Using news analytics data in GARCH models
In this paper we analyze the impact of extraneous sources of information (viz. news and trade volume) on stock volatility by considering some augmented GARCH models. We suppose that trading volume can be considered as a proportional proxy for information arrivals to the market. Then we will consider the daily number of press releases on a stock (news intensity) as an alternative explanatory variable in the basic equation of GARCH model. We will show that the GARCH(1,1) model augmented with volume does remove GARCH and ARCH effects for the most of the companies, while the GARCH(1,1) model augmented with news intensity has difficulties in removing the impact of log return on volatility.
References listed on IDEAS
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