Volatility Analysis of Web News and Public Attitude by GARCH Model

Pinrui Yu, Tianzhen Liu, Qian Ding

School of Journalism and Communication, Southwest University, Chongqing, China.
School of Urban Design, Wuhan University, Wuhan, China.

DOI: 10.4236/psych.2012.38092                

Abstract

GARCH (Generalized Auto-Regressive Conditional Heteroskedasticity) model proposed by Professor Engle is successful to analyze the volatility of stock price. In this paper GARCH model is used to analyze the volatility of web news events and public attitudes by the data coming from typical news events in famous web. The results show that the volatility of web news events and public attitudes are suitable to GARCH model by some adjusting and test of parameters.

Keywords

Web News; Public Attitude; Volatility Analysis; GARCH Model

Conflicts of Interest

The authors declare no conflicts of interest.

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