信贷挤兑如何影响资产相关性

IF 0.3 4区 经济学 Q4 Economics, Econometrics and Finance
Christopher Paulus Imanto
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引用次数: 0

摘要

本文分析了金融危机前不久贷款市场需求飙升的影响(以下简称“信贷挤兑”)。信贷挤兑影响资产相关性,这是巴塞尔协议III框架的内部评级方法(IRBA)的主要参数之一。在该框架中,这些系数是预先确定的,自《巴塞尔协议II》引入以来从未重新校准过。本文不仅质疑了资产相关性恒定的假设,这是IRBA理论基础的一个基本部分,而且通过一种新的方法表明信贷挤兑增加了资产相关性值。因此,本文提供了证据,证明IRBA中给出的资产相关性被低估了。与其他资产相关性研究相比,本文提供了一种与IRBA基础相适应的新方法。假设资产相关性在IRBA中被正确校准,2%的衰退可能就足够了。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
How a credit run affects asset correlation
This paper analyses the effect of soaring demand in the lending market shortly before a fi nancial crisis (hereinafter "credit run"). A credit run affects the asset correlation, which is one of the main parameters in the Internal Ratings-Based Approach (IRBA) of the Basel III framework. In the framework, these coefficients are predetermined and have not been recalibrated since their introduction in the Basel II Accord. This paper not only questions the assumption of a constant asset correlation, which is a fundamental part of the theoretical foundation of the IRBA, but also shows that a credit run increases the asset correlation value through a new approach. Thereby, this paper offers evidence that the asset correlations given in the IRBA are underestimated. In contrast to other asset correlation studies, this paper provides a new approach which is compatible with the foundation of the IRBA. Assuming asset correlations are calibrated correctly in the IRBA, a 2% downturn add-on may be adequate.
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来源期刊
Journal of Credit Risk
Journal of Credit Risk BUSINESS, FINANCE-
CiteScore
0.90
自引率
0.00%
发文量
10
期刊介绍: With the re-writing of the Basel accords in international banking and their ensuing application, interest in credit risk has never been greater. The Journal of Credit Risk focuses on the measurement and management of credit risk, the valuation and hedging of credit products, and aims to promote a greater understanding in the area of credit risk theory and practice. The Journal of Credit Risk considers submissions in the form of research papers and technical papers, on topics including, but not limited to: Modelling and management of portfolio credit risk Recent advances in parameterizing credit risk models: default probability estimation, copulas and credit risk correlation, recoveries and loss given default, collateral valuation, loss distributions and extreme events Pricing and hedging of credit derivatives Structured credit products and securitizations e.g. collateralized debt obligations, synthetic securitizations, credit baskets, etc. Measuring managing and hedging counterparty credit risk Credit risk transfer techniques Liquidity risk and extreme credit events Regulatory issues, such as Basel II, internal ratings systems, credit-scoring techniques and credit risk capital adequacy.
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