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Growth Enterprise Market Risk Measurement Models And Empirical Study

Posted on:2011-08-03Degree:MasterType:Thesis
Country:ChinaCandidate:X XiangFull Text:PDF
GTID:2189360308481039Subject:Finance
Abstract/Summary:PDF Full Text Request
Growth enterprise market, as known as GEM, is an integral part of the capital markets, whose development level directly related to the prosperity of capital markets. However, the market risk on GEM can not be ignored.How to identify, avoid and manage the market risk on GEM effectively is extremely important. First of all, it is an inevitable problem that both individual and institutional investors have to consider about. Secondly, the regulators must always pay closely attention to the market risk on GEM in order to propose effective measures and amendments to the newly framed regulatory programs. Last but by no means least, the economic sector of the government should also keep an eye on market risks on GEM, according to whose healthy development degree they can have a determining influence about the new economic program and the further opening-up of capital market. Thus, all the investors, supervisory departments and government economic sectors should have a clear understanding of the risk on GEM, basing on the premise that we must measure the risk on GEM correctly.GEM market risk is caused by securities prices changes, which is often referred as volatility, the estimation of volatility is the essences of the market risk measurement. Risk is traditionally measured by the variance of volatility. Using a VaR/CVaR, instead of volatility, measure the market risk on GEM probably will have better results. By calculating CVaR, we will see, CVaR is a more accurate measurement of market risk. In this paper, GARCH type time series model are used in calculating VaR/CVaR. However, the estimation of these models is a tedious process. In order to improve the cumbersome process, the author proposed an improved numerical method to estimate the VaR/CVaR.
Keywords/Search Tags:GEM, Risk measurement, Empirical study, VaR, CVaR, GARCH
PDF Full Text Request
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