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The Risk Measurement of Interbank Loan Interest Rate

Author: ChengHang
Tutor: ShiYongDong
School: Dongbei University of Finance
Course: Finance
Keywords: Interbank Offered Interest rate risk Correlation t-copla-GARCH
CLC: F832.33
Type: Master's thesis
Year: 2013
Downloads: 6
Quote: 0
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Abstract


To establish a sound financial system, commercial banks play a major role in indirect financing. Among China’s reform and opening up, we have get lots of successful experience from abroad. So we began to cultivate and develop our inter-bank lending market. With the continuous exploration and reform, SHIBOR market is building and the interbank market continues to improve, China’s interest rate market to build initial results. Now SHIBOR has become China’s most important benchmark money market interest rates. Various debt products based on pricing, and its financial innovation active. More short-term fluctuations reflect current market capital supply and demand, the long-term interest rates are expected to reflectingfluctuate. SHIBOR market trading volume is expanding, the impact has also been strengthened. However, with the interest rate market progresses, mean release rate control, allowing commercial banks to become competitive enterprises, lending market but it is also commercial banks and other financial institutions, short-term financing of the main channel. Continue to promote the marketization of its processes and increasing trading volume, making the commercial banks face increased risk of lending rate. How to effectively and accurately measure the commercial banks lending rates as commercial banks need to solve the problem.Commercial banks in the lending business, due to business needs and their own funds in different positions, often require different terms and different interest rates, trading volumes and different lending in different directions, so complex form of trading makes the lending risk measure becomes complicated. The traditional methods often can not be measured accurately grasp the overall risk faced. Simple gap model, maturity gap model and duration gap model analysis of variance and volatility of various defects exist. The VaR methodology is a very good quantitative indicators of measuring financial risk, with practicality and comparability in the field of financial risk measure has become the mainstream method. However, due to its accuracy in how to simulate the real future of the probability distribution of the portfolio on the issue did not come up with effective solutions, especially in complex structural problems related treatment. So how can we effectively measure of commercial banks in the interbank market, interest rate risk on the need to find more effective ways of measurement.This article with copula function model is applied to commercial bank lending interest rate risk measurement. Compared with traditional methods, copula function model of the advantage of being able to more accurately portray different correlations between asset portfolio, so as to solve how to accurately simulate the real probability distribution of the portfolio problem, for the VaR measurement methods had a very good remedy. First select SHIBOR market transactions account for the vast majority of the overnight interest rate as a measure goals and seven fat tail phenomenon exists, and there is conditional heteroscedasticity, GARCH process are met. By comparing the GARCH (1,1), t-GARCH (1,1) process and found that GARCH (1,1) are better able to simulate the time series of marginal distributions.After considering the correlation between the linkage, because of its tail associated with symmetry, under normal circumstances, bivariate normal copula function and binary t-copula function related to the symmetry of the situation with a tail can be a good description. Then through the squared Euclidean distance method to select a smaller squared Euclidean distance to compare two copula function, found two Dimensions t-copula function has a smaller squared Euclidean distance, better correlation between constitutive description of the structure. Using non-parametric kernel estimation method to estimate the correlation fit function parameters, constructed based on t-copula-GARCH correlation structure model.Constructed using the copula-GARCH model the joint distribution, to better fit the marginal distribution of the joint probability distribution of the whole building, followed by the use of Monte Carlo simulation method SHIBOR commercial banks held50%of the market overnight and seven positions VaR, then the traditional variance-covariance method to calculate VaR. By tracing test to compare the LR statistic found, copula function method is more able to accurately measure commercial bank lending interest rate risk. Commercial banks should improve their risk measurement methods, and constantly improve their own business model, fundamentally eliminate sources of risk.The innovation of this paper lies in the copula function model was applied to commercial bank lending rates measure of risk, constructed based on the correlation structure of copula-GARCH model. In the model building were used different approaches and copula function selection parameter estimation method, the final model was also based on quantitative calculation of VaR, the VaR back test through comparative analysis of the pros and cons of different models.But in the copula function to build the model, there are still many deficiencies. Yields marginal distribution model can be used to build more accurate mathematical model approach. In the interest rate market backdrop, the term structure SHIBOR other transactions will continue to increase interest rates on the interbank market risk measurement model needs to be improved, using a wide range of copula function model. Select a copula function in the form of sometimes not able to quantify the metrics from specific instructions on selecting the advantages of these two functions. And the form of a single parameter copula function is not able to describe the ever-changing interest rate risk related structures, time-varying and mixed copula function approach should be more suitable.

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CLC: > Economic > Fiscal, monetary > Finance, banking > China's financial,banking > Financial organizations, banks > Commercial banks ( specialized banks )
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