No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Corporate bond market interdependence: Credit spread correlation between and within U.S. and Canadian corporate bond markets
Abstract
This study investigates the correlation and interdependence between and within the U.S. and Canadian corporate bond markets. The empirical framework adopted allows credit spreads to depend on common systematic risk factors derived from structural models and incorporates dynamic conditional correlations (DCC) between spreads. Results show that there is a surprisingly weak correlation between the two markets in normal times. However, during crises, there is a sudden and strong increase in the correlation between U.S. and Canadian credit spreads. The analysis of credit spread correlation within each market also shows an unusual increase in credit spread correlations between sectors and between risk classes in the U.S. during the 2007–2009 global financial crisis. This increase persists over the post-crisis period. By contrast, in Canada, credit spread correlations between sectors remain remarkably stable over time, suggesting an interdependence of credit spreads within the Canadian market.
... Thus, the CCS should be affected by volatility with a positive relationship. Because of the difficulty involved in the calculation of firm's future volatility, various studies have used changes in implied volatility of equity index to proxy firm's future volatility with significant expected results (Boss and Scheicher 2002;Campbell and Taksler 2003;Champagne et al. 2017;Chen et al. 2015;Landschoot 2008;Radier et al. 2016). ...
... Credit rating is thought to incorporate both the probability of default and recovery rate and hence a negative relationship is expected between credit ratings and CCS. Studies have found significant negative relationship between credit ratings and CCS (Campbell and Taksler 2003;Champagne et al. 2017;Covitz and Downing 2007;Tsuji 2005). ...
... The other interest rate variable that affects the CCS is the slope of the yield curve. The study uses the difference between the 10and 2-year government bond yield to proxy for the slope of the term structure (Champagne et al. 2017;Chen et al. 2015;Davies 2008;Georgoutsos and Kounitis 2016). This proxy is interpreted as the future short rates expectations and health of the economy. ...
Understanding the behavior of corporate credit spread is of paramount importance to understand and manage risk in fixed income securities. This study examines the determinants of corporate credit spread in Indian bond market. By adopting a panel data approach, the study estimates a fixed-effects regression equation to analyze the determinants of corporate credit spread in Indian bond market. The variables used in the study are motivated from structural models and macroeconomic variables and include interest rate variables, stock market variables, inflation and economic growth. The study found that the interest rate variables, stock market variables and inflation are the key variables in explaining the level of corporate credit spread in Indian bond market. The results are robust to the traditional approach of using aggregate yield spread for the whole sample and also when the sample was divided using different industrial classification. Overall, the study highlights the importance of stable interest rate and inflationary environment for the development of Indian corporate bond market.
... It means that if there is no significant increase in the price co-movement between two stock indices following a shock, it suggests that there is a strong and stable interdependence between the two stock markets. This approach is considered relatively simple, which is fitted to be used as a measure in comparing interdependence between two markets during a stable period (Champagne et al., 2017). ...
The study investigates the effect of spillovers regionally and worldwide on Vietnam’s stock market. The vector error correction model (VECM) is used to analyze the collected data from Bloomberg. Data include eight comparable stock market indices, namely DJI, NKY, SHCOMP, SET, MXSG, PCOMP, FBMKLCI, and JCI. The empirical results show that the Vietnamese stock market is significantly linked to that of the other countries. During the periods of dramatic market fluctuation, the cross-border linkage between the VN-Index and comparable indices is the largest. The impact of the stock markets of small nearby countries such as Singapore and Malaysia on the Vietnamese stock market are greater than the other large ones including the United States, Japan and China. The findings of this study contribute to the literature on the interdependence and interaction of stock markets. The common economic integration, especially in showing that effect found in other studies, is meaningful in explaining the observed phenomenon.
... Applying the DCC-GARCH model, Tsukuda et al. (2017) revealed that integration within the Asian bond market is shallow. Champagne et al. (2017) showed strong market interdependence between the U.S. and Canadian corporate bond markets. Kenourgios et al. (2013) investigated the contagion effects of the global financial crisis (GFC) by applying an asymmetric generalized DCC (AG-DCC) model to Brazilian long-term bond indices, along with other asset classes, and found contagion links of the bonds with U.S. stocks, real estate, and commodities. ...
This study examines emerging market (EM) local bonds from a portfolio risk perspective and suggests methodologies for risk evaluation, on which the literature is limited. Despite the growth of EM bond funds in recent years, comprehensive studies regarding this industry have been scarce. In light of this, 203 different local bonds of EM countries-Indonesia, Brazil, India, South Africa, Mexico, and Turkey-are elaborated in terms of return, volatility, and cross-correlation features. This study focuses on an untouched field-long memory properties-and the application of fractional models to EM bond portfolios. Based on the outcomes of a dynamic conditional correlation and fractionally integrated generalized autoregressive conditional heteroscedasticity approach and related value at risk analysis, the study finds that fractional models are useful tools for risk management, as they deliver satisfactory empirical results for several static and dynamic versions of EM bond portfolios. Introduction and literature review
Recently, corporate bond has been becoming a controversial debate topic in Vietnam. During 2022 Vietnamese economy experienced several devastating scandals relating to corporate bond that leading to the issuance of several legal regulations by the Government. Realistically, given the strong encouragement of Vietnamese Government, the size of corporate bond market has reached approximately 21% of national GDP (VCCI, 2022) illustrating a considerable attention of potential investors and local businesses on this typical capital raising instruments. However, from both academic and society perspectives, there has been a research gap in the extant literature review on the underlying reasons for corporate bond demand in an emerging country. Hence, the study aims to comprehensively examine the determinants of investor demand for corporate bond in the context of Vietnam. The research objectives are achieved by applying both qualitative and quantitative approaches. While the qualitative method which based on VCCI (2022) questionnaires to identify and document the corporate bond demand, the quantitative method provides statistical evidences on determinants of corporate bond demand. The research result show that the credit risk and bond market presence are significant attributes for investor demand. These indicators are more pronounced during the crisis period which is explained by information asymmetry theory and the benefit of diversifications. The research findings are consistent with prior studies of Hotchkiss and Ronen (2002), Hale and Santos (2008) stating that high investor demand shorten the time for subsequent bond issuance events and potentially reduces the corporate’s cost of capital. Therefore, the research is beneficial to the Government, corporate bond issuers and researchers.
The bond market is an important part of the capital market, reflecting the debtor-creditor relationship. Correspondingly, the P2P network lending platform, which plays a vital role in emerging Internet Finance, represents the same relationship. In both markets, the risks in investment and financing channels are complex and diverse, including liquidity risk, market risk, tax risk and so on. All the risks do not exist alone, performed as an integrated risk. This paper establishes an index for measuring corporate bonds’ liquidity, by using a Copula-GARCH approach and generating empirical distribution to integrate the liquidity risk and market risk of corporate bonds. Particularly, according to the Likelihood function test results, t-Copula is the optimum Copula function. The model can also be applied to measure the integrated risk of the P2P network lending platform after improvement.
This study utilizes the nonlinear ARDL (NARDL) model proposed by Shin, Yu, and Greenwood-Nimmo (2014) to quantify the potentially asymmetric transmission of positive and negative changes in each of the possible determinants of industry-level corporate bond credit spreads in China. The determinants we consider include the corresponding industry stock price, China’s stock market volatility, the level and slope of the yield curve (i.e., the interest rate), the industrial production growth rate, and the inflation rate. The empirical results suggest substantial asymmetric effects of these determinants on credit spreads, with the positive changes in the determinants showing larger impacts than the negative changes for most industries we consider. Moreover, the corresponding industry stock prices, the interest rate, and the industrial production growth rate negatively drive the industry credit spreads for many industries. In turn, China’s stock market volatility and the inflation rate positively affect the credit spreads at each industry level. These findings may be helpful to investors, bond issuers and policymakers in understanding the dynamics of credit risks and corporate bond rates at the industry level.
Empirical evidence of cross-asset market linkages when bond markets plunge is scarce in the co-movement correlation literature. In this note we investigate stock-sovereign bond return correlations focusing on the Greek debt crisis period. We show that the return correlation between the two asset classes has increased during the crisis period and contagion has occurred. We conclude that stock-bond diversification benefits decrease with bond market uncertainty.
This paper examines transmission of shocks between the U.S. and foreign markets to delineate interdependence from contagion of the U.S. financial crisis by constructing shock models for partially-overlapping and non-overlapping markets. There exists important bi-directional, yet asymmetric, interdependence and contagion in emerging markets, with important regional variations. Interdependence is driven more by U.S. shocks, while contagion is driven more by emerging market shocks. Frontier markets also exhibit interdependence and contagion to U.S. shocks. Except for Latin America, there is no contagion from U.S. to emerging markets. But there is contagion from emerging markets to the U.S.
http://papers.ssrn.com/sol3/cf_dev/AbsByAuth.cfm?per_id=327186
This paper examines stock market co-movements. It begins with a discussion of several conceptual issues involved in measuring these movements and how to test for contagion. Standard tests examine if cross-market correlation in stock market returns increase during a period of crisis. The measure of cross-market correlations central to this standard analysis, however, is biased. The unadjusted correlation coefficient is conditional on market movements over the time period under consideration, so that during a period of turmoil when stock market volatility increases, standard estimates of cross-market correlations will be biased upward. It is straightforward to adjust the correlation coefficient to correct for this bias. The remainder of the paper applies these concepts to test for stock market contagion during the 1997 East Asian crises, the 1994 Mexican peso collapse, and the 1987 U.S. stock market crash. In each of these cases, tests based on the unadjusted correlation coefficients find evidence of contagion in several countries, while tests based on the adjusted coefficients find virtually no contagion. This suggests that high market co-movements during these periods were a continuation of strong cross-market linkages. In other words, during these three crises there was no contagion, only interdependence.
We propose a model of correlated multi-firm default with incomplete information. While public bond investors observe issuers' assets and defaults, we suppose that they are not informed about the threshold asset level at which a firm is liquidated. Bond investors form instead a prior on these thresholds. Stochastic dependence between default events is induced through correlated asset values and correlated default thresholds. The former results from dependence of firms on common macroeconomic factors, while the latter corresponds to direct inter-firm linkages. Having addressed this issuer interdependence, the predictions of our model are consistent with empirically well documented facts, in particular the clustering of defaults. We characterize joint conditional default probabilities as assessed by the imperfectly informed secondary market. The representation of dependence via (conditional) copulas is emphasized. We propose the default time copula as a consistent default correlation measure, which overcomes the limitations of existing covariance based measures. A case study is examined, where issuers' assets follow geometric Brownian motions and bond investors' threshold prior is uniform.
Time varying correlations are often estimated with multivariate generalized autoregressive conditional heteroskedasticity (GARCH) models that are linear in squares and cross products of the data. A new class of multivariate models called dynamic conditional correlation models is proposed. These have the flexibility of univariate GARCH models coupled with parsimonious parametric models for the correlations. They are not linear but can often be estimated very simply with univariate or two-step methods based on the likelihood function. It is shown that they perform well in a variety of situations and provide sensible empirical results.
In this study we test for the possible contagion effects of the 10-year Greek government bond yield. We first employ the well-documented adjusted correlation coefficient of Forbes and Rigobon (2002) and then we estimate an exponential generalized autoregressive conditional heteroskedasticity model extended for volatility spillovers. Finally, we propose an extension of the corrected Dynamic Conditional Correlation (cDCC) model, which allows for structural breaks in the correlation dynamics. The suggested cDCC specification provides a natural testing framework for the correlation contagion hypothesis. Compared with other similar approaches, the proposed structural break cDCC approach allows for consistent inferences. The results do not confirm any contagious effects stemming from the 10-year Greek sovereign bond.
This paper investigates the contagion effects of the Global Financial Crisis (2007–2009) by examining ten sectors in six developed and emerging regions during different phases of the crisis. The analysis tests different channels of financial contagion across regions and real economy sectors by utilizing dynamic conditional correlation from the multivariate Fractionally Integrated Asymmetric Power ARCH (FIAPARCH) model. Evidence shows that the GFC can be characterized by contagion effects across regional stock markets and regional financial and non-financial sectors.
However, Developed Pacific region and some sectors in particular Consumer Goods, Healthcare and Technology across all regions seem to be less affected by the crisis, while the most vulnerable sectors are observed in the emerging Asian and European regions. Further, the analysis on a crisis phase level indicates that the most severe contagion effects exist after the failure of Lehman Brothers limiting the effectiveness of portfolio diversification.
We analyze the transmission of the 2007 to 2009 financial crisis to 415 country-industry equity portfolios. We use a factor model to predict crisis returns, defining unexplained increases in factor loadings and residual correlations as indicative of contagion. While we find evidence of contagion from the U.S. and the global financial sector, the effects are small. By contrast, there has been substantial contagion from domestic markets to individual domestic portfolios, with its severity inversely related to the quality of countries’ economic fundamentals. This confirms the “wake-up call” hypothesis, with markets focusing more on country-specific characteristics during the crisis.This article is protected by copyright. All rights reserved.
This paper examines the risks and returns of long‐term low‐grade bonds for the period 1977–1989. We find: (1) low‐grade bonds realized higher returns than higher‐grade bonds and lower returns than common stocks, and low‐grade bonds exhibited less volatility than higher‐grade bonds due to their call features and high coupons; (2) there is no relation between the age of low‐grade bonds and their realized returns; cyclical factors explain much of the observed relation between default rates and bond age; and (3) low‐grade bonds behave like both bonds and stocks. Despite this complexity there is no evidence that low‐grade bonds are systematically over‐ or under‐priced.
Using the Markov regime-switching model, this paper examines factor loadings on macroeconomic, market sentiment and other variables that may explain North American investment-grade and high-yield credit default swap indices (CDX) over the period 2003-2011. In both crisis and tranquil market states, spreads are positively related to the market-wide default premium and VIX, and negatively related to changes in Treasury bond yields, the underlying stock index returns and the Fama-French's High-Minus-Low factor. The magnitude of the factor loadings is higher during crisis periods. The results suggest the need to consider regime dependent hedge ratios to manage credit risk exposure.
This paper conducts an investigation of volatility transmission between stock markets in Hong Kong, Europe and the United States covering the time period from 2000 up to 2011. Using intra-daily data we compute realized volatility time series for the three markets and employ a Heterogeneous Autoregressive Distributed Lag Model as our baseline econometric specification. Motivated by the presence of various crisis events contained in our sample, we detect time-variation and structural breaks in volatility spillovers. Particularly during the financial crisis of 2007, we find effects consistent with the notion of contagion, suggesting strong and sudden increases in the cross-market synchronization of chronologically succeeding volatilities. Investigating the role of mean breaks and conditional heteroskedasticity in the realized volatilities, however, we find the latter to be the main driver of breaks in volatility spillovers. Taking the volatility of realized volatilities into account, we find no evidence of contagion anymore.
This study empirically examines the impact of the interaction between market and default risk on corporate credit spreads. Using credit default swap (CDS) spreads, we find that average credit spreads decrease in GDP growth rate, but increase in GDP growth volatility and jump risk in the equity market. At the market level, investor sentiment is the most important determinant of credit spreads. At the firm level, credit spreads generally rise with cash flow volatility and beta, with the effect of cash flow beta varying with market conditions. We identify implied volatility as the most significant determinant of default risk among firm-level characteristics. Overall, a major portion of individual credit spreads is accounted for by firm-level determinants of default risk, while macroeconomic variables are directly responsible for a lesser portion.
We propose a multi-firm first-passage credit model in which investors have incomplete information. In this model, investors observe neither a firm's value nor its default barrier. The model takes into account the short-term risk inherent in default events, the market-wide impact of defaults on security prices due to counterparty relations among firms, and the cyclical default dependence effects observed in credit markets. We explicitly calculate the pricing trend and the arrival intensity of the kth-to-default. These results furnish (1) tractable reduced- form formulae for arrival probabilities of sequential dependent defaults and prices of multi-name credit derivatives, and (2) an algorithm for the simulation of sequential unpredictable default times.
The current economic climate makes understanding credit risk correlation particularly important. After allowing for a comprehensive set of observable firm-specific, industry, market, and macroeconomic factors, there is an economically significant co-movement in credit default swap spreads that remains to be explained. Including a time dummy completely accounts for the remaining co-movement, confirming the existence of a systematic component that has been previously unaccounted for. Our findings suggest that it may be important to consider unobservable risk factor(s) in credit risk models.
Bekaert et al. (2005) define contagion as “correlation over and above what one would expect from economic fundamentals”. Based on a two-factor asset pricing specification to model fundamentally-driven linkages between markets, they define contagion as correlation among the model residuals, and develop a corresponding test procedure. In this paper, we investigate to what extent conclusions from this contagion test depend upon the specification of the time-varying factor exposures. We develop a two-factor model with global and regional market shocks as factors. We make the global and regional market exposures conditional upon both a latent regime variable and three structural instruments, and find that, for a set of 14 European countries, this model outperforms more restricted versions. The structurally-driven increase in global (regional) market exposures and correlations suggest that market integration has increased substantially over the last three decades. Using our optimal model, we do not find evidence that further integration has come at the cost of contagion. We do find evidence for contagion, however, when more restricted versions of the factor specifications are used. We conclude that the specification of the global and regional market exposures is an important issue in any test for contagion.
We investigate the interdependence of the default risk of several Eurozone countries (France, Germany, Italy, Ireland, Netherlands, Portugal, and Spain) and their domestic banks during the period June 2007 - May 2010, using daily credit default swaps (CDS). Bank bailout programs changed the composition of both banks’ and sovereign balance sheets and, moreover, affected the linkage between the default risk of governments and their local banks. Our main findings suggest that in the period before bank bailouts the contagion disperses from bank credit spreads into the sovereign CDS market. After bailouts, a financial sector shock affects more strongly sovereign CDS spreads in the short-run, however, the impact becomes insignificant at a long horizon. Furthermore, government CDS spreads become an important determinant of banks’ CDS series. The interdependence of government and bank credit risk is heterogeneous across countries, but homogeneous within the same country.
We examine the impact of bond market access (measured by having a credit rating) on leverage for Canadian high credit quality (HQ) and low credit quality (LQ) firms, and find that the leverage impact is more pronounced for LQ firms. The results are similar for U.S. firms. Our results are confirmed when we control for the firm's credit quality, examine the change in leverage around rating initiation, and account for the issue size effect. A similar leverage impact for Canadian and U.S. LQ firms suggests that the Canada-U.S. bond market integration has mitigated the financial constraints for Canadian LQ firms.
Motivated by recent financial crises in East Asia and the United States where the downfall of a small number of firms had an economy-wide impact, this paper generalizes existing reduced-form models to include default intensities dependent on the default of a counterparty. In this model, firms have correlated defaults due not only to an exposure to common risk factors, but also to firm-specific risks that are termed “counterparty risks.” Numerical examples illustrate the effect of counterparty risk on the pricing of defaultable bonds and credit derivatives such as default swaps.
Using dealer’s quotes and transactions prices on straight industrial bonds, we investigate the determinants of credit spread changes. Variables that should in theory determine credit spread changes have rather limited explanatory power. Further, the residuals from this regression are highly cross-correlated, and principal components analysis implies they are mostly driven by a single common factor. Although we consider several macroeconomic and financial variables as candidate proxies, we cannot explain this common systematic component. Our results suggest that monthly credit spread changes are principally driven by local supply/demand shocks that are independent of both credit-risk factors and standard proxies for liquidity.
This paper presents a systematic comparison between the determinants of euro and US dollar yield spread dynamics. The results show that US dollar yield spreads are significantly more affected by changes in the level and the slope of the default-free term structure and the stock market return and volatility. Surprisingly, euro yield spreads are strongly affected by the US (and not the euro) level and slope. This confirms the dominance of US interest rates in the corporate bond markets. Interestingly, I find that liquidity risk is higher for US dollar corporate bonds than euro corporate bonds. For both regions, the effect of changes in the bid-ask spread is mainly significant during periods of high liquidity risk. Finally, the results indicate that the credit cycle as measured by the region-specific default probability significantly increases US yield spreads. This is not the case for euro yield spreads.
Economic theory tells us that market and credit risks are intrinsically related to each other and not separable. We describe the two main approaches to pricing credit risky instruments: the structural approach and the reduced form approach. It is argued that the standard approaches to credit risk management – CreditMetrics, CreditRisk+ and KMV – are of limited value when applied to portfolios of interest rate sensitive instruments and in measuring market and credit risk.Empirically returns on high yield bonds have a higher correlation with equity index returns and a lower correlation with Treasury bond index returns than do low yield bonds. Also, macro economic variables appear to influence the aggregate rate of business failures. The CreditMetrics, CreditRisk+ and KMV methodologies cannot reproduce these empirical observations given their constant interest rate assumption. However, we can incorporate these empirical observations into the reduced form of Jarrow and Turnbull (1995b). Drawing the analogy. Risk 5, 63–70 model. Here default probabilities are correlated due to their dependence on common economic factors. Default risk and recovery rate uncertainty may not be the sole determinants of the credit spread. We show how to incorporate a convenience yield as one of the determinants of the credit spread.For credit risk management, the time horizon is typically one year or longer. This has two important implications, since the standard approximations do not apply over a one year horizon. First, we must use pricing models for risk management. Some practitioners have taken a different approach than academics in the pricing of credit risky bonds. In the event of default, a bond holder is legally entitled to accrued interest plus principal. We discuss the implications of this fact for pricing. Second, it is necessary to keep track of two probability measures: the martingale probability for pricing and the natural probability for value-at-risk. We discuss the benefits of keeping track of these two measures.
The paper examines the extent of the current global crisis and the contagion effects it induces by conducting an empirical investigation of the extreme financial interdependences of some selected emerging markets with the US. Several copula functions that provide the necessary flexibility to capture the dynamic patterns of fat tail as well as linear and nonlinear interdependences are used to model the degree of cross-market linkages. Using daily return data from Brazil, Russia, India, China (BRIC) and the US, our empirical results show strong evidence of time-varying dependence between each of the BRIC markets and the US markets, but the dependency is stronger for commodity-price dependent markets than for finished-product export-oriented markets. We also observe high levels of dependence persistence for all market pairs during both bullish and bearish markets.
I conduct an empirical investigation into the pricing of subprime asset-backed collateralized debt obligations (CDOs) and their contagion effects on other markets. Using data for the ABX subprime indexes, I find strong evidence of contagion in the financial markets. The results support the hypothesis that financial contagion was propagated primarily through liquidity and risk-premium channels, rather than through a correlated-information channel. Surprisingly, ABX index returns forecast stock returns and Treasury and corporate bond yield changes by as much as three weeks ahead during the subprime crisis. This challenges the popular view that the market prices of these “toxic assets” were unreliable; the results suggest that significant price discovery did in fact occur in the subprime market during the crisis.
We examine the ability of observed macroeconomic factors and the possibility of changes in regime to explain the proportion of yield spreads caused by the risk of default in the context of a reduced form model. For this purpose, we extend the Markov-switching risk-free term structure model of Bansal and Zhou (2002) to the corporate bond setting and develop recursive formulas for default probabilities, risk-free and risky zero-coupon bond yields as well as credit default swap premia. The model is calibrated with consumption, inflation, risk-free yields and default data for Aa, A and Baa bonds from the 1987 to 2008 period. We find that our macroeconomic factors are linked with two out of three sharp increases in the spreads during this sample period, indicating that the spread variations can be related to macroeconomic undiversifiable risk.
This paper examines the correlation between the returns on individual stocks and the yield changes of individual bonds issued by the same firm, and finds that they are negatively and contemporaneously correlated. This suggests that individual stocks and bonds are driven by firm-specific information that is predominantly related to the mean, rather than the variance, of the firm's underlying assets. Furthermore, I find that lagged stock returns have explanatory power for current bond yield changes, while current stock returns are unrelated to lagged bond yield changes. This shows that stocks lead bonds in reflecting firm-specific information.
This paper develops a framework for analyzing the impact of macroeconomic conditions on credit risk and dynamic capital structure choice. We begin by observing that when cash flows depend on current economic conditions, there will be a benefit for firms to adapt their default and financing policies to the position of the economy in the business cycle phase. We then demonstrate that this simple observation has a wide range of empirical implications for corporations. Notably, we show that our model can replicate observed debt levels and the countercyclicality of leverage ratios. We also demonstrate that it can reproduce the observed term structure of credit spreads and generate strictly positive credit spreads for debt contracts with very short maturities. Finally, we characterize the impact of macroeconomic conditions on the pace and size of capital structure changes, and debt capacity.
In this paper, we test for contagion within the East Asian region, contagion being defined as a significant increase in the degree of comovement between stock returns in different countries. For this purpose, we use a parameter stability test, and, following [Rigobon, R., 2003a. On the measurement of the international propagation of shocks: is the transmission stable?, Journal of International Economics], we control for three types of bias, resulting from heteroscedasticity, endogeneity and omitted variable, respectively. The null of interdependence against the alternative of contagion is then tested as an overidentifying restriction. Unlike other studies, our approach is based on full-sample estimation, and hence avoids the power problems arising from the typical situation of a large “noncrisis” and a small “crisis” sample. We also select endogenously the breakpoints corresponding to the beginning of the contagion period, and finally we impose more plausible restrictions to identify the system. Our findings suggest the existence of contagion within the East Asian region, consistent with crisis-contingent theories of asset market linkages.
This paper builds on a standard factor model of stock market returns to reconsider recent empirical literature on contagion in financial markets based on bivariate correlation analysis. According to this literature, contagion is defined as a structural break in the linear transmission mechanism of financial shocks. Using our framework, we show that the result of ‘no contagion, only interdependence’ stressed by recent contributions is due to arbitrary and unrealistic restrictions on the variance of country-specific shocks. We focus on the international effects of the Hong Kong stock market crisis of October 1997 as a case study. For plausible values of the variance of country-specific shocks in Hong Kong, current tests cannot reject the null of interdependence for 16 countries out of a sample of 17. Our analysis strongly questions such conclusion, finding evidence of ‘contagion’ for at least five countries.
The recent accounting scandals at Enron, WorldCom, and Tyco were related to the misrepresentation of liabilities. We provide a structural model of correlated multi-firm default, in which public bond investors are uncertain about the liability-dependent barrier at which individual firms default. Investors form prior beliefs on the barriers, which they update with the default status information of firms arriving over time. Whenever a firm suddenly defaults, investors learn about the default threshold of closely associated business partner firms. This updating leads to “contagious” jumps in credit spreads of business partners. We characterize joint default probabilities and the default dependence structure as assessed by investors, where we emphasize the the modeling of dependence with copulas. A case study based on Brownian asset dynamics illustrates our results.
This paper introduces measures of volatility and jump risk that are based on individual stock options to explain credit spreads on corporate bonds. Implied volatilities of individual options are shown to contain useful information for credit spreads and improve on historical volatilities when explaining the cross-sectional and time-series variation in a panel of corporate bond spreads. Both the level of individual implied volatilities and (to a lesser extent) the implied-volatility skew matter for credit spreads. Detailed principal component analysis shows that a large part of the time-series variation in credit spreads can be explained in this way.
This paper is an empirical investigation of the excess comovement among 82 industry indexes in the U.S. stock market between January 5, 1976 and December 31, 2001. We define excess comovement as the covariation between two assets beyond what can be explained by fundamental factors. In our analysis, the fundamental factors are sector groupings and the three Fama-French factors. We then estimate residuals of joint (FGLS) rolling regressions of these fundamentals on industry returns. Finally, we compute excess comovement as the mean of square unconditional, statistically significant correlations of these residuals. We show that excess comovement is high (about 0.07, i.e., equivalent to an average absolute correlation of 0.26), statistically significant, and represents an economically significant portion (almost 30%) of the average gross square return correlation. Excess comovement is also uniformly significant across industries and over time and only weakly asymmetric, i.e., not significantly different in rising or falling markets.We explain more than 23% of this market-wide (and up to 73% of sector-wide) excess square correlation by its positive relation to proxies for information heterogeneity and U.S. monetary and real conditions, and its negative relation to market volatility and the level of the short-term interest rate. This evidence is consistent with the implications of portfolio rebalancing and product market theories of financial contagion, but offers little or no support for the correlated liquidity shock channel.
If options are correctly priced in the market, it should not be possible to make sure profits by creating portfolios of long and short positions in options and their underlying stocks. Using this principle, a theoretical valuation formula for options is derived. Since almost all corporate liabilities can be viewed as combinations of options, the formula and the analysis that led to it are also applicable to corporate liabilities such as common stock, corporate bonds, and warrants. In particular, the formula can be used to derive the discount that should be applied to a corporate bond because of the possibility of default.
We use an intensity-based framework to study the relation between macroeconomic fundamentals and cycles in defaults and rating activity. Using Standard and Poor's U.S. corporate rating transition and default data over the period 1980-2005, we directly estimate the default and rating cycle from micro data. We relate this cycle to the business cycle, bank lending conditions, and financial market variables. In line with earlier studies, the macro variables appear to explain part of the default cycle. However, we strongly reject the correct dynamic specification of these models. The problem is solved by adding an unobserved dynamic component to the model, which can be interpreted as an omitted systematic credit risk factor. By accounting for this latent factor, many of the observed macro variables loose their significance. There are a few exceptions, but the economic impact of the observed macro variables for credit risk remains low. We also show that systematic credit risk factors differ over transition types, with risk factors for downgrades being noticeably different from those for upgrades. We conclude that portfolio credit risk models based only on observable systematic risk factors omit one of the strongest determinants of credit risk at the portfolio level. This has obvious consequences for current modeling and risk management practices.
This article provides an empirical decomposition of the default, liquidity, and tax factors that determine expected corporate bond returns. In particular, the risk premium associated with a default event is estimated. The intensity-based model is estimated using bond price data for 104 US firms and historical default rates. Significant risk premia on common intensity factors and important tax and liquidity effects are found. These components go a long way towards explaining the level of expected corporate bond returns. Adding a positive default event risk premium helps to explain the remaining error, although this premium cannot be estimated with high statistical precision. Copyright 2005, Oxford University Press.
Evaluating default correlations or the probabilities of default by more than one firm is an important task in credit analysis, derivatives pricing, and risk management. However, default correlations cannot be measured directly, multiple-default modeling is technically difficult, and most existing credit models cannot be applied to analyze multiple defaults. This article develops a first-passage-time model, providing an analytical formula for calculating default correlations that is easily implemented and conveniently used for a variety of financial applications. The model also provides a theoretical justification for several empirical regularities in the credit risk literature. Article published by Oxford University Press on behalf of the Society for Financial Studies in its journal, The Review of Financial Studies.
This paper examines the risks and returns of long-term low-grade bonds for the period 1977-1989. We find: (1) low-grade bonds realized higher returns than higher-grade bonds and lower returns than common stocks, and low-grade bonds exhibited less volatility than higher-grade bonds due to their call features and high coupons; (2) there is no relation between the age of low-grade bonds and their realized returns; cyclical factors explain much of the observed relation between default rates and bond age; and (3) low-grade bonds behave like both bonds and stocks. Despite this complexity there is no evidence that low-grade bonds are systematically over- or under-priced. The Journal of Finance, Vol. XLVI, No. 1 (March 1991), pp. 49-74. (Reprinted with permission of The Journal of Finance.)
Because the option to call a corporate bond should rise in value when bond yields fall, the relation between noncallable Treasury yields and spreads of corporate bond yields over Treasury yields should depend on the callability of the corporate bond. I confirm this hypothesis for investment-grade corporate bonds. Although yield spreads on both callable and noncallable corporate bonds fall when Treasury yields rise, this relation is much stronger for callable bonds. This result has important implications for interpreting the behavior of yields on commonly used corporate bond indexes, which are composed primarily of callable bonds. Copyright The American Finance Association 1998.
We develop a simple approach to valuing risky corporate debt that incorporates both default and interest rate risk. We use this approach to derive simple closed-form valuation expressions for fixed and floating rate debt. The model provides a number of interesting new insights about pricing and hedging corporate debt securities. For example, we find that the correlation between default risk and the interest rate has a significant effect on the properties of the credit spread. Using Moody's corporate bond yield data, we find that credit spreads are negatively related to interest rates and that durations of risky bonds depend on the correlation with interest rates. This empirical evidence is consistent with the implications of the valuation model. Copyright 1995 by American Finance Association.
Time varying correlations are often estimated with multivariate generalized autoregressive conditional heteroskedasticity (GARCH) models that are linear in squares and cross products of the data. A new class of multivariate models called dynamic conditional correlation models is proposed. These have the flexibility of univariate GARCH models coupled with parsimonious parametric models for the correlations. They are not linear but can often be estimated very simply with univariate or two-step methods based on the likelihood function. It is shown that they perform well in a variety of situations and provide sensible empirical results.
This paper explores the effect of equity volatility on corporate bond yields. Panel data for the late 1990s show that idiosyncratic firm-level volatility can explain as much cross-sectional variation in yields as can credit ratings. This finding, together with the upward trend in idiosyncratic equity volatility documented by Campbell, Lettau, Malkiel, and Xu (2001) , helps to explain recent increases in corporate bond yields. Copyright 2003 by the American Finance Association.
Heteroskedasticity biases tests for contagion based on correlation coefficients. When contagion is defined as a significant increase in market comovement after a shock to one country, previous work suggests contagion occurred during recent crises. This paper shows that correlation coefficients are conditional on market volatility. Under certain assumptions, it is possible to adjust for this bias. Using this adjustment, there was virtually no increase in unconditional correlation coefficients (i.e., no contagion) during the 1997 Asian crisis, 1994 Mexican devaluation, and 1987 U.S. market crash. There is a high level of market comovement in all periods, however, which we call interdependence. Copyright The American Finance Association 2002.