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The Comparison Study of Parameters Estimation of ARSV Model

Author: LiuYouJun
Tutor: ZhangTong
School: Tianjin University
Course: Technology Economics and Management
Keywords: Random fluctuations Markov chain Monte Carlo GMM Estimator Efficient Method of Moments Parameter estimation
CLC: F830.9
Type: Master's thesis
Year: 2007
Downloads: 337
Quote: 1
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Abstract


Financial market risk has been an issue of concern . This risk is mainly due to fluctuations in the prices of financial assets caused . Therefore, estimates and projections of the price volatility has become the core issue of risk measurement , to become the focus of research scholars from various countries . Markowitz first introduced mathematical concepts to the fluctuations in the study to measure fluctuations in the sample variance . After him , the scholars from various countries have put forward some of the estimated volatility model , but these models assume that fluctuations do not change over time . With the deeper understanding , people gradually find that volatility does not change over time , it is not reasonable to assume that . Since autoregressive conditional heteroskedasticity model and stochastic volatility models proposed in the eighties of the last century , began varying fluctuations in the field of quantitative modeling . Stochastic volatility model as an important model for the quantitative study of the financial market volatility , parameter estimation problem is the hot areas of research in the recent ten years . This article focuses on the generalized method of moments estimation method , three each with distinct characteristics of the Markov chain Monte Carlo methods and the effective moment estimation method stochastic volatility model parameter estimation method . GMM estimation method is the first one of the estimation methods for SV models , the most important feature of this method is simple ; Markov chain Monte Carlo methods Over the past decade the rise of a numerical method its characteristics of the statistical properties of the estimated amount of good and famous ; effective moment estimation method is a new parameter estimation method , its unique and innovative ideas in the large sample statistics and Markov chain Monte Carlo method is quite . The paper begins with a brief analysis of the stochastic volatility model and model parameter estimation method . GMM estimation method and then focus on the three parameter estimation methods theory of Markov chain Monte Carlo methods and effective moment estimation method and its specific application in the stochastic volatility model and data on each parameter of China 's stock market the estimated empirical research . Finally, we compare the effect of three parameter estimation methods in the empirical study of China's stock market .

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CLC: > Economic > Fiscal, monetary > Finance, banking > Finance, banking theory > Financial market
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