The Measurement Of Commercial Bank’s Interrated Risks Based On Copula Function

Before the1980s, the risk management of commercial banks is major in single local-basedmanagement method to manage the financial risk.. Since1990s, with the pace of economic globalizationand financial liberalization accelerating, the risk management of commercial banks faced tow real scenarios:one is that the financial industry is developing towards the trend of conglomeration and internationalization,and the other is that the use of information technology is becoming more and more widely. As the newBasel Capital Accord, commercial bank risk management mode also changed, from the previous singlecredit risk management mode into credit risk, market risk, operational risk of three kinds of risk and theoverall risk management mode, and also points out that there are some correlation between risks.Sincethere is a correlation between the various risks, the banks in risk management to develop a more perfectstrategy.On the other hand, The mixed management is the development trend of all financial industry thiscentury. In this background, the banking industry is in the mixed operation performance is the mostprominent one industry. Mixed risk due to a combination of different business capital of the single riskmanagement mode can not cope with it, and so will all kinds of risk integration management is attractingmore and more researchers and risk regulators attention. Therefore, the integration of risk management hasbecome one of the most prominent contemporary development trend of risk management of commercialbank.This paper first makes a general analysis of the three kinds of risks that commercial banks face,respectively introduced their respective financial meaning, characteristics and summarizes the commonmeasure method in practice. Then introduced the VaR related content, CVaR, Copula functions and thebasic steps of Monte Carlo simulation. In the past a very long period of time, most researchers and riskregulators are using the simple sum of different risk values, to estimate the overall risk, but this method isgreatly overestimated the integration of value at risk. The integration of risk measurement model of Copulafunction can more accurately describe the dependence structure between different marginal distributionbased on risk, so the risk measurement model to measure the risk of the individual is no longer, but theoverall consideration of the three main risks that financial institutions face. The integration measure of commercial banks face three kinds of risk using the Copula function and CVaR method. At the same timerespectively by Normal copula and t-copula functions to describe the dependence structure between threekinds of risk, and construct the joint distribution function of them, and finally through the Monte Carlosimulation to estimate the CVaR integration risk dependence structure of different value. This model cancalculate the Commercial Bank of the three major risk facing the integration of CVaR and VaR values, so asto compare the quality of the two, at the same time, this paper also studies the influence weight of differentcombinations of CVaR values...