Forecasting Interval Valued Stock Returns Based on News Media Sentiments
Since the investor sentiment is closely related to the price movement of Chinese stock market,it is crucial to correctly understand the investor sentiment for both financial investors and regulators for risk management.This paper aims to construct a fan-weighted news sentiment index based on the State Council news texts and financial sentiments dictionary,and then to investigate the predictability of the fan-weighted news sentiment indicator on the main board market and sub-markets of Chinese stock market by an interval-valued autoregressive model.The empirical results show that:1)Our proposed fan-weighted news sentiment index can not only reflect news sentiment effectively,but also has a significant negative impact on Chinese stock market;2)Compared with the simple average news sentiment index,our proposed fan-weighted news sentiment index can significantly improve the predictive ability on Chinese stock market under both the main board market and sub-markets,which provides a new idea for constructing sentiment indicators;3)The predictive ability of news sentiment index gradually decreases over time for the main board market,but it is heterogeneous for the sub-markets.These empirical findings show that the investor sentiment mined from news text is important to predict the stock market performance.
stock prices forecastingtext miningemotional analysisinterval-valued data
NETL
NSTL
万方数据
