Investor Sentiment and Credit Default Swap Spreads During the Global Financial Crisis

• Published date: 01 July 2017
• Author: Yuen Jung Park,Jeehye Lee,Sol Kim
• Date: 01 July 2017
• DOI: http://doi.org/10.1002/fut.21828

Investor Sentiment and Credit Default

Swap Spreads During the Global

Financial Crisis

Jeehye Lee, Sol Kim, and Yuen Jung Park*

This paper examines whether investor sentiment can predict credit default swap (CDS) spread

changes. Among several proxies for investor sentiment, change in equity put–call ratio

performs best in predicting variation in CDS spread changes in both firm- and portfolio-level

regressions; in particular, the explanatory power of this proxy is greater for non-investment-

grade firms than for investment-grade firms. More importantly, sentiment may be a critical

factor in determining CDS spread changes during the global financial crisis and may best

explain the differences in CDS spread in the group of firms whose leverage ratio and stock

volatility are highest. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 37:660–688, 2017

1. INTRODUCTION

Recent literature investigating credit spread changes focuses on finding the systematic

determinant to resolve the weak explanatory power of theoretical variables.

1

Avramov,

Jostova, and Philipov (2007) conduct a linear time series regression of differences in

corporate bond credit spread using a structural model incorporating macroeconomic

dummies and the Fama and French (1993) three factors (hereafter, FF factors). These

authors report that although the FF factors are significant in the total sample, the explanatory

power of the FF factors are not observed when corporate bonds are categorized by the three

credit risk groups—low, medium, and high. Galil, Shapir, Amiram, and Ben (2014) propose a

model for CDS spread changes by analyzing the FF factors along with the Pastor and

Jeehye Lee is a graduate at Hankuk University of Foreign Studies, Seoul, Korea. Sol Kim is at College of

Business, Hankuk University of Foreign Studies, Seoul, Korea. Yuen Jung Park is at Department of Finance,

Hallym University, Gangwon-do, Korea. We thank the editor, Robert Webb, and an anonymous referee for

their valuable comments. We also thank discussant Professor Chan Shik Jung and seminar participants for

helpful suggestions at the 2015 Conference of the Asia-Pacific Association of Derivatives. This study was

written while the first author was a student at the Korea Advanced Institute of Science and Technology.

This work was supported by the Hallym University Research Fund, HRF-201602-009. This work was

supported by Hankuk University of Foreign Studies Research Fund of 2017.

JEL Classification: G01, G13, G14

*Correspondence author, Department of Finance, Hallym University, 1 Hallymdaehak-gil, Chuncheon, Gangwon-

do, Korea. Tel: þ82-33-248-1855, Fax: þ82-33-256-3424, e-mail: yjpark@hallym.ac.kr

Received February 2016; Accepted October 2016

1

The theoretical model shows a large gap from the historically observed credit spread. For example, Collin-Dufresne

et al. (2001) show that the variablesof the theoretical model explain only a limited portion of credit spread changes of

bonds. In addition, using credit default swap (CDS) spreads as a proxy of credit risk, Ericsson et al. (2009) show that

theoretical variables have low explanatory power for credit spread changes.

The Journal of Futures Markets, Vol. 37, No. 7, 660–688 (2017)

© 2016 Wiley Periodicals, Inc.

Published online 28 December 2016 in Wiley Online Library (wileyonlinelibrary.com).

DOI: 10.1002/fut.21828

Stambaugh (2003) liquidity factor and the Chen, Roll, and Ross (1986) five factors

(henceforth, CRR factors). Although the coefficients are significant only in the FF factor

model, insignificant coefficients are observed in the CRR and FF factor models in addition to

the Pastor and Stambaugh (2003) liquidity factor.

The poor performance of such empirical studies of rational CDS spread determinants

motivates us to undertake a study considering factors beyond traditional structural

determinants. In this paper, we suggest a novel approach to the determination of corporate

credit spread and investigate whether credit default swap (CDS) spread changes can be well

predicted by investor sentiment proxies, utilizing a structural model that embeds theoretical

factors as control variables. Thus, we test the hypothesis that investor sentiment plays a role

in common or systematic risk factors for CDS spread changes, and we explore which

sentiment measure is the most effective determinant of CDS spread changes.

In addition, a second, more important hypothesis in the present research is that investor

sentiment explains CDS spread changes better in turbulent periods. Tang and Yan (2010)

empirically show that the interaction between default risk of CDS spread and investor

sentiment can be dependent on market states, such as bullish or bearish markets. Further,

Stambaugh et al. (2012) show that when sentiment is widespread in the market, limitations

on short sales play a major role in increasing the severity of asset mispricing. These authors

also hold that a higher level of sentiment, in turn generally considered as an indicator of a

downturn, is associated with more overpricing. Based on the theory of Stambaugh, Yu, and

Yuan (2012) as well as the results from Tang and Yan (2010), we conjecture that, in bad

economic times, overpricing boosted by the impediment to short selling hinders the hedging

of CDSs by equity or equity options and increases CDS spreads, whereas in stable periods the

effect of market-wide sentiment should not be strong, due to the absence of short selling

restrictions. Therefore, to examine the framework set forth in Stambaugh et al. (2012), we

divide the sample period into two periods: the pre-crisis period as a normal term and the

Global Financial Crisis period as a representative turbulent term.

This paper restricts examination to the Global Financial Crisis and does not include the

post-crisis period in the comparative sample. The reason for this is that asset prices in

the U.S. market were externally influenced by several events originating in the debt problems

of Greece in the post-crisis period. Many studies report a contagion effect of the European

debt crisis. See for example, Beirne and Fratzscher (2013), Gorea and Radev (2014), Kim,

Park, and Ryu (2016), and Mink and Haan (2013), among others. In this regard, the post-

crisis period in the U.S. market cannot be considered either a purely normal or purely

(endogenously) turbulent term.

To test our hypotheses, we perform both firm- and portfolio-level regressions. Although

most studies on credit risk conduct regression analyses only at the firm-level, a regression

analysis at the portfolio level is carried out here to alleviate the problem of idiosyncratic risk in

firm-level regressions. We build our 5 5 portfolios using the leverage ratio and stock

volatility of individual firms.

2

The main results of our empirical tests are as follows. First, most of the sentiment

proxies are economically significant factors that explain CDS spread changes. Among the

sentiment measures, change in equity put–call ratio performs best in predicting CDS spread

2

In detail, the process of constructing portfolios follows Kim et al. (2017). We first compute the time series averages

of volatility and leverage ratio for each corporation over the full sample period. Next, we set the upper and lower

limits of five groups classified by the magnitude of the average leverage ratio and then, within a leverage ratio group,

set the upper and lower limits of five groups classified by the magnitude of the average volatility. Each of the 285

firms are allocated to 1 of the 25 portfolios, classified by five volatility and five leverage ratio ranges. Finally, we

calculate the cross-sectional averages of the CDS spread, volatility, and leverage ratio for each portfolio, and

generate the time series of each variable for the 25 separate portfolios.

Investor Sentiment and Credit Default Swap Spreads 661