UserName:
PassWord:
Home >> Working Paper
Empirical Analysis of Future Market Volatility based on the Markov Switching GARCH Models
Read        DownLoad
TitleEmpirical Analysis of Future Market Volatility based on the Markov Switching GARCH Models  
AuthorZhaoJinwen and Fang Hao  
OrganizationSchool of Finance, Dongbei University of Finance and Economics 
Email 
Key WordsCopper Futures; Market Volatility; GARCH-Class; Markov State Transition Model; Probability Smooth 
AbstractAs the global economic integration and our futures markets, the rapid rise of the international financial market risk conduction and contagion is more efficient, on the domestic economy and social development impact of increasingly clear. Accurate analysis of the futures price volatility characteristics is the basis to identify the market risks and promote the healthy operation of futures market. In this paper, we introduced the state variables to establish the Markov state transition GARCH model (MS-GARCH model) based on the GARCH–type model analyzing the commodities futures market volatility characteristics for the copper futures varieties as an example. The results show that, China's copper futures yield sequence has obvious GARCH effect, but no significant leverage effect. Further, it can be divided into market volatility high and low for two kinds of state, different state of the coefficient estimation results obvious difference. Relative to the low volatility state, the state of the high volatility average duration is short, the impact of persistent were also lower. From fitting effect to see, MS-GARCH model is superior to the traditional GARCH model, better able to describe copper futures price volatility characteristics. 
Serial NumberWP175 
Time2012-02-14 
  • Institute of Economics, Chinese Academy of Social Sciences
  • Copyright Economic Research Journal
  • The uploaded articles by this website express the authors’ views, not necessarily the views of this website.
  • Perennial Legal Counsel: Lu Kang (Chong Guang Law Office)
  • ISSN 0577-9154 CN 11-1081/F Postal Distribution Code 2-25l (Domestic) M16 (Overseas)
  • ICP 10211437 (Beijng)
  • No.2,Yuetan Bei Xiaojie, Xicheng District, Beijing 100836, P. R. China
  • Phone/Fax: (+8610) 68034153