A Risk Analysis Of A+H Banking Shares Based On GARCH Models

Under the global financial crisis, how to effectively manage market risk has become a huge challenge for financial institutions. Therefore, for China's financial market stability and financial institution's healthy development, the study of market risk management technology, which is the most basic aspects of risk measurement, is of research significance.In recent years, research on China's stock market based on GARCH model is a relatively new idea and method. In this paper, some references are provided in help of future research on China's stock market.This paper selected three most representative banks of which both A shares and H shares have gone to the market at a earlier time:One is China Merchants Bank (600036.SH & 3968.HK) which issued A shares before H shares; another is Bank of China (601988.SH & 3988.HK) which issued H shares before A shares, a third is Industrial and Commercial Bank of China (601389.SH & 1389.HK) which issued A shares and H share at the same time. By using the methods in Time Series we set up corresponding ARMA models, GARCH models or EGARCH models for the log return series of the A shares and H shares separately, and conditional variance and variance are used to describe the average risk degree of each stock. From the result we can conclude that, for National A+H listed Banks, the risk level of H shares is a little higher than that of A shares, and rising trend of H shares is more significant than that of A shares.This article is divided into six sections as follows:preamble introduces the research background, research status, and the ideas, structure, methods and technical route of the paper as a whole. The first chapter describes the overview A+H shares, including the definition, production, development, impact on stock market, and situation of listed companies with A+H Shares in China. In the second chapter, the theory of time series analysis is introduced, including the basic concepts, general autoregressive models and conditional heteroscedasticity models. The third chapter is for the model establishment, and three most representative banks are selected, that is China Merchants Bank (600036.SH & 3968.HK), Bank of China (601988.SH & 3988.HK), and Industrial and Commercial Bank of China (601389.SH & 1389.HK), and corresponding ARMA models, GARCH models or EGARCH models for the log return series of the A shares and H shares are set up separately. Chapter IV describes the average risk degree of each stock based on conditional variance analysis. The fifth chapter is the conclusion.This paper uses qualitative and quantitative, normative analysis and empirical analysis, theoretical and practical combined research methods, using econometric methods (such as time series, autoregressive, conditional variance, etc.), and software EVIEWS to program and compute.This article systematically summarizes the financial risk measurement techniques, especially the GARCH models. The innovations of the paper is to apply the GARCH models to the listed commercial banks with A+H shares, some references are provided in help of the operation of future listed banks both at Hong Kong and mainland stock market. The deficiency in the model building process is that the data collected is incomplete, and the program is complex to run and so on. In addition, ARIMA model and IGARCH (ARCH/GARCH) model in fitting curves and predicting value of one step forward exist first order lag. Therefore, the application of mathematical models should be further improved.