Traditional heuristics for evaluating performance in investment committees lack the sophistication required for modern analysis. Emphasis should be placed on quantifying metrics rather than relying on subjective judgments. The shift towards analytics in finance, as seen through the lens of portfolio analysis, highlights the importance of measuring dispersion—a crucial metric for understanding the effectiveness of strategies in non-factor portfolios. Leveraging data not only enhances decision-making but also illuminates the underlying value that can be achieved in investment choices.
One of the problems in investing or trading is that — to use a common disclaimer — past results are no guarantee of future success. Someone can have a great track record in their stock picks, but maybe they just got lucky. Or maybe they were particularly well-dialed into one market regime that inevitably shifts. Or maybe they're actually just better than other traders. For multi-strategy hedge funds or "pod shops," there's an ongoing battle to hire or train the next great portfolio manager. But how can managers tell who is actually good and who isn't? On this episode of the podcast, we speak with Joe Peta, who was previously the head of performance analytics at Point72 Asset Management and has had a long career in the trading world. He's also an avid fan of sports gambling, and the author of the recent book, Moneyball for the Money Set, which attempts to take some of the talent analytical principles that originated in Major League Baseball and apply them to evaluating portfolio managers. He talks us through the traditional approach funds use to find or create superstars, and how these approaches can be improved upon using more rigorous, quantitative methods.
Mentioned in this episode:
Hedge Fund Talent Schools Are Looking for the Perfect Trader
How to Succeed at Multi-Strategy Hedge Funds
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