The Role of a Changing Market Environment for Credit Default Swap Pricing

• Author: Stefan Reitz,Julian S. Leppin
• Published date: 01 July 2016
• Date: 01 July 2016
• DOI: http://doi.org/10.1002/ijfe.1543

INTERNATIONAL JOURNAL OF FINANCE AND ECONOMICS

Int. J. Fin. Econ.21: 209–223 (2016)

Published online 14 January 2016 in Wiley Online Library

(wileyonlinelibrary.com). DOI: 10.1002/ijfe.1543

THE ROLE OF A CHANGING MARKET ENVIRONMENT FOR CREDIT

DEFAULT SWAP PRICING

JULIAN S. LEPPIN1and STEFAN REITZ2,

1University of Kiel and Hamburg Institute of International Economics (HWWI), Heimhuder Strasse 71, 20148 Hamburg,Germany

2Kiel Institute for the World EconomyGermany, and Institute for Quantitative Business and Economics Research, University of Kiel,

Heinrich-Hecht-Platz 9, 24118 Kiel, Germany

ABSTRACT

This paper investigates the impact of a changing market environment on the pricing of credit default swaps (CDS) spreads

written on debt from EURO STOXX50 firms. A panel smooth transition regression reveals that parameter estimates of standard

CDS-pricing variables are time varying depending on current values of a set of variables such as the European Central Bank’s

systemic stress composite index, the Sentix index for the current and future economic situation and the VStoxx. These variables

describe the market’s transition between different regimes, thereby reflecting the impact of substantial swings in agents’ risk

perception on CDS spreads. Overall, our results confirm the importance of nonlinearities in the pricing of risk derivativesduring

tranquil and turbulent times. Copyright © 2016 John Wiley & Sons, Ltd.

Received 31 July 2015; Revised 27 October 2015; Accepted 16 November 2015

JEL CODE: G13; G15; C33

KEY WORDS: CDS spreads; financial crisis; panel smooth transition regression; nonlinear pricing; risk dynamics

1. INTRODUCTION

Triggered by the money market breakdown in the aftermath of the Lehman default in 2008, the European Central

Bank (ECB) launched a number of measures to ensure firms’ access to credit. However, the ECB’s unconventional

monetary policy via the credit channel exerted little influence on bank-lending volume to the real sector of the

economy (di Patti and Sette, 2012; Blot and Labondance, 2013). Besides liquidity hoarding, balance sheet consid-

erations and deleveraging, this is because the elevated credit risk of banks’ counterparts clearly dominates lending

rates in times of crisis. Against this backdrop, it is important to understand the time-varying influence of credit

risks’ driving forces. Credit default swaps (CDS) are one of the most popular measures of the credit component

of lending rates.1CDS are insurance contracts insuring the policy holder the par value of the underlying bond that

should the firm default or restructure its debts. In return, the provider receives a periodic payment (the CDS spread)

expressed in percentage points of the bond’s par value.2CDS became increasingly popular in the early 2000s

when their notional outstanding volume rose quickly, peaking in 2007 at $60 trillion. Thereafter, traded volumes

declined considerably to $30 trillion in the first half of 2010 (Vause, 2010) and further in December 2013, with a

notional outstanding amount of $21 trillion according to the Bank of International Settlements. Despite a decline

over time, the overall high liquidity in the market ensures a fast adaption to changing market circumstances, ren-

dering the CDS market especially appealing for the study of the determinants of credit risks. Following the Merton

(1974) model, the literature mainly reported empirical evidence on the linear influence of the risk-free rate, the

firm value, its debt level and the asset volatility. However, the unconditional estimates of parameter coefficients

represent sample-specific averages and do not account for a time-varying market environment. This is particularly

relevant during times of crisis when agents’ perceptions of risk undergo massive changes.

Correspondence to: Stefan Reitz, Kiel Institute for the World Economy Germany, and Institute for Quantitative Business and Economics

Research, University of Kiel, Heinrich-Hecht-Platz 9, 24118 Kiel, Germany.

E-mail: stefan.reitz@qber.uni-kiel.de

Copyright © 2016 John Wiley & Sons, Ltd.

