Measuring and Managing Risk

The job of the fund manager is to select and manage a portfolio of assets, according to a mandate, which produces the best possible results at the lowest possible level of risk. Going back to our racing pool, it is clear that, once in a while, people get lucky and win money on the outsiders. But it is the punter who knows his horses and his odds who, hopefully, can enjoy his sport without losing his shirt.

There is a saying that you can't manage something if you can't measure it. This certainly seems true of risk in the financial markets. In prosaic terms, risk statistics are about measuring inherent riskiness of different securities and asset classes, and about differentiating the fund managers who just got lucky from the ones that know their horses. In other words, they help us to identify fund managers who achieve returns at an acceptable level of risk.

Standard Deviation / Volatility

Standard deviation is a measure of the 'dispersion' of a data set (ie, to what extent the data is dispersed around its average). A flat line has a standard deviation of zero. Unpredictable data has a high standard deviation.

In order to make standard deviation comparable for stocks and funds it is usually calculated using the month-on-month percentage price change over 36 months. A low standard deviation of returns (also called low volatility) indicates a fund that, historically, has been comparatively low-risk. A high volatility figure indicates a higher-risk fund. The absolute levels of volatility shift over time depending on the fluctuations in the markets (ie, share prices, bond prices and other asset prices), so it is difficult to give general guidelines. The top of the volatility scale for South African unit trusts has ranged between 8 and 12 over the past ten years. Money market funds have volatility of zero (because of constant unit pricing), and the most conservative bond and income funds usually have volatilities of below 2. General equity funds can be anywhere between 4 and 8, depending on market conditions. Note that these are rough guidelines which may not be valid under all market conditions.


Maximum Drawdown

This risk measure shows the most the fund has lost at any point in the defined period over an unbroken series of down movements (using month-end prices). It can be thought of as the maximum percentage reversal in the price of the fund measured from a peak to a trough.

Sharpe Ratio

Named after Nobel laureate William F Sharpe, the Sharpe ratio was originally called the reward-to-variability ratio. It was designed to show the 'excess return' per unit of risk taken. It is typically calculated by subtracting a risk-free rate -- such as an overnight call rate or bankers' acceptance rate -- from the rate of return achieved by a fund and then dividing the result by portfolio volatility. The performance of other benchmarks can also be used to determine the 'excess return'.

The Sharpe ratio gives an indication of whether the excess return was due to clever investment decisions or simply a result of taking big risks. The higher the Sharpe ratio, the better the fund's historical risk-adjusted performance.


Sortino Ratio

Developed by Frank Sortino, this ratio is a variation of the Sharpe ratio which takes into account downside volatility only (the Sharpe ratio penalises both downside and upside volatility equally). Like Sharpe, the Sortino ratio measures the excess return over a risk-free rate or benchmark, but Sortino only uses downside deviation in calculating risk. One consequence is that Sortino gives a higher score to a fund which rises more than it falls, even if this fund has the same overall volatility as another. As with Sharpe, a higher Sortino ratio means a better risk-adjusted return.


Performance Consistency

One of the risks in using past performance to evaluate funds is that the top performers may not be able to repeat or sustain past returns. Consistency of performance measures seek to identify funds that consistently provide the best returns, usually in comparison to the fund's peers.

Click here for more information about the methodology used to calculate consistency of performance for FundsData Online.