The Optimization Management Model Of Interest Rste Risk Based On Gap Management And Its Application

With the promotion of interest rate market-oriented reform in China, interest rate fluctuation and its risk faced by commercial bank are increasingly frequent. It gains wide attention in the industry to control and measure interest rate risk, as well as how to reduce it. Owing to long-existing policy of interest rate regulation in our country, commercial banks generally lack interest rate management experience on pricing, risk measurement and monitoring system. So in the process of promoting interest rate marketization in our country, it is a very important part for current commercial banks to distinguish, measure and control interest rate risk caused by interest rate market environment change. In recent years, the central bank abandoning the control over interest rate not only illustrates that commercial banks have strengthened initiative for regulating interest rate, but also increases interest rate risk caused by interest rate fluctuation. However, interest rate control is on basis of interest rate measurement. Although there have some common measurements like interest rate sensitivity gap, duration analysis and Value at Risk (VaR), these are interest rate risk control imposed on commercial banks by themselves. What’s more, these static measurements are not continuously dynamic control, so there is to some extent limitation using them.Based on interest rate volatility clustering, this paper will evaluate VaR applying to ARCH---GARCH(1,1) model. And then, combing with net asset value of six listed banks, it will get a good explanation for maximum loss which six listed banks afford to lose everyday. This paper, under the prediction of interest rate, will also solve optimal net asset value taking advantage of the relationship between maximum loss and optimal net asset. It will try to apply optimal control theory to interest rate risk control based on above model. By empirical test on six listed banks, all of methods and empirical results have theoretical and practical significance for back supervision department and investors.This paper has the result that after optimal adjustment on asset and liability in the first three quarters of this year 2015 based on optimal control model.the optimal control of six listed banks from the first quarter to the fourth quarterl are gradually increasing trend in our optimal control, and the fourth quarter is down to adjust back to our best level of control, namely the fourth quarter of optimal asset is equal to the same amount of control over the assets,and at last the article analyzes the amount of changes between the actual value of assets in the first and second quarters of 2015 and our predicted values. Although there is a certain difference between the two values, but the paper also analyzes a series of reasons for the difference, and the difference is within a certain range of fluctuation. Empirical Analysis of this series is a good description of the effectiveness of our optimal control model in the practical application.From six listed banks, it indicates that founded optimal control model, based on gap-filling interest rate risk, and optimal control variation are effective and stable. Based on the actual situation, this paper has given some practical suggestions for improving commercial banks external environment and regulating theirs interest rate risk.The innovation of this paper:firstly, in view of interest rate volatility clustering, it chooses GARCH model describing volatility degree to evaluate VaR, making a good relationship between GARCH model and dynamic optimal control model. Secondly,this paper not only predicts the optimal amount of change in net assets for each quarter in 2015 but also compares with the actual amount of change in net assets.It is better to verify the feasibility of the proposed model. It has evaluated overnight call interest rate future value and considered fully that interest-rate spread can not exceed VaR. Thirdly, it span a longer period of time and has an important practical significance.The deficiency of this paper:Firstly, the ideal net asset is constant, while in reality it will be fluctuant caused by fluctuant macro-economy. This aspect should be further studied. Secondly, the optimal asset rate is also constant got by the relationship between liability and time point, using EViews7.2 least square method, while it will be changeable because of economic fluctuation.