Most investors often rely on a simple search and ranking across managers to find the best trading strategies. For example, sort by the highest Sharpe ratio and choose the manager with the highest number; then you have a winner. Alternatively, search for a manager with a minimum Sharpe ratio and then conduct due diligence as a two-step process.
Unfortunately, life is more complicated. There is a distribution of Sharpe ratios across managers and over time, based on the strategy type and analysis used. If there is an average Sharpe for a strategy, then outliers on the high side may not be following the strategy named, or they may be subject to mean-reversion. The Sharpe ratio for any period may differ, so the last three years may not be representative of the manager's performance over the long run. There is a reversion to the mean when you sample the Sharpe ratio for a set of managers over a specific timeframe. Time and context matter.
If you look at enough managers, you will find some that are perceived to have an edge based on the sample data collected, yet this analysis may generate a false signal. For managers, you need to examine the sample set that has been analyzed. For quantitative strategies, you need to consider the backtesting performance and the length of time reviewed for the strategy. Again, sample size matters.
Unfortunately, life is more complicated. There is a distribution of Sharpe ratios across managers and over time, based on the strategy type and analysis used. If there is an average Sharpe for a strategy, then outliers on the high side may not be following the strategy named, or they may be subject to mean-reversion. The Sharpe ratio for any period may differ, so the last three years may not be representative of the manager's performance over the long run. There is a reversion to the mean when you sample the Sharpe ratio for a set of managers over a specific timeframe. Time and context matter.
If you look at enough managers, you will find some that are perceived to have an edge based on the sample data collected, yet this analysis may generate a false signal. For managers, you need to examine the sample set that has been analyzed. For quantitative strategies, you need to consider the backtesting performance and the length of time reviewed for the strategy. Again, sample size matters.
Additionally, evaluation is usually not concluded with the numbers but through extensive discussion with the manager to find their edge, yet the edge narrative or the manager's story-telling is inherently subjective. Is the choice of the manager a function of their skill at describing what they do or what they actually do?
Perhaps a critical selection skill is reviewing why you chose a manager who failed as well as looking at the managers that you rejected who then went on to perform better than your existing portfolio. What your selection impacted by bad luck, and where the managers you rejected subject to good luck, or in either case did you miss something that is not in your due diligence analysis.
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