Measurement Of Interest Rate Risk In The Banking Book Of Commercial Banks

From 2007 to 2008, the outbreak of the sub-prime mortgage crisis, not only lead to economic recession in the United States, but also threaten the economic security of other countries and regions. How to reform the financial regulatory framework and improve the financial supervision is recently a hot topic among governments and the financial supervisory authorities. Interest rate risk (IIR) is a major risk in the banking sector. If inflation comes, interest rates will increase substantially, the banking sector will suffer a huge adverse impact. Savings and Loan Associations Crisis in the United States from 1980s to 1990s is a typical case. In recent years, as China's commercial banks continue to expand the size of assets and liabilities, and the reform of the market-oriented interest rate gradually make progress, interest rate risk in the banking book has become the substantial risk.Interest rates are important variables in the economic theory. John M. Keynes and Franco Modigliani have made tremendous contributions to the theory of the term structure of interest rates. In view of the importance of bank risk management on national economic security, interest rate risk of the commercial banks has become one of the topics of concern in the economics and finance in last two decades. Basel Committee on Banking Supervision in July 2004 promulgated the "Principles for the Management and Supervision of Interest Rate Risk", in order to guide the management of interest rate risk in the banking book of the commercial banks. China Banking Regulatory Commission on December 25,2009 also promulgated the "Guidelines for the Management of Interest Rate Risk in the Banking Book of Commercial Banks", requesting the commercial banks to establish the framework of interest rate risk management in the banking book. The issue and implementation of these documents will further promote the study of interest rate risk management of the commercial banks.The dissertation is studying the measurement of interest rate risk in the banking book based on the specific situation of China's commercial banks, and the the relationship between the structure of asset-liability and interest rate risk exposure exposure to banks'net interest income (NII) and economic value of equity (EVE). Comparative analysis and scenario simulations are the two major methodologies. Because banks'interest rate risk includes net interest income risk and economic value risk, and a variety of measurement techniques and different sample data are applied, comparative analysis will be an effective method to find out which measurement techniques are more applicable, and how the interest rate changes influence net interest income and economic value in different way. Scenarios simulations based on the specific models will help measure the banks' potential loss in the worst-case. Based on the logic of finding problems through empirical studies and analyzing problems through theoretical models, the study has three steps:the estimation of the yield curve dynamics and the test of the predictability of the models; Measurement, comparison, validation of the banks' exposure to interest rate risk in terms of the different yield curve dynamics models; Establishment of an analytical framework model to further reveal the relationship between the structure of asset-liability and interest rate risk.The main contents of the dissertation are as follows:Firstly, the short-term interest rate models are empirically estimated using China's yield curve dynamics. The first step, the different single-factor short-term interest rate models are estimated time-seriously under the CKLS nested model framework. The second step, Vasicek model and CIR model are further calibrated cross-sectionally with the actual yield curve on specific dates, but retain some of the information from the time-series estimates. The third step, the models after calibration are tested with out-of-sample data. The results showed that:the models fit well, and the parameters obtained from calibration are also relatively stable. However, the longer is forecasted, the greater the prediction error. Thus, even the models fit well with in-sample data, it is also necessary to recalibrate the models with the passage of time.Secondly, China's yield curve dynamics are estimated using Principal Component Analyses (PCA). The first step, the daily yield curve changes are estimated using PCA. The second step, the PCA series distribution is estimated with kernel density estimation. The third step, the envelope abilities of the estimated PCA models are tested using out-of-sample data. The results showed that: There exists a huge difference among the PCA coefficients estimated with the sample of the different periods. The changes in PCA series showed significantly the distribution of heavy-tailed characteristics. Therefore, the normal distribution assumption may underestimate the interest rate risk. The scope of the prediction using non-parametric PCA models, to better reflect the extreme scenarios of interest rate risk, can overall envelop the scope of the prediction using normality assumption models.Thirdly, a study of the measurement of the interest rate risk exposure to banks'net interest income (NII). Changes in banks'net interest income to interest rate fluctuation in one year are only short-term effects. The first step, compute the potential decline in net interest income following Basel standardized interest rate shock, using China's five commercial banks're-pricing gap data in the end of 2007. The second step, compute the potential decline in net interest income through the simulation using Vasicek model and CIR model. The third step, rank five banks in terms of their interest rate risk exposure to net interest income. The results show that:If don not remove demand deposits and legal deposit reserve out of the re-pricing gaps, whose interest rate doesn't adjust often and adjustment is very small, simulation results are very different from the actual situation. After deduction, all banks'net interest income is subject to the risk of the fall in interest rates. Also found that, the net interest income risk predicted by Vasicek model and CIR model is less than that by standardized interest rate shock approach, because yield curve remains very low at the end of 2007. Ranked five banks in terms of the declines in net interest margin (NIM), and found the ranking results with different models are very consistent.Fourthly, a study of the measurement of the interest rate risk exposure to banks'economic value of equity (EVE). Changes in economic value may stand for the potential long-term impact of interest rate shock to banks, to which bank managers and banking supervisory authorities should pay more attention. The first step, compute the potential decline in economic value following Basel standard duration approach. The second step, compute the potential decline in economic value through the simulation using Vasicek model and CIR model, as well as the PCA model and the historical simulation method. The third step, rank five banks in terms of their interest rate risk exposure to economic value. The results showed that:All five banks'economic value is subject to the risk of the rise in interest rates. The economic value risk predicted by Vasicek model and CIR model, using 2-year or 3-year historical data sample, is less than that by standard duration approach. The studies of the principal component VaR and historical simulation VaR showed that economic value risk predicted by non-normal simulation to be greater than by normal simulation, reflecting the heavy-tailed distribution of PCA series. The economic value risk predicted by standard duration approach is between results predicted by non-normal principal component 1-year holding period VaR using 2-year and 3-year historical data sample. Ranked five banks in terms of the economic value risk, and found the ranking results predicted by historical simulation, normal and non-normal VaR models, as well as standard duration approach, are very consistent. But the ranking results predicted by Vasicek model and CIR model are very different.Finally, a study of the consistency of the objectives of interest rate risk management. The first step, establish a framework model to analyze the relationship between re-pricing gap structure of bank's assets and liabilities, and interest rate risk exposure to net interest income and economic value. The second step, further explore the policy implications of the framework model. The results show that:For the typical situation of China's commercial banks, when interest rate fluctuates, the changes in the direction of short-term net interest income and economic value are inconsistent; the effect of asset-liability management strategy is also inconsistent. In this case, the purposes of supervisory authorities and bank managers prone to departure, and then increase the difficult in banking supervision.The innovations of the dissertation are as follows:Studying integratedly the interest rate risk exposure to banks'net interest income and economic value. When the interest rate changes, it is very important for bank managers and banking supervisory authorities whether the changes in the direction of net interest income and economic value are consistent. Studying the impact of net interest income and economic value simultaneously will be helpful for bank managers'integrated management of interest rate risk, and for banking supervisory authorities'effective supervision programs. It's helpful to manage the interest rate risk exposure to banks'economic value through marking to market, after introducing the principal component VaR method. It's helpful to manage the interest rate risk exposure to banks'economic value through day to day marking to market, using principal component normal or non-normal simulation VaR with back-testing.An analytical framework model is established to reveal the relationship between the structure of asset-liability and interest rate risk. Only one variable, the ratio of one-year cumulative gaps to total cumulative gaps, could effectively stand for different gaps structure of assets and liabilities. This model could intuitively reveal the relationship between the structure of banks'asset-liability and interest rate risk.In conclusion, the interest rate risk exposure to commercial banks'banking book has a diversity of sources and multiple impacts. The measurement of the risk is also very hard. As knowledge and time constraints, there are some limitations. A lot of work should be done in the future study.