Investing Research Articles

Investors typically employ backtests to estimate future performance of investment strategies. Two approaches to assess in-sample optimization bias in such backtests are: Reserve (hold out) some of the historical data for out-of-sample testing. However, surreptitious direct use or indirect use (as in strategy construction based on the work of others) of hold-out data may contaminate its independence…. Keep Reading

Iterative testing of strategies on a set of data introduces snooping bias, such that a winning (losing) strategy is to some degree lucky (unlucky). Sharing of strategies across a community of researchers carries the luck forward, with accretion of additional bias from testing by subsequent researchers. Is there a rigorous way to account for this… Keep Reading

How should investors interpret findings of statistical significance in academic studies of financial markets? In the March 2014 draft of their paper entitled “Significance Testing in Empirical Finance: A Critical Review and Assessment”, Jae Kim and Philip Ji review significance testing in recent research on financial markets. They focus on interplay of two types of… Keep Reading

What are the main investment behaviors of emerging markets and component stocks? In their January 2014 paper entitled “Studies of Equity Returns in Emerging Markets: A Literature Review”, Yigit Atilgan, Ozgur Demirtas and Koray Simsek survey the stream of research on emerging markets equity return predictability and volatility. This survey covers articles in the top four finance journals (Journal of… Keep Reading

How can researchers account for the snooping bias derived from testing of multiple strategy alternatives on the same set of data? In the July 2014 version of their paper entitled “Evaluating Trading Strategies”, Campbell Harvey and Yan Liu describe tools that adjust strategy evaluation for multiple testing. They note that conventional thresholds for statistical significance assume an independent… Keep Reading

Are the widely used Fama-French three-factor model (market, size, book-to-market ratio) and the Carhart four-factor model (adding momentum) the best factor models of stock returns? In their September 2014 paper entitled “Digesting Anomalies: An Investment Approach”, Kewei Hou, Chen Xue and Lu Zhang construct the q-factor model comprised of market, size, investment and profitability factors and test its ability to predict… Keep Reading

Does adding profitability and asset growth (investment) factors improve the performance of the widely used Fama-French three-factor (market, size, book-to-market) model of stock returns? In the September 2014 version of their paper entitled “A Five-Factor Asset Pricing Model” Eugene Fama and Kenneth French assess whether extensions of their three-factor model to include profitability and investment… Keep Reading

Why and how should investors pursue investment premiums associated with factors that explain performance differences among related assets (like common stocks)? In the January 2015 version of his paper entitled “Better Investing Through Factors, Regimes and Sensitivity Analysis”, Cristian Homescu summarizes recent research on: (1) factor-based investing; (2) enhancement of factor-based investing via regime switching models; and, (3) strategy robustness testing. Factor… Keep Reading

What are the most pressing systematic weaknesses in financial research, and how should the investment community address them? In the May 2015 version of his article entitled “The Future of Empirical Finance”, Marcos Lopez de Prado identifies three major problems in empirical finance and proposes ways to mitigate them. Based on his experience and common sense arguments and references… Keep Reading

Is it possible to test factor models of stock returns directly on individual stocks rather than on portfolios of stocks sorted per preconceived notions of factor importance. In their November 2015 paper entitled “Tests of Alternative Asset Pricing Models Using Individual Security Returns and a New Multivariate F-Test”, Shafiqur Rahman, Matthew Schneider and Gary Antonacci apply a statistical… Keep Reading