Pseudo-mathematics and financial charlatanism: the effects of backtest overfitting on out-of-sample performance

Title: Pseudo-mathematics and financial charlatanism: the effects of backtest overfitting on out-of-sample performance
Creator: Bailey, David H.; Borwein, Jonathan M.; de Prado, Marcos López; Zhu, Qiji Jim
Relation: Notices of the American Mathematical Society Vol. 61, Issue 5, p. 458-471
Publisher Link: http://dx.doi.org/10.1090/noti1105
Publisher: American Mathematical Society
Resource Type: journal article
Date: 2014
Description: A backtest is a historical simulation of an algorithmic investment strategy. Among other things, it computes the series of profits and losses that such strategy would have generated had that algorithm been run over that time period. Popular performance statistics, such as the Sharpe ratio or the Information ratio, are used to quantify the backtested strategy’s return on risk. Investors typically study those backtest statistics and then allocate capital to the best performing scheme.
Subject: backtest; algorithmic investment strategy; profits; loss; out-of-sample performance
Identifier: http://hdl.handle.net/1959.13/1303607
Identifier: uon:20685
Identifier: ISSN:0002-9920
Language: eng
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