Example https://www.quantopian.com/posts/new-challenge-build-smart-beta-factors
I probably don't understand something fundamental on how challenge submissions are evaluated. Naively I'd think if all data is known about a past time period, most algorithms can be backfitted to look good for that period, for just about any metric.
How can the jury differentiate between truly valuable factors, and backfitted ones?
Quantopian evaluates winners on both in-sample (i.e. the period they list in the challenge) as well as out-of-sample (the ~2 years of data they hold out from the community) performance. They often also use true out-of-sample data by running the algorithms after every trading day. Looking at all of these things combined, with some different weighting metrics, etc., they can arrive at a "score" that weeds out most of overfit strategies that you're describing.
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.
