PT - JOURNAL ARTICLE AU - Keith L. Miller AU - Chee Ooi AU - Hong Li AU - Daniel Giamouridis TI - Size Rotation in the U.S. Equity Market AID - 10.3905/jpm.2013.39.2.116 DP - 2013 Jan 31 TA - The Journal of Portfolio Management PG - 116--127 VI - 39 IP - 2 4099 - https://pm-research.com/content/39/2/116.short 4100 - https://pm-research.com/content/39/2/116.full AB - In this article, Miller, Ooi, Lee, and Giamouridis develop a hybrid model that relies on the nonlinear classification decision tree (DT) approach, and also on multivariate predictive regressions, to help implement a size rotation strategy in the U.S. equity markets. They derive an investment prediction with a two-stage algorithm. In the first stage, they use a decision tree to determine whether large-cap or small-cap stocks will outperform in the subsequent quarter. In the second stage, the authors use a multiple linear regression model to predict whether large-cap stocks will outperform or underperform small-cap stocks in the next quarter. A binary variable obtained from the first stage of the analysis—the DT model—is a key variable in the second-stage model. The authors find that a size rotation strategy based on the proposed hybrid model outperforms strategies based on the constituent models, as well as alternative strategies investigated in other studies.TOPICS: Exchanges/markets/clearinghouses, global, analysis of individual factors/risk premia