基于VaR模型的银行同业拆借利率风险度量研究

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浙江财经学院硕士学位论文

摘要

商业银行利率风险是指利率风险资产因利率波动导致其价值向不利方向运动

的不确定性，随着我国利率市场化的推进，尤其是 2008 年金融危机爆发以来，受

国际经济形势和国内经济形势的影响，利率波动日益频繁和剧烈，特别是同业拆

借利率，作为我国市场化程度最高的利率之一，其敏感性日益加强。如何提高同

业拆借利率风险度量准确性越来越受到我国商业银行的重视，而准确度量利率风

险关键是选择什么样的度量方法，当前国际上运用最广泛的利率风险度量模型

VaR 模型法，利率风险度量VaR 模型能否准确预测利率风险对商业银行来说非常

重要。本文在国内外学者研究的基础上，将 ARMA-GARCH 族模型引入到VaR 模

型同业拆借利率风险度量等问题的研究。

本文首先分析了利率风险定义、表现形式、我国同业拆借市场利率风险特征，

并比较分析了传统静态利率风险度量方法和VaR 模型法，结合同业拆借利率风险

特征，提出当前我国商业银行宜采用VaR 模型法度量同业拆借利率风险。然后介

绍了 ARMA-GARCH 族模型，并根据国内外学者对VaR 模型有效性评价研究成果，

提出了一个有效性评价思路。最后选取 2007 年3月12 日到 2010 年1月18 日同

业拆借市场隔夜拆借利率数据为研究对象，将 ARMA-GARCH 族模型及巴塞尔协

议推荐的VaR 方法引入到同业拆借利率风险度量中，结合不同的残差分布假设，

建立了 12 种VaR 模型具体方法对利率风险进行估计，利用无条件覆盖、有条件覆

盖回测技术对具体的VaR 模型估计准确性及突破事件的独立性进行分析，并利用

指标评价工具对通过了回测检验的VaR具体方法进行比较分析。结果发现：在 95%

的置信水平下，GED 分布下的 GARCH 族模型的有效性高于正态分布假设下的

GARCH 族模型，非对称的 GARCH 族模型估计的有效性高于对称的 GARCH 模型，

通过 GED 分布尾部参数及非对称 GARCH 族模型的杠杆系数可以发现，同业拆借

利率收益率序列分布具有“厚尾性”，同业拆借利率波动具有“反杠杆效应”特

征。在90%的置信水平下，所有的VaR 模型具体方法都高估了利率风险，其中 GED

分布下非对称的 GARCH 族模型及历史模拟法估计的准确性相对较高。在 99%置

信水平下，所有的VaR 模型具体方法都通过了混合 Kupiec 检验，但从模型的例外

值次数来看，正态假设分布下的 GARCH 族模型的有效性高于 GED 分布下的

GARCH 族模型。

关键词：VaR；GARCH 族模型；回测技术；杠杆效应

浙江财经学院硕士学位论文

ABSTRACT

Positions in risk assets expose commercial banks in China to interest rate

risk,which refers to the possibility of loss in the market value of the positions dued to

adverse changes in interest rate. Along with the liberalization reformof interest rate in

our country, especially after the explosion of financial crisis in 2008,the fluctuation of

interest rate is becoming more and more frequently and sensitively. Interest rate of

inter-bank, which has become the most marketizational interest in China, is more

sensitive increasingly. The inter-bank interest rate risk which our commercial banks

faces is stronger gradually. How to improve the level of interest rate risk management

attracts more and more attentionof commercial bank in China. The key to measure of

interest rate risk accurately is the which measurement to use. Currently, the most widely

used international risk measurement of interest rate is VaR model. Whether VaR model

can predict the interest rate risk accurately is very important tocommercial banks .

Based on the research of foreign and domestic researchers, we introduced the

ARIMA-GARCH models into the research on measurement of interest rate risk of

inter-bank in the paper.

Firstly ,we analysed the definition and form of interest rate risk, and characteristics

of inter-bank interest rate risk. We take a comparative analysis on traditional static

measurement of interest rate risk and VaR model. Connected with the characteristics of

inter-bank interest rate risk nowadays, we think that VaR model is fit for measurement

of inter-bank interest rate risk. Secondly, this paper will introduce the class of

ARMA-GARCH model, and propose an idea on evaluating the validity of the VaR

model basedg on domestic and foreign research. Thirdly, this paper will chose Chinese

interbank market data as the research object and introduce the ARMA-GARCH models

and the methods recommended by the Basel II into measurement of the interest rate

risk. CombineD with different residual distribution hypothesis, we set up 12 specific

methods of interest rate models to estimate the risk. Unconditional coverage and

conditional coverage back testing are used to analysized the accuracy of VaR models

estimation and independence of exceptional value in the paper. We also made a

comparative analysis on the specific measurements of VaR models by Back-testing.

The results showed that under 95% confidence level, under GED distribution the

浙江财经学院硕士学位论文

GARCH models are more effective than the normal distribution assumption of the

GARCH models, and asymmetric GARCH models estimation are more effective than

the symmetric GARCH models. Through GED distribution tail parameter and

asymmetric GARCH model leverage analysis, we find that income of inter-bank lending

distribution series appear "fat tail", And fluctuation of the income has a "negative

leverage effect" feature. Under 90% confidence level, all measurements of VaR models

overestimate the risk of interest rate, while measurements under the GED distribution of

asymmetric GARCH models and historical simulation method are more accurater

relatively. Under 99% confidence level, all models have passed the mixed Kupiec test,

but through the view of exception, the GARCH models under normal distribution was

more validity than the GARCH models under GED Distribution.

Keywords：Value at Risk；GARCH Model；Backtesting；Leverage Effect

浙江财经学院硕士学位论文

第一章绪论.....................................................................................................................1

第一节研究背景......................................................................................................1

第二节研究目的与意义..........................................................................................1

第三节 VaR 与同业拆借利率风险度量研究综述..................................................2

第四节研究思路与论文结构..................................................................................9

第五节创新之处....................................................................................................10

第二章同业拆借利率风险度量 VaR 模型理论分析...................................................11

第一节利率风险的定义及分类............................................................................11

第二节同业拆借利率风险特征............................................................................12

第三节传统的利率风险度量方法........................................................................13

第四节利率风险度量 VaR 模型法.......................................................................16

第五节 VaR 模型在同业拆借利率风险度量中适用性分析................................19

第三章同业拆借利率波动预测模型及 VaR 模型有效性评价框架构建...................22

第一节同业拆借利率波动预测模型....................................................................22

第二节有效性评价框架的构建............................................................................26

第四章基于 VaR 模型同业拆借利率风险度量实证分析...........................................33

第一节数据选取及分析........................................................................................33

第二节 ARMA-GARCH 族模型条件标准差的计算........................................... 36

第三节利率风险动态 VaR 值的计算...................................................................40

第四节 VaR 模型有效性分析.................................................................................41

第五章结论与展望.......................................................................................................45

第一节结论............................................................................................................45

第二节展望............................................................................................................46

参考文献.........................................................................................................................47

附录一

...........................................................................................................................50

附录二

...........................................................................................................................51

致谢

...............................................................................................................................52

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摘要：

浙江财经学院硕士学位论文摘要商业银行利率风险是指利率风险资产因利率波动导致其价值向不利方向运动的不确定性，随着我国利率市场化的推进，尤其是2008年金融危机爆发以来，受国际经济形势和国内经济形势的影响，利率波动日益频繁和剧烈，特别是同业拆借利率，作为我国市场化程度最高的利率之一，其敏感性日益加强。如何提高同业拆借利率风险度量准确性越来越受到我国商业银行的重视，而准确度量利率风险关键是选择什么样的度量方法，当前国际上运用最广泛的利率风险度量模型VaR模型法，利率风险度量VaR模型能否准确预测利率风险对商业银行来说非常重要。本文在国内外学者研究的基础上，将ARMA-GARCH族模型引入到VaR模型...

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