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B. Venkatesh

XLRI Jamshedpur recently tied up with Riskmetrics, US, for risk management practice. Riskmetrics made popular the concept of Value-at-Risk (VaR) in the late 1980s. What is VaR?

VaR is a measure of portfolio risk. Suppose the one-day VaR on your Rs 50-lakh portfolio is 2 per cent based on a 95 per cent confidence level. This means that in 95 out of 100 days, your portfolio is likely to lose 2 per cent on a trading day. It also means that your portfolio can lose more than 2 per cent in five of 100 days.

Some firms use 99 per cent confidence levels to be more certain of their likely portfolio loss. Suppose the one-day VaR for a bank is 5 per cent on its Rs 1,000-crore portfolio. This means that in 99 out of 100 days, the bank is likely to lose 5 per cent of Rs 1,000 crore on a single day. So, the bank will have enough capital to support expected losses.

How is VaR computed? The simplest VaR model is based on the normal distribution.

Suppose you find that the standard deviation of daily returns on your portfolio is 5 per cent; that is, your portfolio can move up or down by 5 per cent on any day. Since you are bothered about losses on your portfolio, you have to find the area on the left side of the normal curve for a certain confidence level.

You can find the value of the normal distribution in any statistics book. The left side area under the normal curve for a 95 per cent confidence level is 1.65.

You have to multiply the portfolio standard deviation with 1.65 to get the portfolio VaR. This VaR model is similar to the semi-deviation, except that the latter does not involve confidence levels.

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