Manager’s strategy: Risk and Standard Deviation:
Even within one particular investment style there can be a wide range in the returns that they deliver (volatility). Understanding a manager’s sub-style can provide insight into what risks may be an integral part of the strategy.
For example, you might select a multi-cap value manager with a deep value sub-style without understanding the volatility in the excess return that this manager seeks to generate. However there is no such fund available in India which distinguishes between Value and Deep Value in its strategy. In fact in India the great regulator does not insist that the fund house tell you the investment style, so all fund houses get away not describing the style. I find Franklin Templeton the only fund which describes its style and being true to label.
The absolute risk in a deep value portfolio, as measured by standard deviation, might be low relative to the large cap value benchmark’s standard deviation. However, the manager’s returns could be DRAMATICALLY different from the benchmark’s returns. For example when I see people investing in Templeton India Growth fund of Icici Pru Value Discovery fund I keep wondering whether the investor realizes that the only way to compare both these funds to the benchmark is to take a 5 year block view preferably on an SIP basis. It is almost impossible for value (or deep value) fund to keep pace with the benchmark (in fact the objective is not that at all). In other words, though the absolute risk—as measured by volatility—may be low, the relative risk could be high.
It would be interesting to see how the Tracking error can be used in such cases. If I were a value fund manager, I would not want any ‘benchmark’ except the sensex and that too on a 5 year rolling return basis / SIP basis.
Evaluating risk using standard deviation alone
Standard deviation is academically used to measure risk; however, standard deviation rarely (never?) reflects the true overall potential risk in a portfolio and should never (cannot) be used as the only determinant of risk. While standard deviation helps in measuring the (historical) volatility of returns in a portfolio and in assessing how portfolio returns have fluctuated relative (to the mean) or to other investments, it is not as effective (or useful for investment reactions) for shorter measurement periods (i.e., fewer than (say) five years of monthly or quarterly returns). This is because standard deviation does not reveal the portfolio’s underlying holdings, industry, style, time frames for holding cash, or market capitalization concentration. Also, standard deviation is typically highly correlated to market volatility, making it difficult (impossible) to isolate individual strategy risk from general market risk.
Misconstruing good manager selection for good portfolio construction
There are significant shortcomings in the all-too-common methodology of “constructing” a portfolio simply by selecting “good” managers for each asset class. Yes, it is wrong, but in India there is not much choice is there? I would choose a Bluechip over a Focused Bluechip for the longer term, but in the short term I might consider a Focused Bluechip too. However, when I get into the Value space my choice is severely restricted.
The overlap and correlations between and among managers of different styles can create unintended exposures or overweights. Remember we do have overlap calculators, but sometimes overlap is inevitable.
For example, the combination of a multi cap value manager with a tilt toward larger cap stocks and a large cap manager with an overweight to mid cap stocks would most likely create an overexposure to the mid/large cap sectors.
Thus, greater emphasis should be placed on evaluating the combination of investments to judge whether the blended exposure corresponds with the intended asset allocation.
Or you say, Dammit, I like this fund manager, so I will stay here.
Investing your own money has one huge, huge advantage – the world does not know how badly you screwed up. YOU are the accused, judge, jury, and hangman 🙂
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