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Exploiting News Analytics for Volatility Forecasting
This study investigates the potential of news sentiment in predicting stock market volatility. We augment traditional time series models of realized volatility with the sentiment of macroeconomic and firm-specific news. Our results demonstrate that incorporating the sentiment of domestic macroeconomic news significantly improves volatility predictions for individual stocks and the S&P 500 Index. Notably, we find substantial enhancements in long-horizon volatility predictions when including the sentiment of macroeconomic news in the regression models. In contrast, firm-specific news sentiment shows only modest predictive power in the general framework. However, expanding the set of predictors to include the news count of firm-specific news occurring overnight between two consecutive trading periods significantly improves one-period-ahead volatility forecasts.
期刊介绍：
The Journal of Applied Econometrics is an international journal published bi-monthly, plus 1 additional issue (total 7 issues). It aims to publish articles of high quality dealing with the application of existing as well as new econometric techniques to a wide variety of problems in economics and related subjects, covering topics in measurement, estimation, testing, forecasting, and policy analysis. The emphasis is on the careful and rigorous application of econometric techniques and the appropriate interpretation of the results. The economic content of the articles is stressed. A special feature of the Journal is its emphasis on the replicability of results by other researchers. To achieve this aim, authors are expected to make available a complete set of the data used as well as any specialised computer programs employed through a readily accessible medium, preferably in a machine-readable form. The use of microcomputers in applied research and transferability of data is emphasised. The Journal also features occasional sections of short papers re-evaluating previously published papers. The intention of the Journal of Applied Econometrics is to provide an outlet for innovative, quantitative research in economics which cuts across areas of specialisation, involves transferable techniques, and is easily replicable by other researchers. Contributions that introduce statistical methods that are applicable to a variety of economic problems are actively encouraged. The Journal also aims to publish review and survey articles that make recent developments in the field of theoretical and applied econometrics more readily accessible to applied economists in general.
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