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...

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...

We analyze the effect of scheduled macroeconomic news on intraday market sentiment by comparing the sentiment of the announcement date with that of the non-announcement date. The announcement of the macroeconomic indicators itself does not change the market sentiment, but the direction of the...

This study comprehensively examines the economic and financial drivers of volatility changes in terms of a cross-country perspective. We exhaustively review a wide range of studies related to financial volatility forecasting and collect a diverse set of prediction variables. By analyzing them...