A credit default swap application by using quantile regression technique


ÜNVAN Y. A.

Communications in Statistics - Theory and Methods, vol.50, no.7, pp.1573-1586, 2021 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 50 Issue: 7
  • Publication Date: 2021
  • Doi Number: 10.1080/03610926.2019.1711126
  • Journal Name: Communications in Statistics - Theory and Methods
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Business Source Elite, Business Source Premier, CAB Abstracts, Compendex, Veterinary Science Database, zbMATH, Civil Engineering Abstracts
  • Page Numbers: pp.1573-1586
  • Keywords: Credit default swap, quantile regression, credit risk
  • Ankara Yıldırım Beyazıt University Affiliated: Yes

Abstract

© 2020 Taylor & Francis Group, LLC.A credit default swap (CDS) is a type of financial derivative or contract that permits an investor to swap or balance the owned credit risk with that of another investor. Recently, this investment tool has been preferred by a wide range of investors in order to minimize their probability of credit default. Many economists and researchers agree that credit default swaps contribute significantly to the prevention of credit risk. Quantile regression provides conditional quantiles of solutions with a general linear model that assumes non parametric form for the conditional distribution of the solutions. Moreover, it is possible to obtain more information by this method which could not be reached directly from standard regression methods. Furthermore, the quantile regression method has a broad application area in various disciplines since it gives the option of modeling the tails of the conditional distribution. In this study, a comprehensive literature review was given at the beginning and then a credit default swap application was implemented by using the quantile regression method. In the application section, the Credit Default Swap variables and the ratings of various independent rating agencies such as Standard&Poor’s, Fitch, and Moody’s of Turkey were used for between 2013 and 2018 as monthly.