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A Note on Conditional Variance and Decaying Rate: Chinese Equity Market

Amanjot Singh ()
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Amanjot Singh: Punjabi University

Journal of Quantitative Economics, 2018, vol. 16, issue 2, 595-611

Abstract: Abstract Conventional GARCH based models capture short run dependence structures in financial markets or shocks decaying at a faster exponential rate. However, the present study attempts to model long run dependence or memory in Chinese stock market volatility process by employing autoregressive (p)—fractionally integrated generalized autoregressive conditional heteroskedasticity model, i.e. AR (p)—FIGARCH model; following Bollerslev and Mikkelsen (J Econ 73(1):151–184, 1996) with a shift variable. Apart from FIGARCH (1, d, 1) model, conventional GARCH (p, 0, q) and Integrated GARCH (p, 1, q) based models are also employed in order to ensure comparability across integrated processes. The empirical findings advocate long run dependence structure in volatility process of Chinese equity market, whereby a shock to the future volatility decays at a slower hyperbolic rate. However, the integrated decaying parameter relates more to conventional GARCH (p, 0, q) model after considering structural breaks and foreign exchange rate movements, whereby exponential decaying rate is expected in the equity market. The findings bear strong implications for different market participants in their attempt to comprehend volatility component of the equity market.

Keywords: China; Fractional integration; GARCH; US; Volatility (search for similar items in EconPapers)
Date: 2018
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