Abstract
This paper examines the effect of news and social media sentiments on the stock and bond market volatility and their dynamic return correlation over the period 1998−2017. A principal component analysis is used to construct sentiment variables. Results indicate that news sentiments have more pronounced effects on volatility while social media show stronger impacts on the correlation. These sentiments also exhibit strong and significant reflections on volatility persistence. Furthermore, result show economically different impacts of some sentiments across different market states. Finally, an extended model with news sentiments performs better in forecasting returns than the basic and social media ones.
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