The Hindu Business Line : Investors should consider risk-adjusted returns

RISK management is likely to get an impetus in India with the entry of global risk management firms such as Riskmetrics. This US firm recently tied up with XLRI, Jamshedpur to facilitate the latter's risk management practice. The entry of risk management firms assumes importance because mutual funds do not disclose their portfolio risk at present, though risk is an important factor for investor decision-making.

SEBI should make it mandatory for funds to disclose a simple measure of risk that investors can understand. Value-at-risk is one such measure. JP Morgan made popular this measure of risk in the late 1980s. Its risk management business was later spun off as Riskmetrics.

Importance of risk: Investors have a plethora of funds to choose from. Past returns is a typical measure used to pick funds among peer groups. But sometimes, a portfolio manager may have taken higher risk to generate higher returns. This means that a fund with higher absolute returns may not necessarily be superior to a fund with lower absolute returns. Investors need to pick funds that have the highest risk-adjusted returns to earn optimal returns. But retail investors may not have the necessary resources to compute a useful measure of risk to aid in their decision making process.

Value at Risk: The risk for investors in a mutual fund is the decline in the net asset value (NAV). VaR is a simple measure of risk that can capture this downside. To start with, mutual funds can use a parametric VaR that assumes that returns follow a normal distribution.

Suppose a fund has a portfolio of Rs 1,000 crore, and a one-day VaR of Rs one crore at a 95 per cent confidence interval. This means that the portfolio can lose a maximum of Rs one crore in a one trading day in 95 out of 100 trading days. It also means that in five out 100 days, there is a likelihood of the portfolio losing more than Rs one crore in a single trading day.

A confidence interval is used because we cannot be certain of the losses. The reason is that the suggested VaR model is based on past asset price movements and their historical portfolio joint correlation. And this relationship can change in the future.

Now, VaR is typically described in value terms. This can be converted into a percentage for the convenience of the investors. In the above example, Rs one crore amounts to 0.10 per cent of the portfolio. So, we can say that the portfolio or the net asset value is likely to lose 0.10 per cent on a single trading day in 95 out of 100 days.

But we need a monthly VaR to calculate monthly risk-adjusted returns. The daily VaR can be scaled to a monthly VaR by multiplying the one-day VaR with square root of the number of trading days.

Suppose the monthly VaR is 1.5 per cent, and the monthly return is 5 per cent. Investors can divide the monthly return by the monthly VaR to arrive at the risk-adjusted return. Investors can then use this measure to choose funds among a peer group.

Flipside of VaR: Experts may, of course, point out the flaws in using a simple VaR model to capture risk. The primary objection is that asset returns (especially equity) do not follow a normal distribution. True, but remember, we are not calculating a measure that will help portfolio managers' control risk. The objective of this exercise is to provide investors a simple measure that will enable them to risk-adjust returns. Clearly, the parametric VaR is more sophisticated than the standard deviation, a more commonly used risk measure. The reason is that standard deviation takes into consideration price movements on either side, though investors are only concerned with the downside in asset prices.

Importantly, there is an overwhelming need at present for investors to consider risk-adjusted returns what with the high volatility in asset returns and plethora of funds to choose from. The basic VaR model suggested above serves the purpose. SEBI should mandate mutual funds to publish monthly VaR along with the fund portfolios in the monthly newsletter.

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