Our study is the first to examine the pricing effect of U.S. trade policy uncertainty (TPU) on Chinese stocks. We estimate the U.S. TPU beta, which measures Chinese stock exposure to the U.S. TPU index. Both portfolio analyses and cross-sectional regressions suggest a significantly negative...

We estimate the relative signal jump variance (RSJV) as the difference between the realized positive half-variance and negative half-variance divided by the realized variance using high-frequency intraday data and investigate its role in the cross-sectional pricing in the Chinese stock market....

We study investors' perceptions of inflation through the lens of a high-frequency event study and document that they have a stagflationary view of the world. In response to higher-than-expected inflation, investors expect firms' nominal cash flows to remain stagnant while discount rates...

In this paper, we derive an intertemporal dividend-surprise-augmented asset-pricing model and show that the expected risk premium compensates for stock returns’ exposure to (i) the market-wide dividend-surprise hedge portfolio based on dividend yield surprise and volatilities, in addition to...

This paper examines the potential profit of bull flag trading rules in the Shanghai Stock Exchange Composite Index (SSE) using a template matching technique based on price pattern recognition. This paper fills a gap in the literature by applying a template matching technique for the recognition...

We combine a customized survey and randomized controlled trial (RCT) to study the effect of higher-order beliefs on U.S. retail investors' portfolio allocations. We find that investors' higher-order beliefs about stock market returns are correlated with but distinct from their first-order...

We study the effects of a price transparency shock in the Brazilian OTC equity lending market. Previously, a publicly available stock-specific loan fee benchmark was the average fee of the past 15 trading days. On March 1, 2011, this interval was reduced to 3 days, significantly improving...

We evaluate whether machine learning methods can better model excess portfolio returns compared to the standard regression-based strategies generally used in the finance and econometric literature. We examine 17 benchmark factor model specifications based on Expected Utility Theory and theory...