STREET DOGS

From Jason Zweig: The problem of “p-hacking”, or dredging through an ocean of data until you find a pattern you can present as statistically significant, is endemic to research in finance. You should approach all claims of market-beating patterns with extreme scepticism.

Campbell Harvey, a finance professor at Duke University, estimates that at least half of all “discoveries” in investment research (thus the expectations of investors in funds based on them) are false … that so much data is available in finance that someone searching for a pattern “predicting” outperformance is all but certain to find one — even by statistical fluke alone.

The incentives to find a pattern are huge and the costs are minimal. Supply a smart young analyst with a computer and plenty of pizza and in a matter of days or weeks you will have a set of data full of patterns – many of them probably spurious — that you can market to investors.

In the US you can now buy exchange-traded funds that own the 60 stocks with the highest dividend yield among the biggest 900 US companies, weighted by their total sales; all big US stocks in opposite proportion to their recent volatility; equal proportions of every major infrastructure partnership that pays a high dividend; short-term, high-yield bonds weighted by the total debt outstanding from each issuer; equal stakes in about 250 companies that support workplace equality regardless of gender orientation; companies in the Middle East in proportion to the size of their dividends; and the biggest US bank stocks in proportion to their total revenues.

Some of these might turn out to be great investment ideas. Unfortunately, the odds are that many of them will turn out to be nothing more than patterns that appear to have worked in the past that have no predictive power for the future.