We provide empirical evidence of volatility forecasting in relation to asymmetries present in the dynamics of both return and volatility processes. Using recently-developed methodologies to detect jumps from high frequency price data, we estimate the size of positive and negative jumps and...

We provide new empirical evidence on volatility forecasting in relation to asymmetries present in the dynamics of both return and volatility processes. Leverage and volatility feedback effects of the S&P 500 price and volatility dynamics are examined using recently developed methodologies to...

We analyze the impact of sentiment and attention variables on volatility by using a novel and extensive dataset that combines social media, news articles, information consumption, and search engine data. Applying a state-of-the-art sentiment classification technique, we investigate the question...

We empirically investigate how retail and institutional investor attention is related to the way stock markets process information. With a focus on 360 US stocks in the S&P 500 universe, our results show that higher retail investors' attention around news releases increases the post-announcement...