Risk management within hedge funds uses many of the same techniques used by traditional fund management, such as Jenssen's alpha, the sharp ratio, and value at risk. There are, however, a number of issues hedge funds face in using these techniques. So care must be taken in analyzing hedge funds using these approaches.
Jensen's measure or Jensen's alpha is a risk adjusted performance measure that represents the average return on a portfolio or investment above or below that predicted by the capital asset pricing model CAPM, given the portfolio or investments beta and the average market return. If Jensen's alpha is positive, it means that a fund has generated more return than would be expected by CAPM indicating good performance by the fund manager relative to the risk that has been taken. An alternative measure is the Sharpe ratio, which is the average return earned in excess of the risk-free rate of return per unit of volatility or risk taken. Volatility is a measure of the price fluctuation of an asset or portfolio. The higher the Sharpe ratio, the better. Comparing ratios across a range of available funds helps investors appraise performance on a like with like or risk adjusted basis.
Value at risk is a statistic that quantifies the extent of possible financial losses within a firm portfolio or position over a specific timeframe. This can be based on an expected distribution of losses. On the left-hand side, an assumption has been made that losses are symmetrically distributed following a pattern referred to as the normal distribution. If this is the case, then the expected loss a fund might be expected to make would be 50% of the way along the distribution, which also happens to match the highest probability of that outcome occurring. It is also possible to draw confidence intervals around this most likely outcome for losses or the expected loss to allow a fund to say, for example, they are 67% sure that the losses a fund makes will fall into a certain range, one standard deviation or sigma above or below that expected loss level. However, what value at risk tries to capture is not the most likely outcome for losses, but what the maximum loss might be with a given probability. Giving a picture of the downside risk a fund might face, or in other words, how bad things could get for the fund within that certain probability. As such, VAR or value at risk captures the highest, highest losses the fund will be expected to make over a particular timeframe with a given level of probability. So here that is shown to be 99.9%, so the VAR or unexpected loss will be the highest loss. The fund will be expected to make 99.9% of the time over that specific timeframe. It's worth noting that this doesn't capture the maximum loss ever that this fund might face, but only within this given probability. As such, hedge fund managers and risk managers within hedge funds can use VAR to measure and control the level of risk exposure within a fund. However, not all fund returns are normally distributed, and it's not uncommon for funds to have lost distributions, which are positively skewed, meaning the chance of a higher loss is greater than would be predicted by the normal distribution alone. As such, an assumption of normally distributed returns can lead to an underestimate of the real risk the fund is exposed to. This is because standard deviation is not a complete measure of risk.
