Opinion
A Money Manager’s Past Performance Matters More Than Ever
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Absent an outlier or a fluke, the most probable explanation to a high IR is that there’s a process.
By Vasant Dhar
A common disclaimer in the investment business is that “past performance is not indicative of future results.” This is consistent with the Theory of Finance which argues that obvious advantages disappear quickly in a competitive market. Historical evidence largely supports this position: Manager performance is mostly unpredictable from month to month.
The theory rests on some key assumptions, namely, that the money manager is a human whose basis or “investment philosophy” for decision making is discretionary, variable and opaque. But in today’s age of data and algorithms, the theory should be revisited. For starters, algorithms are driven by an explicit “objective function.” If the investment process is algorithmic and invariant then a track record demonstrating how the basis and the process performed under different regimes should provide an expectation of its performance in similar market regimes.
Let’s consider an example. Imagine a human investor who is plugged into markets and makes decisions based on the latest available information. Compare this with a scenario where decisions are generated by an algorithm that ingests similar information and follows a well-defined process without exception. If you observe both over a sufficient period, which one provides more useful information? The obvious answer is the latter example.
Read the full Bloomberg article.
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Vasant Dhar is a Professor of Information Systems.
The theory rests on some key assumptions, namely, that the money manager is a human whose basis or “investment philosophy” for decision making is discretionary, variable and opaque. But in today’s age of data and algorithms, the theory should be revisited. For starters, algorithms are driven by an explicit “objective function.” If the investment process is algorithmic and invariant then a track record demonstrating how the basis and the process performed under different regimes should provide an expectation of its performance in similar market regimes.
Let’s consider an example. Imagine a human investor who is plugged into markets and makes decisions based on the latest available information. Compare this with a scenario where decisions are generated by an algorithm that ingests similar information and follows a well-defined process without exception. If you observe both over a sufficient period, which one provides more useful information? The obvious answer is the latter example.
Read the full Bloomberg article.
___
Vasant Dhar is a Professor of Information Systems.