Investing Research Articles

What methods are available to suppress data snooping bias derived from testing multiple strategies/strategy variations on the same set of historical data? Which methods are best? In their March 2018 paper entitled “Systematic Testing of Systematic Trading Strategies”, Kovlin Perumal and Emlyn Flint survey statistical methods for suppressing data snooping bias and compare effectiveness of these methods on simulated… Keep Reading

See the notes on Chapter 6 in “Evidence-Based Technical Analysis: Applying the Scientific Method and Statistical Inference to Trading Signals (Chapter-by-Chapter Review)” for some qualitative aspects of data snooping bias. The book itself presents the mathematics of correcting for data snooping bias.

A subscriber flagged an apparently very attractive exchange-traded fund (ETF) momentum-volatility-correlation strategy that, as presented, generates a optimal compound annual growth rate of 45.7% with modest maximum drawdown. The strategy chooses from among the following seven ETFs: ProShares Ultra S&P500 (SSO) SPDR EURO STOXX 50 (FEZ) iShares MSCI Emerging Markets (EEM) iShares Latin America 40… Keep Reading

…”much of the wisdom comprising the popular version of TA does not qualify as legitimate knowledge,” and “TA must evolve into a rigorous observational science if it is to deliver on its claims and remain relevant.”

Are there any seasonal, technical or fundamental strategies that reliably time the U.S. stock market as proxied by the S&P 500 Total Return Index? In the February 2018 version of his paper entitled “Investing In The S&P 500 Index: Can Anything Beat the Buy-And-Hold Strategy?”, Hubert Dichtl compares excess returns (relative to the U.S. Treasury… Keep Reading

…even though S&P 500 index timing rules based on fundamental indicators and investor sentiment indicators might significantly beat a buy-and-hold benchmark when evaluated in isolation, this outperformance generally evaporates after correcting for data snooping bias. In other words, luck is the dominant differentiator of rule performance.

…potential issues regarding sample size, data quality, data snooping bias and look-ahead bias undermine belief in this study’s conclusion that changes in the population for age nine in the U.S. accurately predict U.S. stock market returns. Also, smoothing rules applied in variable construction obscure exploitability.

Best guess is that combining low volatility with high momentum might offer an edge…

How should researchers address the issue of aggregate/cumulative data snooping bias, which derives from many researchers exploring approximately the same data over time? In the October 2014 version of their paper entitled “. . . and the Cross-Section of Expected Returns”, Campbell Harvey, Yan Liu and Heqing Zhu examine this issue with respect to studies… Keep Reading

Is data snooping bias a material issue for cross-sectional stock return anomalies published in leading journals? In the September 2017 update of their paper entitled “Publication Bias and the Cross-Section of Stock Returns”, Andrew Chen and Tom Zimmermann: (1) develop an estimator for anomaly data snooping bias based on noisiness of associated returns; (2) apply it to replications… Keep Reading