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The EGARCH Effect Test of Chinese Stock Market from the Perspective of Behavioral Finance

  • Wenting CaoEmail author
  • Jiangyue Luo
  • Xiaojuan Wu
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 885)

Abstract

Financial time series often tend to show obvious volatility clustering. Selecting the daily closing data of the Shanghai Composite Index from January 2008 to April 2018, we first test the ARCH effect, and then establish the EGARCH model adding asymmetric item to the conditional variance equation. Our findings indicate that in the past decade the fluctuation of China’s stock price has performed a long-lasting clustering phenomenon. At the same time, “bad news” causes the fluctuation of stock price to be greater than that of “good news”. The reason is that Chinese stock market is characterized by a large number of retail investors, and the investment income mainly comes from the bid-offer gaps of stock prices. Investors’ philosophy is over-speculative, short-term and herding. We combine the Prospect Theory of behavioral finance and find that Certainty Effect and Loss Aversion can well explain the empirical results of the EGARCH model.

Keywords

Behavioral finance Prospect theory BAPM EGARCH 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.School of EconomicsSichuan UniversityChengduChina
  2. 2.School of Economics and ManagementYunnan Normal UniversityKunmingChina
  3. 3.Collaborative Innovation Center for Security and Development of Western Frontier ChinaSichuan UniversityChengduChina
  4. 4.School of BusinessSichuan UniversityChengduChina

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