New Vistas for Risk Management in India's Equity Derivatives Market
Stock markets today are in a phase where regulators as well as exchanges need to evolve new risk management techniques for mitigating risks. The turnover in the Indian equity derivatives market today is far in excess of those in the cash-settled equity segment. In such a situation, it becomes imperative that regulators and exchanges strive to engender more transparency and disclosures. They also need to look beyond traditional risk management measures offered by the conventional value at risk models.
A lot has been spoken of risk in the derivatives market but little has been done about understanding it better. The first step in this direction then becomes the formulation of a clear definition of risk in this market. A large proportion of risk can be mitigated if risk is defined and understood clearly. We shall therefore divide our discussion here into two parts, with the first part focusing on the definition of risk. In the second part we shall look at ways of reducing risks – beyond the conventional VaR method. This is something that also offers hope to the investor by reducing their costs of transacting in the derivatives markets. The proposed solution envisages utilizing idle stocks with investors as a substitute for the expensive margins that they have to put up with the clearing corporation for transacting in the derivatives market.
The three major risks that exchanges and clearing corporations worldwide (and Indian stock exchanges are no different) are wary of are (a) credit risk, (b) liquidity risk and (c) price risk. The credit risk is beyond the purview of any conventional stock exchange risk management model where exchange membership norms have to be strengthened. The liquidity risk is adequately handled by the limits of open interest which are typically in terms of the number of outstanding shares and past month(s) trading volume in the underlying stock, with exemptions granted to certain qualified hedging strategies. However, towards handling the most formidable of them all i.e. the price risk, exchanges and clearing corporations the world over place their bet on initial margin requirements which are mostly based on the conventional value at risk (VaR) models.
It is surprising that exchanges and regulators even today deal only with statistical volatility for estimating price risk, despite the derivatives market having grown immensely over recent years. Statistical volatility is basically a measure of how much the price of an asset has bounced around recently. This method uses one or the other time series or a macro economic model for volatility forecasting. For instance, the exponential weighted moving average model for volatility forecasting quantifies the magnitude of the asset’s price swings on a percentage basis, with weights attached to historical and current volatilities. Statistical volatility can be plotted on volatility charts to show periods of relative price activity and inactivity over time.
The other kind of volatility is called implied volatility. The term implied volatility comes from the fact that options imply the volatility of their underlying. The market price of the option can be used as an effective tool for forecasting volatility. Using any options pricing model, a program can be devised to find the volatility that makes the fair value of the option equal to the market price of the option. The underlying assumptions being that (a) the options market is liquid, and (b) one has faith in the option pricing model that is chosen. To understand the concept of implied volatility one may ask the simple question: What volatility must traders have in mind in order to generate the observed options price? This is called implied volatility.
Several papers have found that implied volatility works better than most or all time series econometrics when it comes to forecasting volatility. Almost all time series econometricians forecast volatility which is based on one or the other statistical volatility model. Implied volatility, on the other hand, uses market parameters for inputs which lend it an edge as the market knows things about future volatility which is unknown to any time series model. For instance, the budget day is known in advance and one can expect a reasonably elevated options price in the preceding week. Purely from the perspective of the clearing corporation, using implied volatility makes much more sense since the market would incorporate the statistical volatility while generating prices. Implied volatility would therefore contain the invaluable information on market perception which would not be available in any time series analysis. Using implied volatility for computing value at risk would therefore be that much more effective.
From the perspective of the investor, the implied volatility levels in the options market help him determine the optimum strategies. There are a lot of customers who look at ‘playing it safe’. They are sure that stock prices will move, but have no idea in which direction. The risk graph for these can often look deceptively attractive if one is concentrating only on price moves of the underlying stock over time. There is very obviously a need for market participants to move beyond this simplistic view and incorporate probable volatility changes into their analysis to better understand the true risk associated with a trade.
The most important feature of volatility is that it tends to revert to the mean. This is amply illustrated in Fig. 1 which plots the daily returns from S&P CNX NIFTY Index for the period 01-JAN-2000 to 31-MAR-2004.
Periods of high volatility are followed by periods of normal to low volatility and vice-versa. The market can almost always count on volatility returning to normal levels after going to an extreme. This can be very easily confirmed by looking at a few volatility charts.
There are two ways to judge how volatility is likely to move in the future. The first is by comparing current implied volatility with the current statistical volatility of the underlying stock itself. The implied volatility of a stock should usually reflect the actual statistical volatility of the asset. Another way to judge the probable future volatility is to compare the current implied volatility with the asset’s past levels of implied volatility. If current implied volatility is higher than it has been in the past, it will eventually return to more normal levels, unless there has been some fundamental change in the company, market, or the economy that will make this asset more volatile in the future.
The traditional risk management measures help in risk mitigation only up to a point. Even this limited risk management assumes an accurate understanding of the associated risks. Beyond this and more so in the Indian context, where stock volatility is unusually high, it becomes imperative to look beyond the ordinary. It is a fact that the cash-settled equity markets in India today do not hold the same sway as the markets of yesteryear. With the introduction of derivatives since June 2000, investor interest in cash markets has been continuously on the decline. In the absence of any effective (read organized) securities lending scheme, investors are probably sitting on equity stocks without earning any returns. On the other hand, the margining methodology in the derivatives segment (based on the conventional value at risk model) requires investors to put upfront cash margins before taking up positions in the derivatives segment. Given that the constitution of the Indian market comprises a large retail segment, margin numbers churned out of the standard value at risk models make transactions expensive.
In serving the two ends of (a) minimizing counterparty risk with the clearing corporation, and (b) lowering transaction cost of participants, the markets can be tailored to offer new risk management products which have not been used even in the developed west.
One such measure could be a variant of the covered call writing. For the sake of nomenclature we shall call this Covered Pay In (CPI). Traditionally, covered call writing is defined as either (a) the simultaneous purchase of stock and the sale of a call option, or (b) the sale of a call option against stock currently held by an investor. From the perspective of an exchange / clearing corporation, definition under (b) shall hold and can be used for the purpose of granting margin exemption to the extent that such stocks are placed with the clearing corporation. This holds true as much for short futures position as for short call options. Given the waning investor interest in the cash markets, it is worthwhile for derivative clearing corporations to exploit this opportunity and get the investors to place these stocks against their short futures position or a short call option position.
For all short call option and short equity futures positions (we shall limit our discussion here to these two class of products which would stand to benefit from this model), members are required to put up initial margin with the clearing corporation. This is ordinarily computed using the delta hedging method. In addition to the initial margin, the clearing corporation charges a variation margin which is pledged with the clearing corporation to make the margin requirements coherent with the fluctuating derivative values. Trading in derivatives is associated with the risk that a participant may fail to provide the collateral required to cover his positions. Given that the clearing corporation provides settlement guarantee, such a margin serves as a cover in the event of a default.
In lieu of margin calls, participants may instead be called upon to place the relevant stocks with the exchange / clearing corporation against their position in such short call option and futures contracts. Provided that these stocks are not earning any returns for the participant (which is very likely in the absence of any securities lending scheme), these can be used to seek margin exemptions on such positions. To the extent that the short positions have been paid in, they do not constitute any risk to the clearing corporation and can be exempt from margin payments.
The extent of benefit is evident from the following example. Assume a short call option position of a single contract (100 shares) of Infosys in the March expiry contract (expired on March 25, 2004) at a strike price of INR6050.00. The closing price of Infosys on March 24, 2004 at NSE was INR5047.50. This is very obviously an ‘out of money’ option which should typically attract near nil margins. However, given regulatory requirements even such positions are margined and in this instance, the position shall have to pay an initial margin of INR37905.00, owing to short option charge (reference: March 24, 2004 end day SPAN file generated by NSE). Considering that the premium that would be paid for the purchase of a single unit of such ‘out of money’ contract is a pittance at INR5.00, the margin amount is indeed huge. In addition, variation margin is charged depending on individual stock volatility.
Participants could entirely get away without paying this margin with no corresponding increase in risk to the clearing corporation if the corresponding stocks are placed as a cover against such positions. On expiry of contract, these stocks could be returned to the participants, provided such positions are not exercised. In the event of the positions being exercised, the stocks could be used to complete the settlement (physical settlement) or returned after the completion of cash settlement.
While there already exist facilities for participants to offer stocks as ‘Grade B’ (non-cash) collateral to the clearing corporation, these are mandatorily required to satisfy the cash / non-cash ratio for collateral. Such rules essentially make offering such ‘Grade B’ collateral very unattractive.
It can be proved that the CPI route is a pareto-optimal strategy for investors and members on one side and exchanges and clearing corporations on the other. Investors are better off with margin exemptions leading to lower transaction costs and the exchanges and clearing corporations would definitely do well with risk free positions. This is aptly illustrated in Fig. 2.
In the above illustration of a general equilibrium analysis, the lower left hand corner represents the origin for the investor (IN) and the upper right hand corner represents the origin for the clearing corporation (CC). The investor’s preferences (indifference curves) are convex to the origin OIN with any move to the north-east representing a move to a higher indifference curve (the investor derives greater satisfaction from that bundle of goods compared to a bundle yielding less overall utility and that appears on a lower indifference curve). Likewise, clearing corporation’s preferences are convex to OCC. Any trade-off between the appetite for stocks on one hand and cash on the other between the two entities in the negotiating space shall make one or both entities better off.
As is evident, any move to the right in the negotiating space, means that the investor has more cash in hand and less securities (which are lying idle with him). If for example, the investor (IN) and the clearing corporation (CC) are at an initial endowment point W, it is possible to make the investors better off by moving to point R without making the clearing corporation any worse off (a move along the same indifference curve of the clearing corporation). A second trade off could be movement toward point E which would make both investors as well as the clearing corporation better off. Hence, through a simple process of exchange, given their initial endowments, both the individual investor and the clearing corporation can be better off.
The beauty of this solution is enhanced by the fact that this works as well for cash settled derivatives as for derivatives that are physically settled.