious problems in arriving at a rational value for these "indeterminate convertibles". Even if the investor can make some estimate of the likely conversion terms, there is no valuation model available to arrive at a price. This paper applies the general theory of derivative securities (Cox, Ingersoll and Ross, 1985) to obtain a valuation model for these instruments. The model shows that the naive valuation model which sets the value of the debenture equal to the current stock price times the expected conversion ratio is likely to be a significant overestimate of the price. It also shows that changes in the stock price lead to less than proportionate changes in the debenture price unlike in the case of pre-specified conversion terms. Similarly, the CAPM beta of the debenture would be significantly lower than that of the share. While the model does not obviate the need for obtaining estimates of unobservable parameters related to the market expectations about the likely conversion ratio, the qualitative insights given by the model are quite useful. The model is successful in explaining some of the empirical patterns and anomalies that have been observed in ongoing empirical research into the market prices of these debentures.

Value at Risk Models in the Indian Stock Market

This paper provides empirical tests of different risk management models in the Value at Risk (VaR) framework in the Indian stock market. It is found that the GARCH-GED (Generalised Auto-Regressive Conditional Heteroscedasticity with Generalised Error Distribution residuals) performs exceedingly well at all common risk levels (ranging from 0.25% to 10%). The EWMA (Exponentially Weighted Moving Average) model used in J. P. Morgan’s RiskMetrics� methodology does well at the 10% and 5% risk levels but breaks down at the 1% and lower risk levels. The paper then suggests a way of salvaging the EWMA model by using a larger number of standard deviations to set the VaR limit. For example, the paper suggests using 3 standard deviations for a 1% VaR while the normal distribution indicates 2.58 standard deviations and the GED indicates 2.85 standard deviations. With this modification the EWMA model is shown to work quite well. Given its greater simplicity and ease of interpretation, it may be more convenient in practice to use this model than the more accurate GARCH-GED specification. The paper also provides evidence suggesting that it may be possible to improve the performance of the VaR models by taking into account the price movements in foreign stock markets.

Mastershares: Enigmatic Performance

In this paper we have examined the performance of Mastershares, the first all equity close ended growth fund established by the Unit Trust of India (UTI) in the country, using the various portfolio performance measures that have been suggested in the literature. We found that while in terms of return on the Net Asset Value (NAV) the fund has out-performed the market, in terms of returns based on Market Prices it has shown a mixed performance. On further investigation, we inferred that the excellent performance in terms of NAV could neither be ascribed to selectivity nor to timing of decisions. The explanation possibly lies in UTI’s acquisition of stocks in the primary market as well below prevailing market prices and in the manner of allocation of stocks to various funds managed by the Trust. Our analysis also revealed that the market quite irrationally inflates the volatility of the market price of Mastershares as compared to the volatility observed in the NAV. This observation which implies market inefficiency is in line with the recent researches done in the developed capital markets.

Regulatory Implications of Monopolies in the Securities Industry

Since the mid-1990s, investors and regulators have benefited from a high degree of competition in the Indian securities industry. Even more than all the policy changes that have taken place, it is technology and competition that have transformed the Indian capital market in the last 7-8 years. This paper shows that there is now considerable evidence that critical elements of the Indian securities industry are becoming significantly less competitive than in the past. Reduced competition would remove the single most important driver of capital market modernisation in this country and would create several serious regulatory problems. The paper argues that rather than applying the traditional solution of “regulated monopolies”, regulators need to adopt strong measures to stimulate competition. The regulator must also ruthlessly discard those elements of the regulatory regime that are anti-competitive in nature.

Where Utility Functions Do Not Exist - A Note on Lexicographic Orders

There seems to be some amount of confusion in the finance text books regarding the conditions under which an individual’s preferences can be represented by a utility function. Fama and Miller, for example, assert that two axioms (comparability and transitivity) are sufficient to establish the existence of a utility function (when the set of alternatives is Rn). This is totally false: a real valued utility function need not exist even in the single good case (R1). One might hope that a vector valued utility might exist (with lexicographic ordering of the utility vector); but this is not the case. Indeed we cannot salvage the situation even by allowing the utility to be a vector in Rn) (i.e. to have an (countably) infinite number of components); only an uncountable number of real components can do the job. None of these results are new, but they do not seem to be sufficiently well known to researchers in finance. This may be because the original papers are mathematically forbidding or because they are scattered in sources somewhat removed form the mainstream finance literature. If that be so, this note should be of some help; some of our proofs and examples are new and hopefully more elementary (for example we avoid taking recourse to Sierpinski’s lemma).

When AAA Means B: The State of Credit Rating in India

As in many other countries, India five year old credit rating industry has grown rapidly amidst persistent doubts about the quality of the rating service. This paper evaluates the ratings given by India leading credit rating agency, CRISIL. We find that CRISIL ratings are not only too liberal by international standards but also internally inconsistent. We argue that to improve the quality of credit rating in India, there must be more competition; credit rating must be opened up to the private sector; and raters must provide unsolicited ratings.

Securities Scam Genesis, Mechanics and Impact

The term "securities scam" refers to a diversion of funds to the tune of over Rs. 3500 crores from the banking system to various stockbrokers in a series of transactions (primarily in Government securities) during the period April 1991 to May 1992. The scam has for several months become a permanent feature of the front pages of the newspapers. Despite the massive media coverage of the scam, most readers found it hard to understand it particularly when they were confronted with arcane terms and acronyms like ready forward, double ready forward, SGL, PDO, BR, PMS etc. Nevertheless an understanding of the scam is a prerequisite for any meaningful analysis of policy alternatives to improve the functioning of the financial system. This paper presents a plausible reconstruction of how the scam originated, how it was perpetrated, and what would be its aftermath. The paper is expository in nature and the authors make no claims to omniscience. The paper goes on to discuss the response of the government to the scam in terms of 1) discovering and punishing the guilty, 2) recovering the money, and 3) reforming the system. While agreeing with the importance of discovering and punishing the guilty, the paper argues that the attempt of the government to recover the money by such measures as the tainted shares law which cause severe and unjustified hardship to genuine and innocent investors is misguided. Turning to the arena of reforms of the financial system, the paper argues that the origins of the scam lie in overregulation of our markets. It recommends that normal transactions must be allowed to be done openly and transparently, and the role of brokers as market makers must be recognized. The second lesson from the scam is that artificial insulation of closely related markets from each other is counterproductive in the long run. Artificial barriers between the money market and the capital market, between the market for corporate securities and the market for government securities and between the formal money market and the informal one must be eliminated.