We document that acquiring firms are more likely than non-acquiring firms to split their stocks before making acquisition announcements, especially when acquisitions are financed by stock and when the deals are large. Our findings support the hypothesis that some acquiring firms use stock splits...

Whether higher idiosyncratic return volatility means more or less informative stock prices is an ongoing debate. All the existing literature relies on cross-sectional evidence, which makes it hard to isolate the effects of price informativeness on idiosyncratic volatility from other effects. I...

In the absence of market imperfections, the mutuality principle leads to efficient risk sharing and the Pareto optimal asset allocations. With market imperfections such as transaction costs and information asymmetry, risk-sharing becomes costly, and it can even lead to financial crises. We...

This study predicts stock splits using two ensemble machine learning techniques: gradient boosting machines (GBMs) and random forests (RFs). The goal is to form implementable portfolios based on positive predictions to generate abnormal returns. Since splits are rare events, we use SMOTE...