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Interest Rate Liberalization And Interest Rate Risk Measurement And Management Of Commercial Banks

Posted on:2012-09-30Degree:DoctorType:Dissertation
Country:ChinaCandidate:H B LiFull Text:PDF
GTID:1109330467968340Subject:Finance
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The outbreak of American Financial Crisis at2008year attracted much more attention on identification, accurately measurement and control of commercial banks’ interest rate risk (IRR). Under the circumstance of accelerative interest rate liberalization, however, Chinese commercial banks’ asset and liability scale sharp expands from2009year. With world economy recovering and increasing inflation pressure, china enters into interest rate raise cycle. Then, commercial banks pursuing steady operation will suffer huge adverse shock and IRR becomes substantial risk. Therefore, the research on IRR’s measurement tends to be an inevitable topic in Chinese commercial bank’s IRR management practice. The thesis’s key contents and main conclusions are as follows:The thesis compared and analyzed possibility of Chinese main interest rate as potential benchmark interest rate from2006.10~2011.5. The empirical result of representative term shows that SHIBORO/N, REPO7D, YP3M and DR1Y are most representative. The empirical result of benchmark interest rate choice indicates that SHIBOR O/N functions as benchmark interest rate in Chinese short-term interest rate system, but the basis status should be further strengthened. Subsequently, the thesis applied GMM method to estimate and forecast SHIBORO/N based on CKLS nested model framework during2008.10~2010.12,2007.10~2010.12,2006.10~2010.12. The outcome suggests that CKLS nested model has partial forecast function, but has weak performance in forecasting extreme value and volatility.The thesis choose Bank of China, China Construction Bank, Industrial and Commercial Bank of China, Agricultural Bank of China, Bank of Communications’ interest rate sensitive gap data at2010year as samples, employing standard shock method and VaR simulation method to measure IRR in Banking Book of Commercial Banks. The simulation results of standard shock show that:firstly, if not remove demand deposits and legal deposit reserve out of re-pricing gaps, simulation results of net interest income (NII)’s IRR are not consistent with reality. After deduction, all commercial banks’ NII are subject to interest rate falling risk. At the meantime, VaR simulation results of interest rate dynamic shock are approximately equal to60~80basis standard shock, because the2010year’s yield curve located comparative bottom in recent years. In addition, the ranks of sample banks’ declines in NII margins are very consistent under standard shock method and VaR simulation method. Secondly, after removing demand deposits and legal deposit reserve out of re-pricing gaps, Bank of China’s IRR of economy value of equity (EVE) declines litter than not removing. After applying two simulation methods, the sample banks’ EVE face interest increasing risk. At the same time, the ranks of sample banks’ declines in EVE margins are unanimous. Because Bank of China’s3month to1year re-pricing gap shared high percent in total1year re-pricing gaps, its EVE’s IRR are highest among five sample banks.The thesis choose SHIBORO/N and7day inter bank’s impawn REPO’s data during2010.1.4~2011.1.17as sample, applying delta norm method and Monte Carlo simulation method to measure single IRR and integrate IRR of interbank market’s dealing separately. The results are as follows:firstly, according to the VaR calculated by delta norm method, state-owned commercial banks’ VaR and its volatility are least; stock commercial banks’ VaR is largest due to big asset and liability scale; foreign-invested commercial banks’ VaR is second largest but its volatility is little due to advanced IRR management level; rural commercial banks’ VaR is second least but has high volatility, due to seasonal character of rural economy and "long term asset but short term liability" feature. Secondly, the VaR calculated by Monte Carlo simulation method is quite different from the VaR calculated by delta norm method. Applying the sample data during2011.1.18~2011.5.31to implement back-test, the results shows that the VaR model using Monte Carlo simulation method passed back-test and has more power than the VaR model using delta norm method. Thirdly, the thesis builds the VaR calculation model of interest rate future and interest rate swaps in off-balance sheet activities.Based on above research result and analysis, the thesis put forward some suggestions on commercial banks’ IRR management as follows:firstly, banking book’s IRR management should make balance between pursing EVE target and NII target, improve IRR quota management and promote IRR centralized management. Secondly, tradable accounts’ IRR management should try to build VaR measurement and control IRR’s vertical management pattern, consummate IRR management’s information system, develop internal VaR model accordance with reality, utilize VaR model to improve IRR internal control and strengthen IRR’s supervision.
Keywords/Search Tags:Interest Rate Liberalization, Commercial Banks, Measurement and Management of Interest Rate Risk, Interest Rate Risk in Banking Book, Interest Rate Risk in Banking Tradable Accouts
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