High-yield Corporate Bonds Research Articles

The advantages of CBOE credit VIXs for corporate bond investors in North America: A sectoral analysis

This paper examines the safe-haven role of the recently introduced CBOE credit VIXs for investment-grade and high-yield corporate bonds, at both aggregate and sectoral levels. Using a time-varying quantile-based framework and daily data from June 5, 2014 to December 10, 2023, the safe-haven role of credit VIX is confirmed irrespective of bond sector. The safe-haven property of credit VIX is pronounced for high-yield bonds which embed a high credit risk-premium. This result stands when taking into account interest rate volatility, as measured by the MOVE index. A time-varying analysis shows the persistence of credit VIX as a safe-haven for all bond sectors after the COVID-19 pandemic and during a high US interest-rate regime. Corporate bond investors and traders can use these findings to refine their investment and trading decisions and offset credit risk during both normal and turbulent periods.

Hedging investment-grade and high-yield bonds with credit VIX

The existing literature lacks evidence of the ability of newly introduced credit VIXs to hedge investment-grade and high-yield corporate bond indices. A dynamic hedging analysis shows that credit VIX is an effective hedge for its corresponding bond index, but the hedging ability of high-yield credit VIX for high-yield bonds is more stable and effective than that of investment-grade credit VIX for investment-grade bonds. A regression analysis indicates that conditional correlations decreased during the Fed tightening cycle, resulting in more hedging effectiveness for both credit VIXs; whereas, the hedging effectiveness of high-yield bonds improved around the peak of the COVID-19 outbreak.

Corporate carbon emissions data for equity and bond portfolios

PurposeTo better understand the impact of choosing a carbon data provider for the estimated portfolio emissions across four asset classes. This is important, as prior literature has suggested that Environmental, Social and Governance scores across providers have low correlation.Design/methodology/approachThe authors compare carbon data from four data providers for developed and emerging equity markets and investment grade and high-yield corporate bond markets.FindingsData on scope 1 and scope 2 is similar across the four data providers, but for scope 3 differences can be substantial. Carbon emissions data has become more consistent across providers over time.Research limitations/implicationsThe authors examine the impact of different carbon data providers at the asset class level. Portfolios that invest only in a subset of the asset class may be affected differently. Because “true” carbon emissions are not known, the authors cannot investigate which provider has the most accurate carbon data.Practical implicationsThe impact of choosing a carbon data provider is limited for scope 1 and scope 2 data for equity markets. Differences are larger for corporate bonds and scope 3 emissions.Originality/valueThe authors compare carbon accounting metrics on scopes 1, 2 and 3 of corporate greenhouse gas emissions carbon data from multiple providers for developed and emerging equity and investment grade and high yield investment portfolios. Moreover, the authors show the impact of filling missing data points, which is especially relevant for corporate bond markets, where data coverage tends to be lower.

The Announcement Effect of Monetary Policy on the Corporate Bond Markets

This study investigates the impact of the central bank’s monetary policy announcements on the perceptions of yield spread in corporate bond markets under the event of extreme events. These results highlight that the coronavirus pandemic has caused a market panic in the global economy. This caused investors to withdraw their money from bond markets, which caused a liquidity crisis in bond markets. The Fed announcements caused statistically significant tightening on US and global investment grades and high-yield corporate bond spreads. The Euro investment grade and high-yield corporate bond spread narrowed when the Fed took additional actions to provide more funds and expanded the buying scope to support market liquidity. These results suggest that forward guidance that emphasizes the Fed’s monetary policy causes stronger information effects.

Foreign-law premium for European high-yield corporate bonds

We provide novel evidence on importance of governing laws for returns of high-yield corporate bonds. Around 29% of sample bonds are governed by laws which are different from laws of issuers’ countries of domicile. The most popular foreign law is English, followed by New York, and German laws. The foreign-law bonds exhibit higher excess returns than their domestic-law counterparts. The effect of foreign law on excess returns increases with an increase in downside risk. This conditional effect is particularly evident for English foreign governing law. The results are robust to controls for endogeneity concerns, alternative proxies, and model specifications.

Research on the Credit of High-Yield Corporate Bonds in My country Under Machine Learning

As an important part of the bond market, corporate bonds have the characteristics of high yield and high risk. This work aims to design an index system of influencing factors through the literature research on the current situation of corporate bond defaults, credit risk related theories and credit risk model theories, using corporate bond default data, and integrate machine learning models and KMV optimization models to construct the credit risk early warning model of my country's high-yield corporate bonds. Investors, regulators and other relevant parties can use this early warning model to more effectively pay attention to the potential default risk of corporate bonds, and carry out corresponding credit risk control to ensure the stable development of the bond market.

Occam’s Razor for Bond Trade Costs

Inability to accurately project transaction cost is one of the main drags on alpha and performance for bond investors. We introduce a framework for bond trade cost analysis that reflects bond characteristics as well as order information. This framework leverages historical and real-time data to deliver solid explanatory power. The authors goal is to help buy-side traders and dealers to build liquidity trees, while assisting portfolio managers to make investment decisions that include trade costs. We lean on 20 years of experience modeling transaction cost for equities, as well as intimate knowledge of the bond market microstructure. Our work covers investment grade and high yield corporate bonds, issued in USD, EUR, and GBP, as well as government bonds in developed and emerging markets globally.

The clientele effect around the turn of the year: evidence from the bond markets

Studying the returns of US Treasury, corporate, and municipal (muni) bonds at the index level over 2004-2020, I find a strong turn-of-the-year effect – low December returns and high January returns – in the high-yield muni index. The investment-grade muni index exhibits a similar but weaker effect. High-yield munis is the only class whose December returns are negatively correlated with year-to-date yield changes. Dominance of highly tax-sensitive households who engage in tax-loss selling, combined with opaqueness, low liquidity, and a small role of ETFs in munis make it difficult to arbitrage away the December price decreases. The investment-grade and high-yield corporate bond indices have abnormally high December returns in years with capital losses. The high-yield corporate index also has abnormally high December returns even in years without capital losses. It represents a change from the findings of prior research and suggests that corporate bond investors exhibit contrarian tendencies in December.

COVID‐19 and ESG preferences: Corporate bonds versus equities

I examine investors' within ESG investment preferences during the COVID‐19 pandemic by investigating the return spillover effects across the three different corporate bonds and equities‐based investment strategies. Investors prefer making investments in ESG leaders in the investment‐grade corporate bond market over ESG leaders in the equity and high yield corporate bond markets during times of uncertainty. It suggests that capital flows away from high yield corporate bond and equity markets to the investment‐grade corporate bond market. Investors find refuge in firms with relatively higher ESG ratings and creditworthiness in the fixed income market over the equity market during crisis periods.

Interdependence between Green Financial Instruments and Major Conventional Assets: A Wavelet-Based Network Analysis

This paper examines the interdependence between green financial instruments, represented by green bonds and green stocks, and a set of major conventional assets, such as Treasury, investment-grade and high-yield corporate bonds, general stocks, crude oil, and gold. To that end, a novel wavelet-based network approach that allows for assessing the degree of interconnection between green financial products and traditional asset classes across different investment horizons is applied. The empirical results show that green bonds are tightly linked to Treasury and investment-grade corporate bonds, while green stocks are strongly tied to general stocks, regardless of the specific time period and investment horizon considered. However, despite their common climate-friendly nature, there is no a remarkable association between green bonds and green stocks. This means that these green investments constitute basically two independent asset classes, with a distinct risk-return profile and aimed at a different type of investor. Furthermore, green financial products have a weak connection with high-yield corporate bonds and crude oil. These findings can have important implications for investors and policy makers in terms of investment decision, hedging strategies, and sustainability and energy policies.

Risk Mitigation and Return Resilience for High Yield Bond ETFs with ESG Components

The objective of this study is to investigate the effects of ESG components on financial products by using high yield bond exchange traded funds (ETFs). For the objective, we propose a new price correlation and volatility model between an existing financial market such as conventional high yield bond ETFs and a new financial market such as ESG high yield bond ETFs, in which the former affects the latter. Empirical studies show that ESG factors have hedging effects to the downside risk of conventional high yield bond ETF prices in the Covid-19 shocks of March, 2020 from the positive impacts of conventional high yield bond ETF prices on the correlations with ESG ones by using ESG high yield corporate bond ETFs of the Nuveen and the iShares compared with a conventional high yield bond ETF of the SPDR Bloomberg Barclays. Additionally, high yield bond ETFs that take ESG into account are observed to reduce risk compared to a conventional high yield bond ETF. Results also show that ESG high yield bond ETF returns are higher than conventional high yield bond ETF returns in the Covid-19 shocks. The implication from these results is that the value of ESG investing lies in the mitigation of risks and the resilience of expected returns.

What Drove Recent Trends in Corporate Bonds and Loans Usage?

<ns2:p>U.S. nonfinancial business debt increased substantially in recent years in both absolute and relative terms and is now near its record high. Figure 1 shows that most of this increase was due to significant growth in investment-grade (IG) corporate bonds and institutional leveraged loans, while high-yield (HY) corporate bonds and C&I loans largely remained steady.</ns2:p>

Stock return predictability in the time of COVID-19

We examine predictive ability of a relatively large number of variables from currency, bond and commodity markets for US stock returns during the COVID-19 crisis. As a novel contribution, we estimate robust Lasso predictive regressions with Cauchy errors, consistent with extreme movements and nonlinearities in the market. Both investment grade and high yield corporate bonds emerge as significant predictors of US stock returns in the period, lending support to recent policy decisions by the Federal Reserve.

Bond Mutual Fund Flows, Fund Liquidity, and Broker-Dealer Inventories

Some financial supervisors worry that liquidity transformation within the “shadow banking” sector might threaten financial stability. For example, a mutual fund promising overnight liquidity based on illiquid assets (such as corporate bonds) runs the risk of needing to “fire sale” some assets, with potentially deleterious external effects. One protection against this possibility would be a broker-dealer sector that stands ready to stabilize prices by buying (or selling) for its own inventory. I evaluate the extent to which bond mutual funds’ flows are reflected in broker-dealers’ inventories. Although brokers generally trade in the same direction as the mutual funds, high-yield corporate bonds present an exception. Flows out of high-yield bond funds are associated with a significant increase in dealers’ high-yield bond inventories. These results provide further information about how various types of bond mutual funds handle liquidity demands.

A three-stage model of the volatility-volume relation in the Junk bond market during the 2007-2008 financial crisis

PurposeThe purpose of this paper is to examine the joint dynamics of volatility–volume relation in the high-yield (junk) corporate bond market during the 2007–2008 financial crisis.Design/methodology/approachThe author proposes a new empirical model of three-stage equations to better estimate the volume–volatility relation that helps in alleviating three econometrical problems. In Stage 1, the author estimates the fitted values of trading volume using a censored regression model, to alleviate the truncation problems of using Transaction Reporting and Compliance Engine data. In Stage 2, the author calculates the fitted values of bond return volatility using asymmetric Sign-GARCH model, to control for the asymmetric volatility in return series. In Stage 3, the author uses the fitted values of trading volume from the censored regression model (Stage 1) and the fitted values of return volatility from the GARCH model (Stage 2), to better alleviate the endogeneity problems between both variables.FindingsThe central finding is that conclusions about the statistical significance and the direction of the volume–volatility relationship in the junk bond market are dependent on the econometric methodology used.Originality/valueFrom a practitioner perspective, it is important for professional traders holding positions in fixed income securities in their trading accounts to be aware of their asymmetric time-varying volume–volatility shifting trends. Such knowledge helps traders diversify their positions and manage their portfolios more appropriately.

Network connectedness of green bonds and asset classes

We identify network connectedness between green bonds and different asset classes over different investment horizons in the EU and US asset markets. We first focus on dynamic correlations between green bond and asset class price changes in different time scales on the basis of wavelet coherence. We then identify network connectedness by decomposing time series into different frequency components, in each of which we evaluate connectedness on the basis of the error variance decomposition of a multivariate vector autoregressive model. Our empirical evidence reveals strong connectedness between green bonds and treasury and corporate bonds in the short and long run and in both the EU and the USA, with green bonds receiving sizeable spillovers from treasury and corporate bond prices and transmitting negligible effects. Likewise, we find that green bonds are weakly connected with high-yield corporate bond, stock and energy assets over different time scales. These findings have implications for green bond investors regarding portfolio design and hedging decisions, and for the channelling of financial flows to economic activities that are consistent with a decarbonized economy.

The Market Risk Premium for Unsecured Consumer Credit Risk

We use the prices of credit card asset-backed securities to study the market risk premium associated with unsecured consumer credit risk. The consumer credit risk premium has historically been comparable to high yield corporate bond spreads, but has increased dramatically since the financial crisis. We find evidence that this increase is primarily due to balance-sheet costs imposed by recent changes in regulatory capital requirements which have effectively placed credit card securitizations back onto issuer balance sheets. These changes in capital regulation may have added hundreds of basis points to the cost of unsecured household credit. Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

A Three-Stage Model of the Volume-Volatility Relation in the Junk Bond Market during the 2007–2008 Financial Crisis

This article examines the joint dynamics of volatility-volume relation in the high-yield (junk) corporate bond market during the 2007-2008 financial crisis. I propose a new empirical model of three-stage equations to better estimate the volatility-volume relation that helps in alleviating econometric problems. My central finding is that different methodologies can easily lead to different inferences about the volatility-volume relation in the junk bond market. More specifically, conclusions about the statistical significance and/or the direction of the association between both variables is dependent on the econometric methodology used. From a practitioner perspective, it is important for professional traders holding positions in fixed income securities in their trading accounts to be aware of their asymmetric time-varying volatility-volume shifting trends. Such knowledge helps traders diversify their positions and manage their portfolios more appropriately.

Price connectedness between green bond and financial markets

We study price connectedness between the green bond and financial markets using a structural vector autoregressive (VAR) model that captures direct and indirect transmission of financial shocks across markets. Using heteroskedasticity to identify the structural VAR model parameters, our empirical findings reveal that the green bond market is closely linked to the fixed-income and currency markets, receiving sizeable price spillovers from those markets and transmitting negligible reverse effects. We also show that, in contrast, the green bond market is weakly tied to the stock, energy and high-yield corporate bond markets. These findings have implications in terms of portfolio and risk management decisions for environmentally aware investors holding positions in green bonds.

Resilience of Trading Networks: Evidence from the Sterling Corporate Bond Market

We study the network structure and resilience of the sterling investment-grade and high-yield corporate bond markets. Using proprietary, transaction-level data, first we analyse the key properties of the trading networks in these markets. We find that the trading networks exhibit a core-periphery structure where a large number of non-dealers trade with a small number of dealers. Consistent with dealer behaviour in the primary market, we find that trading activity is particularly concentrated for newly issued bonds, where the top three dealers account for 45% of trading volume. Second, we test the resilience of these markets to the failure or paralysis of a key dealer, or to bond rating downgrades. We find that whilst the network structure has been broadly stable and the market broadly resilient around bond downgrades over our 2012–2017 sample period, the reliance on a small number of participants makes the trading network somewhat fragile to the withdrawal of a few key dealers from the market.