Research

Following research is ongoing.

• Equity Premium Prediction with Shrinkage Estimation Guided by Economic Theory
  with Xiaobin Liu, Yanchu Liu and Tao Zeng
  Abstract： We demonstrate that economic linkages between predictors and the real economy, combined with theory-implied parameter restrictions, substantially enhance out-of-sample equity premium forecasting performance. We introduce a novel empirical Bayes (EB) framework that captures these economic relationships while accommodating theoretical constraints on predictor coefficients. Our EB methodology optimally shrinks coefficient estimates toward intermediate values between unrestricted OLS estimates and theory-implied restricted estimates. Empirical applications reveal improved forecasting performance across numerous established predictors. Using two comprehensive datasets, we document superior EB forecasting performance compared to traditional OLS methods. The improvements become particularly pronounced when implementing classic economic constraints following Campbell and Thompson (2008) and Pettenuzzo, Timmermann, and Valkanov (2014). These findings provide new insights into the crucial role of economic theory in time-series predictability and demonstrate how theory-implied parameter restrictions enhance predictive accuracy.
  Keywords： Empirical Bayes, Shrinkage estimator, Equity premium prediction