The Application Of Copula Function In Financial Market Risk Management

Under the floating-exchange-rate system, exchange rate fluctuates much more frequently than that under the fixed-exchange-rate system, thus leading to government’s frequent use of interest-rate-tools to intervene in the economy under the guidance of Keynesian economic theory. Also, such frequent fluctuation of exchange-rate makes companies and individuals face more risks, which require civil subjects to increase risk management consciousness, and employ more risk management tools to improve risk management level.In the risk management practice, we mainly and traditionally use three types of risk management methods, which are elastic method, volatility method and risk value method. However, the hypotheses of those traditional three methods unusually are difficult to be satisfied. So those traditional methods not only underestimate the magnitude of risks, but also underestimate the probability of risks.So, generally we employ other assumptions on the asset yields and the marginal distributions of risk factor, and also we always employ the copula-function, instead of linear correlation, to describe the return on assets or market risk factor related structures.In the improvements in related structure, the copula function has many advantages, such as not limiting the marginal distribution of return on assets and market risk factors, reducing the difficult of modeling by Step-by-step estimates, and describing the nonlinear-asymmetric-related structure, and providing more relevant information. Especially, we can focus mainly on the tail-correlation by selecting different types of copula faction, and such is crux to risk management.Based on those fundamental acknowledge, this paper employ MATLAB and EVIEWS to calculate and simulate the portfolio VaR of the Shanghai index and Shenzhen index.This paper is consists of five chapters. The first chapter introduces the multiple-choice background, the literature review, and the significance of research. The second chapter firstly reviews the traditional methods of financial risk management and its shortcomings, and then summarizes several methods of calculating risk value and how to conduct the post-hoc-tests of risk value. In the third chapter, we mainly introduce the definition, types and rank correlation of copula function. In the forth part, we show the marginal distribution and features of financial time series modeling, introduce how to use FARCH model to estimate the risk value, and summarize the conversion process of GARCH-model to distribution.Finally, in the fifth chapter, we employ the Shanghai index and Shenzhen index to estimate the marginal distribution of return-rate, employ different copula function to describe the relating-structure of Shanghai index and Shenzhen index. Then we estimate the risk value of assets portfolio, and get the conclusion that we can better describe the portfolio risk by employing proper copula function.