In a world of low rates and high stock prices, it's natural many investors are looking for ways to earn a good return with limited exposure to equities. However, many candidate strategies have return distributions which are significantly different from the Normal and Log-normal distributions...

This paper presents a synthesized model explaining the returns of short-sale constrained stocks. We combine short-sale constraints that were previously treated individually or in pairs into a more fully specified model. The model is also specified in generally falling versus generally rising...

Using a large sample of U.S. firms during 1987–2011, we find robust evidence that the issuance of seasoned equity is associated with abnormally high future stock price crash risk. The association between seasoned equity offerings and crash risk is stronger among offerings that involve the sale...

We provide a new monthly cross-sectional measure of stock market tail risk, defined as the average of the daily cross-sectional tail risk, rather than the tail risk of the pooled daily returns within a month. The former better captures monthly tail risk rather than merely the tail risk on...

Many studies document predictable stock returns known as anomalies. We investigate whether insiders exploit anomalies and the consequences of mandatory disclosure using a large backward-extended insider trading database from 1975 to 2014. Our results suggest that all 13 anomalies we consider are...

Early in the 1950s, academics and investors started proposing in earnest a variety of summary statistics to capture in a single number the quality of an investment. Sharpe Ratio became the most commonly used, and it's an important metric, but maximizing Sharpe Ratio doesn't always maximize...

Prediction of stock prices using econometrics and machine learning based approaches poses significant challenges to the research community since the movement of stock prices are essentially random in its nature. With the rapid development and evolution of algorithms using sophisticated machine...

For mean-variance investors, using predictive information unconditionally optimally produces better portfolios than using predictive information conditionally optimally. The latter is more usually done in practice. Empirically, the unconditionally optimal portfolios have higher Sharpe ratios and...

This paper analyzes stocks' price behavior after IPO events in the pharmaceutical sector and explores the role of social media in determining this behavior. The results indicate positive and significant cumulative average abnormal returns (CAAR) of 3.70% in the first 20 days following an IPO...

This study examines the language effect on investing using the Google search records of Chinese- versus English-speaking searchers. First, we find that the attention of Chinese speakers induces that of English speakers, increases abnormal news coverage, and has better predictability on stock...