Undiversifiable (or systematic risk) has long been an enemy of investors. Many countercyclical strategies have been developed to counter this. However, like all insurance types, these strategies are generally costly to implement, and over time can significantly reduce portfolio returns in long...

The Baker and Wurgler (2006) sentiment index purports to measure irrational investor sentiment, while the University of Michigan Consumer Sentiment Index is designed to largely reflect fundamentals. Removing this fundamental component from the Baker and Wurgler index creates an index of investor...

The real estate investment trust (REIT) industry experienced a liquidity crisis resulting from reduced access to credit commitments as banks were restoring their balance sheets during the 2007-2009 financial crisis. Employing generalized autoregressive conditional heteroscedasticity (GARCH)...

Volatility is an important component of asset pricing; an increase in volatility on markets can trigger changes in the risk distribution of financial assets. In conventional financial theory, investors are considered to be rational and any changes in relevant risk are assumed to be a result of...

News move markets and contains incremental information about stock reactions. Future trading volumes, volatility and returns are a ected by sentiments of texts and opinions expressed in articles. Earlier work of sentiment distillation of stock news suggests that risk prole reactions might differ...

Sentiment indices based on investor sentiment surveys attempt to measure the stock market sentiment. The literature on these indices focusses mainly on whether investor sentiment influences the financial markets or not. But the term “sentiment” has never been defined in the literature....

News carry information of market moves. The gargantuan plethora of opinions, facts and tweets on financial business offers the opportunity to test and analyze the influence of such text sources on future directions of stocks. It also creates though the necessity to distill via statistical...

Recent advances in natural language processing have contributed to the development of market sentiment measures through text content analysis in news providers and social media. The effectiveness of these sentiment variables depends on the implemented techniques and the type of source on which...

This study examines the relationship between positive and negative investor sentiments and stock market returns and volatility in Group of 20 countries using various methods, including panel regression with fixed effects, panel quantile regressions, a panel vector autoregression (PVAR) model,...

We apply machine-learning techniques to predict drug approvals using drug-development and clinical-trial data from 2003 to 2015 involving several thousand drug-indication pairs with over 140 features across 15 disease groups. To deal with missing data, we use imputation methods that allow us to...