Tags
2017, alpha, beta, Fund, funds, investing, mathematics, measures, mutual fund, mutual fund investment, mutual funds, mutual funds investment, rsquared, statistical
In the past, I have almost never posted anything regarding calculations or statistical measures used in mutual fund investing. In the coming posts, as well as a means to improve my tools of trade, I will start to incorporate any measures that I find useful and worthy of mentioning to anyone interested in investing.
While most of the measures I mentioned have been widely and perhaps even better described than I did, I’m treating these posts of mine as a way to test my understanding as well, to see if I’m capable of explaining these to the readers.
Since this the first post of such topic, I’ll be starting with 3 most widely seen measures; Alpha, Beta and R-Squared.
Alpha
A measure of performance of a fund against its expected return, which have its calculation based on beta. Excess returns, as how it was called by some. An example is, if Fund A is expected to gain 10%, but realized a 15% return, the fund is said to have 5.0 as its alpha. Alpha can be used as a measure to gauge the performance of fund managers that both have portfolio focusing in the same market. A higher alpha in this case, means a better fund manager in capturing extra profits than the others.
Beta
A measure of volatility against an identified index, a larger beta means a more volatile performance, in other words how sensitive the fund is against the index movements. The range can be negative to beyond 1.0. In a simpler way of saying, a fund with beta 1.0, its volatility will mirror exactly the index, and a fund with beta < 1.0 means a less volatile performance. If the beta is below 0.0, this would means the fund’s performance is having an inverse relationship with the index. For beta to be > 1.0, this means the fund is more volatile than the index, e.g. for beta of 2.0, the performance of the fund against the index is doubled.
R-Squared
A measure of the funds performance as a result of the benchmark in percentage. The range will be 0 to 1 or 0% to 100%. In layman’s term, the performance of the fund itself, can be explained by the benchmark movement, for example, a 0% R-Squared value means none of the movement in the fund is explained by the benchmark index of the fund, a 100% R-Squared value means all of the movements can be explained by the benchmark itself. If the R-Squared is low (<50%), the beta is not a good indicator of the fund volatility, because the relationship between the fund and its benchmark is too weak to be useful at all.