本文選題：操作風(fēng)險(xiǎn)度量 + 損失分布法　； 參考：《南京大學(xué)》2012年碩士論文

【摘要】：在金融系統(tǒng)的改革與波動(dòng)影響下,商業(yè)銀行的經(jīng)營(yíng)業(yè)務(wù)體系也在不斷的變革和發(fā)展,同時(shí)一些能夠?qū)︺y行造成重大威脅的極端突發(fā)事件發(fā)生的幾率增大,銀行業(yè)面臨的操作風(fēng)險(xiǎn)呈現(xiàn)出逐步上升的狀況。在此種內(nèi)外部環(huán)境下,合理度量銀行業(yè)所面臨的操作風(fēng)險(xiǎn)不僅有利于增加銀行的核心競(jìng)爭(zhēng)力,更是銀行提高內(nèi)部控制水平,適應(yīng)外部監(jiān)管要求的必要條件,因此積極開發(fā)適應(yīng)當(dāng)下銀行風(fēng)險(xiǎn)經(jīng)營(yíng)水平的度量方法勢(shì)在必行。本文主要圍繞我國(guó)商業(yè)銀行操作風(fēng)險(xiǎn)度量的問(wèn)題展開研究與討論,整理收集了我國(guó)商業(yè)銀行在1994-2009年之間的254起操作風(fēng)險(xiǎn)損失事件的相關(guān)歷史數(shù)據(jù),并運(yùn)用基于蒙特卡羅模擬的損失分布法與極值理論法對(duì)我國(guó)商業(yè)銀行的操作風(fēng)險(xiǎn)進(jìn)行了度量。 本文介紹了商業(yè)銀行操作風(fēng)險(xiǎn)的定義、分類和特征,分析了我國(guó)商業(yè)銀行操作風(fēng)險(xiǎn)的表現(xiàn)和成因,總結(jié)了目前商業(yè)銀行操作風(fēng)險(xiǎn)的系列度量方法,分析了操作風(fēng)險(xiǎn)中損失分布法與極值理論度量的理論與步驟,并比較分析了這兩種度量方法的特點(diǎn)與應(yīng)用情況。理論追溯之后,運(yùn)用基于蒙特卡羅模擬的損失分布法與極值理論法對(duì)我國(guó)商業(yè)銀行的操作風(fēng)險(xiǎn)進(jìn)行了度量研究。運(yùn)用損失分布法進(jìn)行度量時(shí)發(fā)現(xiàn),我國(guó)商業(yè)銀行操作風(fēng)險(xiǎn)損失事件發(fā)生的概率服從威布爾分布,發(fā)生強(qiáng)度服從對(duì)數(shù)正態(tài)分布；模擬的操作風(fēng)險(xiǎn)損失總金額的平均值為6.2337e+005；標(biāo)準(zhǔn)差為1.9824e+006,99.9%分位值為2.4517e+007,并且在99.9%的置信水平下,VaR值為2451.7億元,若銀行能夠證明自身已對(duì)預(yù)期損失在日常經(jīng)營(yíng)中進(jìn)行了相應(yīng)的防范,則需要準(zhǔn)備的監(jiān)管資本應(yīng)為2389.4億元。運(yùn)用POT模型度量時(shí)發(fā)現(xiàn),在99.9%的置信水平下,我國(guó)商業(yè)銀行操作風(fēng)險(xiǎn)的在險(xiǎn)價(jià)值為1931.1億元。
[Abstract]:Under the influence of the reform and fluctuation of the financial system, the business system of the commercial banks is also constantly changing and developing, and at the same time, the probability of some extreme emergencies which can pose a significant threat to the banks increases.The operational risk faced by the banking industry is gradually rising.In such an internal and external environment, the reasonable measurement of the operational risks faced by the banking industry is not only conducive to increasing the core competitiveness of banks, but also to the necessary conditions for banks to improve the level of internal control and adapt to the requirements of external supervision.Therefore, it is imperative to actively develop measures to adapt to the current risk management level of banks.This paper mainly focuses on the research and discussion of operational risk measurement of commercial banks in China, collates and collects the relevant historical data of 254 operational risk loss events of commercial banks in China from 1994 to 2009.The loss distribution method based on Monte Carlo simulation and extreme value theory are used to measure the operational risk of commercial banks in China.This paper introduces the definition, classification and characteristics of operational risk of commercial banks, analyzes the performance and causes of operational risks of commercial banks in China, and summarizes the series of measurement methods of operational risks of commercial banks at present.The theory and steps of loss distribution method and extreme value theory measurement in operational risk are analyzed, and the characteristics and application of these two methods are compared and analyzed.After tracing the theory, the loss distribution method based on Monte Carlo simulation and the extreme value theory method are used to measure the operational risk of commercial banks in China.When the loss distribution method is used to measure, it is found that the probability of operational risk loss events of commercial banks in our country is distributed from Weibull, and the intensity of occurrence is from logarithmic normal distribution.The average value of the total amount of operational risk loss is 6.2337e 005, the standard deviation is 1.9824e 006, the value of 99.9 quartile is 2.4517e 007, and the VaR value is 245.17 billion yuan at 99.9% confidence level.If banks can prove that they have taken precautions against expected losses in their daily operations, the regulatory capital to be prepared should be 238.94 billion yuan.By using POT model, it is found that the operational risk of commercial banks in China is 193.11 billion yuan at 99.9% confidence level.
【學(xué)位授予單位】：南京大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2012
【分類號(hào)】：F224;F832.33

【引證文獻(xiàn)】

相關(guān)碩士學(xué)位論文 前2條

1 李勁嫻;基于Copula的商業(yè)銀行風(fēng)險(xiǎn)綜合度量實(shí)證研究[D];山西財(cái)經(jīng)大學(xué);2013年

2 付麗容;我國(guó)上市商業(yè)銀行操作風(fēng)險(xiǎn)大小的實(shí)證分析[D];暨南大學(xué);2013年

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本文編號(hào)：1750512