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Based on state transition asymmetric PGARCH class model of China's stock market volatility

Author: ChenXian
Tutor: DongJingRong
School: Chongqing Normal University
Course: System theory
Keywords: Stock market Volatility APGARCH model Markov process The RS-APGARCH model
CLC: F832.51
Type: Master's thesis
Year: 2009
Downloads: 178
Quote: 1
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Abstract

Total financial market is constantly changing, especially China's financial market is still in adjustment and transition, changing the laws of economics, the actual existence of the structural changes in financial volatility of the financial markets. Therefore, volatility modeling using variable structure is essential to financial volatility, variable structure of financial volatility model has become the hotspot Volatility Model. This article as a starting point, trying to elaborate theory variable structure of financial volatility model is better than other financial volatility model to reflect the actual volatility characteristics of China's stock market, and then verify that the variable structure through empirical analysis of financial volatility model to characterize the effect of China's stock market fluctuations. Some major event will have a tremendous impact on the financial markets, and fails to consider the impact of these events on the volatility may not meet the actual situation. In particular, China's stock market is not mature enough, and the impact of major events will lead to intensified market volatility. Therefore, to accurately describe the sexual behavior characteristics of the fluctuations in the stock market is not easy. Volatility of financial markets, the domestic and foreign scholars has done a lot of analysis and quantitative model of the many categories. Time series volatility model can generally be divided into two categories: one is the class model autoregressive conditional heteroskedasticity (ARCH); a class of stochastic volatility (SV) model. The ARCH model because of its good statistical properties and accurate description of wave phenomena, is widely used in the financial sector, commonly used model EGARCH, TGARCH, APGARCH variety. This paper describes a new method to study the volatility - the asymmetric state transition PGARCH (referred to as the RS-APGARCH) model, this variable structure volatility model in introduced in APGARCH model of a two-state Markov switching mechanism the fluctuations of the stock market is divided into two types, one is the stock market is in decline, another is the stock market is rising, a random process to control the conversion between the two systems. The paper will use the the more mature GARCH models a flexible APGARCH model the RS-APGARCH model empirical research on the Chinese stock market volatility and the empirical results comparing these abilities to describe the model of China's stock market volatility. Through theoretical analysis and empirical study of China's Shanghai and Shenzhen stock market volatility, the paper argues that the introduction of economic policy, the changes of the financial regulatory system, the financial markets improve as well as the international financial crisis, the impact of events such as the data structure will produce great impact, making the the conditional volatility variable structure, data modeling, fluctuations in variable structure model to better portray the volatility of the Chinese stock market. Thus, for a large degree of stock market volatility, poor stability characteristics, fluctuations in variable structure model with greater practicality and application of space on the stock market volatility. Favorable to the government to strengthen the policy supervision and guidance, investors risk aversion. At the same time, the government needs to further intensify the construction of the capital market system and operational mechanism, enhance investor education, timely introduction of a market-maker system and short-mechanism, enhance market stability, reduce the huge impact of major events on the stock market, to maintain the capital market stability.

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CLC: > Economic > Fiscal, monetary > Finance, banking > China's financial,banking > Financial market
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