In this paper, we provide evidence on two alternative mechanisms of interaction between returns and volatilities: the leverage effect and the volatility feedback effect. We stress the importance of distinguishing between realized volatility and implied volatility, and find that implied...

We investigate changepoints in the cross-section of stock returns using an ensemble of dedicated unsupervised learning methods. Our large-scale study reveals a sustained incidence of changepoints in the mean, variance, and distribution. This finding is robust to the choice of the changepoint...

In 1936, John Maynard Keynes proposed that emotions and instincts are pivotal in decision-making, particularly for investors. Both positive and negative moods can influence judgments and decisions, extending to economic and financial choices. Intuitions, emotional states, and biases...

Using a sample of 97 stock return anomalies, we find that anomaly returns are 50% higher on corporate news days and are 6 times higher on earnings announcement days. These results could be explained by dynamic risk, mispricing via biased expectations, and data mining. We develop and conduct...

The issue of long memory, though has important theoretical and practical implications, has not received much attention in India. This article examines the issue of long memory in mean of the stock returns by employing a set of sophisticated time-series tests including a bias reduced log...

Three concepts: stochastic discount factors, multi-beta pricing and mean-variance efficiency, are at the core of modern empirical asset pricing. This chapter reviews these paradigms and the relations among them, concentrating on conditional asset-pricing models where lagged variables serve as...

This paper exploits different machine learning models to forecast of stock returns. We find that machine learning models substantially improve the performance of various variables in predicting stock returns. Technical indicators generate a significantly better result than the stock...

We study the out-of-sample and post-publication return-predictability of 97 variables that academic studies show to predict cross-sectional stock returns. Portfolio returns are 26% lower out-of-sample and 58% lower post-publication. The out-of-sample decline is an upper bound estimate of data...

We reexamine long-term abnormal returns for portfolios sorted on governance characteristics. Firms with strong shareholder rights and firms with weak shareholder rights differ from the population of firms and from each other in how they cluster across industries. Using well-specified tests under...