Quantopian's community platform is shutting down. Please read this post for more information and download your code.
Back to Community
NYT on the dangers of data mining
2 responses

Interesting article, thanks for sharing. I think these articles are valuable in that they dampen the hype a little. However, while it's true that with more comparisons the risk of a spurious correlation increases I don't think the answer is to stop looking. Instead, I think we should still be looking but correcting for multiple comparisons (e.g. Bonferroni). The more you look, the more evidence you require to deem something interesting.

Disclaimer

The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by Quantopian. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. No information contained herein should be regarded as a suggestion to engage in or refrain from any investment-related course of action as none of Quantopian nor any of its affiliates is undertaking to provide investment advice, act as an adviser to any plan or entity subject to the Employee Retirement Income Security Act of 1974, as amended, individual retirement account or individual retirement annuity, or give advice in a fiduciary capacity with respect to the materials presented herein. If you are an individual retirement or other investor, contact your financial advisor or other fiduciary unrelated to Quantopian about whether any given investment idea, strategy, product or service described herein may be appropriate for your circumstances. All investments involve risk, including loss of principal. Quantopian makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances.

I absolutely agree, or I wouldn't be here! I personally believe that market anomalies with a plausible explanation in behavioral finance/psychology have a better chance of out-of-sample alpha, but I have no evidence to back up that belief. The "low volatility" anomaly is a good example (that I have invested by): if people are more envious than greedy, it might be real. If portfolio managers are leverage-constrained, it might be real. If people prefer long-shot payoffs, it might be real. Etc etc.

So, if you find an anomaly via data-mining that has a plausible explanation, by all means, follow up. If, however, the moving average convergence/divergence of coffee futures seems to portend a widening of corporate bond spreads, I'd probably not waste my time.