The Impacts of Credit Derivatives on Bank Portfolio Performance: An Empirical Analysis

Ma, Xiaosu (2012) The Impacts of Credit Derivatives on Bank Portfolio Performance: An Empirical Analysis. [Dissertation (University of Nottingham only)] (Unpublished)

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Abstract

Following the 2007-2009 financial crisis, the debates on the effects of credit derivatives has become more widely and fierce. The key objective of this dissertation is to understand how credit derivatives can affect portfolio performance of banks, and empirically examine whether credit derivatives can improve portfolio performance and reduce bank earnings volatility during both non-crisis and crisis periods. To reach the research objective, two research questions are addressed: The primary question is does usage of credit derivatives improve bank portfolio performance? The secondary question is does hedging through credit derivatives reduce banks’ risk on return? The secondary is set to offer better answer for the primary question.

Panel data models are employed in this study to investigate the research questions. From the estimation results on these models, no evidence is found that using credit derivatives improve banks’ portfolio performance during the non-crisis period. However, the effects of using credit derivatives are proved to be significantly negative on portfolio performance during the financial crisis. Simultaneously, the hedging activities in credit derivatives market are observed to have no significant correlation with the volatility of bank return. It is suggested that banks should pay attention when using credit derivatives and efficient usage is desirable to offset the potential risks brought about by credit derivatives.

This study provides a systematic review on credit derivatives, and shed a light to the effectiveness of credit derivatives during different macroeconomic environments. Nonetheless, there also exist limitations with the restrictions on the model and data. Future studies are suggested to construct more comprehensive models and employ data of more dimensions.

Item Type: Dissertation (University of Nottingham only)
Depositing User: EP, Services
Date Deposited: 08 Apr 2013 11:31
Last Modified: 19 Oct 2017 13:13
URI: https://eprints.nottingham.ac.uk/id/eprint/26102

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