This study investigates the cross-country impact of U.S. equity market skewness risk. We find that a large decrease in the U.S. market skewness significantly predicts high future returns on international equity markets. The predictability remains significant after controlling for a set of U.S....

While numerous studies have analyzed the asset allocation issue of US stock market from various angles, much less attention has been paid to the asset allocation issue of Chinese stock market. This article investigates the asset allocation in Chinese stock market from a perspective of...

This study investigates the association between stock liquidity and the H-share discount using a sample of Chinese cross-listed stocks in A- and H-shares markets. We examine the liquidity hypothesis by employing depth and trading activity variables. Our results suggest that stocks with a higher...

While economic variables have been used extensively to forecast bond risk premia, little attention has been paid to technical indicators which are widely used by practitioners. In this paper, we study the predictive ability of a variety of technical indicators vis-a-vis the economic variables....

This paper studies the intertemporal relation between U.S. volatility risk and international equity risk premia. We show that a common volatility risk factor constructed from the option-implied U.S. forward variances positively and significantly predicts future stock market returns of the...

We propose a novel measure of firm-level investor sentiment based on the divergence of stock market beta from that of its industry peers. We show that this measure coincides with investor sentiment. In the cross-section, stocks with high investor sentiment significantly underperform those with...

Using the long-term wavelet component of monthly S&P 500 excess returns as supervision information, we employ a machine learning method to extract the common predictive information of 14 prevalent macroeconomic variables, and construct a new macroeconomic index aligned for predicting stock...

Our study presents novel evidence of the pricing effectiveness of sparse macroeconomic risks at the firm level and the underlying economic regimes. Specifically, we employ sparse PCA approach to aggregate macroeconomic variables from the FRED-MD database and obtain the first 8 components,...

We compare several representative sophisticated model averaging and variable selection techniques of forecasting stock returns. When estimated traditionally, our results confirm that the simple combination of individual predictors is superior. However, sophisticated models improve dramatically...

Markowitz's mean-variance portfolio optimization is either inefficient or impossible when the number of assets becomes relatively large. To overcome this difficulty, we propose several component-wise boosting learning methods that, in a linear regression specification, can iteratively select the...