|
基于GARCH族模型及VaR方法的商业银行利率风险度量
|
Abstract:
我国金融的市场变化日新月异,其所面临的各种风险也在日益增加。利率市场化的发展使利率风险成为商业银行面临的主要风险之一。目前,学者们迫切需要探索和研究利率风险的重要问题,从而制定科学有效的各方面防范措施。本文将以上海银行间同业拆借理论为分析对象,运用GARCH族模型及VaR方法研究商业银行目前所面临的利率风险,进行风险衡量以及管理研究。本文以2020年初至2024年5月底Shibor O/N作为本文实证研究的基础数据。进行GARCH(1, 1)模型拟合数据,得出收益率序列相应的均值方程与条件方差方程,计算VaR预测值。结果显示,对目前中国商业银行的隔夜拆借利率业务而言,该文章选取90%、95%、99%三个不同的置信度,所得到的最大损失分别为11.60%、13.30%和15.43%的资产市场价值。基于目前我国利率的波动性,商业银行预防利率风险可以从以下几个方面入手:提高风险意识、完善金融产品的定价机制、注重人才培养、增加表外业务比重等。
The financial market in China is undergoing rapid changes, and the various risks it faces are also increasing day by day. The development of the interest rate market has made interest rate risk one of the main risks faced by commercial banks. At present, scholars urgently need to explore and research the important issues of interest rate risk, to formulate scientific and effective preventive measures in all aspects. This article will take the theoretical basis of Shanghai Interbank Offerings as the analysis object and use the GARCH family model and VaR method to study the current interest rate risk faced by commercial banks for risk measurement and management research. This article takes Shibor O/N from early 2020 to the end of May 2024 as the basic data for empirical research. A GARCH(1, 1) model is conducted to fit the data, and the corresponding mean equation and conditional variance equation of the return rate sequence are derived to calculate the VaR forecast. The results show that for the current overnight lending rate business of Chinese commercial banks, this article selects three different confidence levels of 90%, 95%, and 99%, and the maximum losses obtained are 11.60%, 13.30%, and 15.43% of the asset market value, respectively. Based on the current volatility of interest rates in China, commercial banks can prevent interest rate risks from the following aspects: improving risk awareness, improving financial product pricing mechanisms, focusing on talent cultivation, and increasing the proportion of off-balance sheet businesses.
[1] | 郑文通. 金融风险管理的VaR方法及其应用[J]. 国际金融研究, 1997(9): 58-62. |
[2] | 张海军. 金融风险的度量方法及其在我国的应用研究[D]: [硕士学位论文]. 南宁: 广西大学, 2002. |
[3] | 韦玉怀. 我国商业银行利率风险管理研究及实证分析[D]: [硕士学位论文]. 北京: 首都经济贸易大学, 2004. |
[4] | 喻晴. 基于VaR模型的我国商业银行利率风险度量及实证研究[D]: [硕士学位论文]. 北京: 首都经济贸易大学, 2018. |
[5] | 陈建华. 利率市场化及商业银行的应对策略研究[J]. 市场论坛, 2018(11): 58-60+68. |
[6] | 李新凤. 利率市场化背景下我国商业银行利率风险管理研究[D]: [硕士学位论文]. 海口: 海南大学, 2016. |
[7] | 谢合亮, 黄卿. 基于蒙特卡洛方法的金融市场风险VaR的算法分析[J]. 统计与决策, 2017(15): 157-162. |
[8] | 刘宇飞. VaR模型及其在金融监管中的应用[J]. 经济科学, 1999(1): 39-50. |
[9] | 赵睿, 赵陵. VaR方法与资产组合分析[J]. 数量经济技术经济研究, 2002(11): 44-47. |
[10] | 於勇成, 陈超. 股票质押式回购业务风险控制——基于多因子模型和VaR方法的研究[J]. 金融经济, 2019(6): 78-82. |
[11] | 王松. 利率市场化对我国商业银行影响的探究[J]. 现代经济信息, 2019(6): 309. |