Credit Spread Changes Research Articles

Contingent Claims and Hedging of Credit Risk with Equity Options

Abstract Using contingent-claims valuation, we introduce novel hedge ratios for credit exposures using put options. Option hedge ratios are generally in line with the empirical sensitivities of credit spread changes to put option returns and, relative to stock hedge ratios, produce further reductions in volatility for a portfolio of North American firms. We show that option hedge ratios capture option-specific credit exposure related to the VIX index and the default spread, which is unaccounted for by Merton’s (1974) equity hedge ratios alone. Combining stocks and put options for credit risk hedging can be done effectively using the volatility smirk. (JEL E43, E44, G10)

Credit Spreads, Leverage and Volatility: A Cointegration Approach

This work documents the existence of a cointegration relationship between credit spreads, leverage and equity volatility for a large set of US companies. It is shown that accounting for the long-run equilibrium dynamic between these variables is essential to correctly explain credit spread changes. Using a novel structural model in which equity is modeled as a compound option on the firm’s assets, a new methodology for estimating the unobservable market value of the firm’s assets and volatility is developed. The proposed model allows to significantly reduce the pricing errors in predicting credit spreads when compared with several structural models. In terms of correlation analysis, it is shown that not accounting for the long-run equilibrium equation embedded in an error correction mechanism (ECM) results into a misspecification problem when regressing a set of explanatory variables onto the spread changes. Once credit spreads, leverage and volatility are correctly modeled, thus allowing for a long-run equilibrium, the fit of the regressions sensibly increases if compared to the results of previous research. It is further shown that most of the cross-sectional variation of the spreads appears to be more driven by firm-specific characteristics rather than systematic factors.

Credit rating agencies, information asymmetry and US bond liquidity

AbstractDo rating announcements reduce information asymmetries? We investigate the effect of rating disclosures on the volatility and liquidity of the US bond market. Although rating agencies' decisions are often anticipated by credit spread changes, we show that in the case of no regulatory change, their release can reduce volatility and the bid–ask spread. This reduction is stronger when the rating agency announcement has been anticipated by the market, namely, after downgrades, whereas upgrades trigger a mixed reaction. These findings are consistent with the predictions of a simple sequential trade model with event uncertainty and noise and informed traders.

Credit spreads in the European green bond market: A daily analysis of the COVID‐19 pandemic impact

AbstractFinancial crises and economic downturns provide a unique opportunity to investigate the behavior of investors and financial instruments and shed light in the market's anticipation of future economic growth. In view of the current crisis, we examine how the COVID‐19 pandemic affected the European green bond market. Using daily data from Thomson Reuter's Refinitiv, we conducted event studies on corporate credit spread changes over the period from January 1 to December 31, 2020. Our results reveal that green bonds' credit spreads increased significantly after the start of the coronavirus outbreak. However, as the fear of the pandemic eased in response to positive news about the vaccines, green bonds' credit spreads fell below conventional bonds. Overall, green bonds showed a higher risk exposure and lower resilience to distress while profiting during an upside. Our paper provides the first evidence about the impact of the COVID‐19 pandemic and the announcement of vaccines' effectiveness on the European corporate green bond market. Our results suggest several key points that are relevant to both investors and issuers under the unprecedented conditions created by the pandemic.

Commonality in Credit Spread Changes: Dealer Inventory and Intermediary Distress

Abstract Two intermediary-based factors—a corporate bond dealer inventory measure and a broad intermediary distress measure—explain more than 40$\%$ of the puzzling common variation in credit spread changes beyond canonical structural factors. A simple intermediary-based model with partial market segmentation accounts for intermediary factors’ explanatory power and delivers three further implications with empirical support. First, whereas bond sorts on risk-related variables produce monotonic loading patterns on intermediary factors, non-risk-related sorts produce no pattern. Second, dealer inventory comoves with corporate-credit assets only, whereas intermediary distress comoves with both corporate-credit and non-corporate-credit assets. Third, dealers’ inventory responds to (instrumented) bond sales by institutional investors.

Accounting downside risk measures and credit spreads

PurposeThis study aims to examine the association between predictive accounting downside risk measures and changes in credit spreads. Building upon the earnings downside risk (EDR) measure developed in prior literature, this paper introduces cash flow downside risk (CFDR).Design/methodology/approachThis study modifies an existing empirical framework (root lower partial moment) to calculate CFDR and applies it to a sample of firms between 2002 and 2013 for which credit default swap data are available.FindingsAfter validating the measure, this study identifies a positive association between CFDR and changes in credit spreads. This paper further shows the association between CFDR and credit spread changes is stronger than that between EDR and credit spread changes. Financial stability moderates the relationship between CFDR and credit spreads.Originality/valueThis study proposes a novel measure of accounting downside risk, CFDR and demonstrates a negative association between this measure and future cash flow and a positive association between this measure and future credit spreads.

Oil price shocks and credit spread: Structural effect and dynamic spillover

This study analyzes the heterogeneous response of U.S. credit spread to global oil price shocks by building an extended structural vector autoregressive model (SVAR), which can distinguish among the U.S. and non-US oil supply shocks, aggregated demand shocks and oil market-specific demand shocks behind the real oil prices. Meanwhile, a spillover index model developed by Diebold and Yilmaz (2012) (hereafter D.Y. (2012)) is used to estimate the link between oil price shocks and the U.S. credit spread over time. The results show that (i) the credit spread does not respond to global oil supply shocks and non-US oil supply shocks, but has a negative reaction to the U.S. oil supply shocks, aggregate demand shocks, and oil-market-specific demand shocks. (ii) There exists a close connectedness between oil price shocks and the U.S. credit spread, and the link fluctuates cyclically and relates to the economic cycle and the U.S. shale oil revolution. (iii) The spillover from different oil price shocks to the U.S. credit spread shows significant heterogeneity over time. Our findings suggest that policymakers and investors can better track the U.S. credit spread changes using oil price information.

Corporate bond market reactions to quantitative easing during the COVID-19 pandemic.

Using transaction data from the first half of 2020, we examine the reaction of corporate credit spreads to the Federal Reserve’s monetary policy announcements. We find evidence that the bond markets are segmented across credit ratings, which led to different initial reactions across bonds with different credit ratings but spread across various sectors of corporate bonds over the longer event window. To quantify the default risk channel of quantitative easing, we apply the variance decomposition approach to credit spreads and find that a significant fraction of credit spread changes indeed correspond to reduced default risk caused by the corporate bond purchase program. In contrast, we only find mixed evidence for the liquidity channel driving the market reaction.

Asymmetry in Liquidity Pricing in the Cross-Section and Time Series of Corporate Bond Returns

Asymmetry in price pressure from seller versus buyer-initiated transactions is a valuable measure of downside liquidity for corporate bonds. Larger relative price impact of sellers can exacerbate market downturns in flight-to-liquidity environments. While the evidence of an illiquidity characteristics premium in the cross-section of corporate bonds is mixed, aggregate liquidity asymmetry has high explanatory power for the time series of market returns. Its statistical and economic significance justify it as credible asset pricing factor. Average market-wide liquidity asymmetry comoves with interest rate and credit spread changes, investor sentiment, funding liquidity, dealer inventory, ETF flows and post-crisis regulatory change.

CDS Returns

We show that existing metrics of CDS returns poorly approximate cash flow-based CDS returns. Given the complexities involved in computing CDS returns correctly, we provide a simple closed-form approximation that bears a correlation of no less than 99% with the true return series. Our work emphasizes the importance of distinguishing between changes in credit spreads and CDS returns. In addition, it highlights the need to rely on true CDS return metrics to evaluate investment strategies and predictive return regressions that involve the selling or buying of CDS contracts.

Policy uncertainty and corporate credit spreads

We find a significant positive relation between changes in policy uncertainty and changes in credit spreads. Macroeconomic conditions, including general uncertainty, do not explain this result, which also holds when we use instrumental variables to address endogeneity issues. The impact of policy uncertainty is greater for firms that operate in regulation-intensive industries, face high tax rates, or are dependent on government spending. It is also stronger for firms that engage in political activities or rely on external financing. We conclude that policy uncertainty has a significant effect on firms’ borrowing costs, with exposure to government policies representing an important channel.

Credit Spreads, Leverage and Volatility: a Cointegration Approach

This work documents the existence of a cointegration relationship between credit spreads, leverage and equity volatility for a large set of US companies. It is shown that accounting for the long-run equilibrium dynamic between these variables is essential to correctly explain credit spread changes. Using a novel structural model in which equity is modelled as a compound option on the firm's assets, a new methodology for estimating the unobservable market value of the firm's assets and volatility is developed. The proposed model allows to significantly reduce the pricing errors in predicting credit spreads when compared with several structural models. In terms of correlation analysis, it is shown that not accounting for the long-run equilibrium equation embedded in an Error Correction Mechanism (ECM) results into a misspesification problem when regressing a set of explanatory variables onto the spread changes. Once credit spreads, leverage and volatility are correctly modelled, thus allowing for a long-run equilibrium, the fit of the regressions sensibly increases if compared to the results of previous research. It is further shown that most of the cross-sectional variation of the spreads appears to be more driven by firm-specific characteristics rather than systematic factors.

The Corporate Bond Market Reaction to the COVID-19 Crisis

Using transaction data from the first half of 2020, we examine the reaction of corporate credit spreads to the Federal Reserve's monetary policy announcements. We find evidence that the bond markets are segmented across credit ratings, which led to different initial reactions across bonds with different credit ratings but spread across various sectors of corporate bonds over the longer event window. To quantify the default risk channel of quantitative easing, we apply the variance decomposition approach to credit spreads and find that a significant fraction of credit spread changes indeed corresponds to reduced default risk caused by the corporate bond purchase program. In contrast, we only find mixed evidence for the liquidity channel driving the market reaction.

Aggregate insider trading and the prediction of corporate credit spread changes

This paper shows that equity-based aggregate insider trading predicts future changes in US corporate credit spreads. Results suggest that the closer insiders are involved in daily business activities, the greater the predictive power of those insiders’ transactions is. In line with the literature, we reason and find that closely involved insiders are better at gauging future changes in cash flow realizations eventually affecting a firm’s default risk, because these insiders have greater access to in-firm information. The predictive power of aggregate insider trading doubles each time we increase the forecast horizon and each time when gradually increasing the level of default risk from BBB to CCC spreads. For the standard BBB–AAA spread, a univariate model explains up to 52% in annual credit spread change variation and is economically meaningful. An increase in one standard deviation in aggregate insider trading translates into a decrease of up to 72% of the standard deviation of annual credit spread changes. The predictive power of aggregate insider trading is neither just driven by the 2007/08 financial crisis, nor only by information conveyed from net purchasing or net selling insiders. Our results recommend portfolio and risk managers to take aggregate inside information and the heterogeneity among insiders into account when assessing future aggregate default risk.

Improving Evaluation Techniques for Credit Risky Securities

The present value of bonds and loans is commonly calculated as a sum of contractual cash flows discounted by default-free interest rates added by an appropriate credit spread. The evidence that investors require higher nominal returns for credit risky securities is commonly invoked as the main argument in support of this approach. However, although it is widely applied in the common practice, it remains a quick-fix solution for several reasons. First, it does not properly account for the probability of collecting contractual cash flows. Second, it leads to the wrong conclusion that the present value of financial instruments remains unchanged when fluctuations of risk-free rates are perfectly balanced by opposite changes in the relevant credit spread. Third, it makes the more risky bonds appear more profitable because credit spread, when included into discount rates, inevitably leads to calculate internal rates of return inversely correlated to the borrower’s creditworthiness. This work shows how refined cash-flow mapping techniques may be used in order to design a double-leg approach which properly accounts for expected credit losses and credit survival probabilities. This approach leads to an accurate evaluation of traded bonds on the sole basis of market information. In addition, it defines complete non-arbitrage conditions and overcomes the flaws of the most common pricing models for credit risky securities.

Spurious cross-sectional dependence in credit spread changes

In order to understand the lingering credit risk puzzle and the apparent segmentation of the stock market from credit markets, we need to be able to assess the strength of the cross-sectional dependence in credit spreads. This turns out to be a non-trivial task due to the extreme data sparsity that is typical for any panel of credit spreads that is extracted from corporate bond transactions. The problem of data sparsity has led to some erroneous conclusions in the literature, including inferences that have been drawn from spurious cross-sectional dependence in credit spread changes. Understanding the pitfalls leads to improved estimation of the latent factor in credit spread changes and its characteristics.

Commonality in Credit Spread Changes: Dealer Inventory and Intermediary Distress

Two intermediary-based factors - a broad financial distress measure and a dealer corporate bond inventory measure - explain about 50% of the puzzling common variation of credit spread changes beyond canonical structural factors. A simple model, in which intermediaries facing margin constraints absorb supply of assets from customers, accounts for the documented explanatory power and delivers further implications with empirical support. First, whereas bond sorts on margin-related variables (credit rating and leverage) produce monotonic patterns in loadings on intermediary factors, non-margin-related sorts produce no pattern. Second, dealer inventory co-moves with corporate-credit assets only, whereas intermediary distress co-moves even with non-corporate-credit assets. Third, dealers' inventory increases, and bond prices decline, in response to instrumented bond sales by institutional investors, using severe downgrades (fallen angels'') and disaster-related insurance losses as IVs.

Commonality in Credit Spread Changes: Dealer Inventory and Intermediary Distress

Commonality in Credit Spread Changes: Dealer Inventory and Intermediary Distress

Contingent Claims and Hedging of Credit Risk with Equity Options

We introduce a novel methodology to hedge changes in the market values of credit exposures using equity put options. Our new hedge ratios are derived from the application of contingent-claims valuation and are fundamentally different from existing hedging methods aimed at neutralizing the loss following the occurrence of a credit event. We provide evidence that the theoretical hedge ratios are in line with the empirical sensitivities of credit spread changes to put option returns and that, relative to the latter, reduce volatility by a further 15% in an out-of-sample setting including a portfolio of North American firms. Based on in-sample estimates, hedging with options reduces portfolio volatility by an additional 13% relative to hedging with equity. We show that option hedge ratios capture option-specific credit exposure related to the VIX index and the default spread, which is unaccounted for by Merton (1974)'s equity hedge ratios alone. These findings shed new light on the puzzling weak relation between equity and credit returns reported in previous studies and suggest that the predictions of Merton's structural model can be enhanced by combining equity-specific with option-specific information.

What Moves the Correlation between Equity and CDS Markets

We document substantial correlation dynamics between equity returns and CDS spread changes at the firm level, which is critical for cross-market hedging and arbitrage strategies. Using the implied cost of capital approach, we decompose the unexpected equity returns into cash flow and discount rate news, and examine the impact of the shocks on the correlations. We find discount rate news explains the majority fraction. However, at longer horizons and in periods when cash flow news is more negatively related with CDS spread changes, the cross-market integration is stronger. In addition, firms with more cash flow news exhibit stronger correlations between equity returns and credit spread changes, and the structural model can explain more variations of credit spread changes in these firms.