Research On The Risk Measurement Of China Securities 100 Index Based On VaR Model

Since the middle and late 20th century,the global financial market has grown rapidly and the financial environment has become more and more complex.With the intensification of interest rate and exchange rate fluctuations,financial market fluctuations are also increasing,financial liberalization and globalization are developing rapidly,and financial industry regulations are becoming more and more relaxed.The management of financial risks has become a major concern of financial institutions.Experts and scholars are also making risk measurements.The field has conducted in-depth research.However,with the increasing complexity of asset structures,the defects of traditional risk management methods have become more and more obvious.This has led to the emergence of a widely used method that can visually measure financial risks,namely the VaR method.The VaR method uses statistical techniques.Compared with other traditional risk management methods,the VaR method can more accurately reflect financial risk status and make risk management more scientific.It is widely used at present.This article first introduces various methods for measuring risks in the world,and summarizes financial risk theory and VaR theory,which lays a theoretical foundation for subsequent empirical research,and then applies three models.The first model is the traditional variance-Covariance model,which is based on the assumption that the data obeys the normal distribution,taking into account the characteristics of the actual financial data such as the peak-height asymmetry,and adopts an improved VAR model that incorporates the extreme value theory and GARCH theory to calculate the risk.The VaR model of GARCH theory can estimate the volatility,while the VaR model based on extremum theory can consider extreme events,and then obtain the calculated VaR values of the two models respectively.Finally,the effectiveness of the three models is achieved.Test to get the best risk measurement model.Based on this theory,this paper selects 1458 data from the closing price point of the CSI 100 index from 2012 to 2017 as a sample for empirical analysis.The main reason for choosing the CSI 100 index is that it can represent the Shanghai and Shenzhen stock markets.The volatility of large-scale stocks is of practical significance,and then the logarithmic returns of the closing price points are calculated.First-order differentials are easier to observe and more in line with the characteristics of financial time series.The significance of economics is significant.Then models are created and models are calculated.VaR estimates,finally through the validity test of the model to analyze the VaR estimates calculated by the three models,compare and study,select a more effective risk model,so that the CSI 100 index risk more accurate measurement.