This study compares the information content of funds from operation (FFO) and net income (NI) in the real estate investment trust (REIT) industry. We find that models using FFO explain more of the variance in cumulative abnormal returns around earnings announcement dates than models using NI do....

This study investigates the economic and financial drivers of volatility changes and integrates them into stock market volatility forecasting. We first collect a diverse set of predictor variables and analyze them within a unified framework. We discover that only a small number of variables...

We study options market participants’ trading behavior before and after the options multiplier increases. After the options multiplier increases, the options market becomes more efficient. By analyzing the high-frequency microstructure dataset, we show that local retail and local institutional...

This study predicts stock market volatility and applies them to the standard problem in finance, namely, asset allocation. Based on machine learning and model averaging approaches, we integrate the drivers’ predictive information to forecast market volatilities. Using various evaluation...