Corporate Yield Curves Research Articles

The impact of ESG rating on corporate bond yields

This paper is to investigate whether markets assess corporate bonds riskier if their issuers have lower ESG (Environmental Social Governance) scores. For the study we used the corporate yield curves of Refinitiv further segmented by credit rating. The added risk of the ESG factor was measured in the time horizon of 2015 to 2020. It has turned out that in the USA in the group of the best debtor companies by Moody’s investors expected companies with the lowest ESG scores to provide a 35 basis point higher risk premium compared to their counterparts with the highest ESG scores. This statement is also valid for the E, S and G-rating separately. In line with another trend, the riskier your credit rating category, the lower is the risk premium caused by the lack of responsible management.

A macro–financial analysis of the corporate bond market

We assess the contribution of economic and financial factors in the determination of euro area corporate bond spreads over the period 2001–2015. The proposed multi-market, no-arbitrage affine term structure model is based on the methodology proposed by Dewachter et al. (J Bank Finance 50:308–325, 2015). We model jointly the ‘risk-free curve’, measured by overnight index swap (OIS) rates, and the corporate yield curves for two rating classes (A and BBB). The model includes four spanned and six unspanned factors. We find that, in general, both economic (real activity and inflation) and financial factors (proxying risk aversion, flight to liquidity and general financial market stress) play a significant role in the determination of the spanned factors and hence in the dynamics of the risk-free yield curve and corporate bond spreads. Across the risk-free OIS curve, macroeconomic and financial factors are each responsible on average for explaining 30 and 65% of yield variation, respectively. For A- and BBB-rated corporate debt, the selected financial variables explain on average 50% of the variation in corporate spreads during the last decade.

A Macro-financial Analysis of the Corporate Bond Market

We assess the contribution of economic and financial factors in the determination of euro area corporate bond spreads over the period 2001-2015. The proposed multi-market, no-arbitrage affine term structure model is based on the methodology proposed by Dewachter, Iania, Lyrio, and Perea (2015). We model jointly the ‘risk-free curve’, measured by overnight index swap (OIS) rates, and the corporate yield curves for two rating classes (A and BBB). The model includes four spanned and six unspanned factors. We find that, in general, both economic (real activity and inflation) and financial factors (proxying risk aversion, flight to liquidity and general financial market stress) play a significant role in the determination of the spanned factors and hence in the dynamics of the risk-free yield curve and corporate bond spreads. Across the risk-free OIS curve, macroeconomic and financial factors are each responsible on average for explaining 30 and 65 percent of yield variation, respectively. For A-and BBB-rated corporate debt, the selected financial variables explain on average 50 percent of the variation in corporate spreads during the last decade.

The impact of monetary policy on corporate bonds in India

We analyse the impact of monetary policy on the shape of the corporate yield curve and credit spread using a macro-finance approach. Instead of estimating the latent factors from the data on corporate bonds, we use market proxies of level, slope and curvature of the corporate yield curve and credit spread. The results demonstrate that while monetary policy has the dominant impact among macroeconomic variables on the entire term structure, it is particularly strong at the short end and on credit spreads. Changes in credit spreads, in turn, also influence monetary policy. The results are robust to alternative identification schemes and have important policy implications for further development of the corporate bond market, particularly in emerging market economies.

Forecasting growth and stock performance using government and corporate yield curves: Evidence from the European and Asian markets

Past research has shown that the government yield curve and credit spreads can predict future macroeconomic parameters such as the growth rate. However, it has focused mostly on the US government yield curve. In this study we extend the existing notion by using both government and corporate yield curves to predict economic growth and stock market behavior in three main markets outside the US.The results we obtained from the British, European and Japanese markets reveal that government and corporate yield curves can indeed predict future economic growth and stock market trends.

Corporate yield curves as predictors of future economic and financial indicators

The government yield curve is known for its ability to predict the future growth rate of the economy. Later studies showed that credit spreads can assist in predicting macroeconomic behaviour as well. We extend this notion by utilizing corporate yield curves and demonstrating that corporate yield curve spreads can predict future economic growth, the future state of the economy and stock market behaviour. In addition, our sample covers the most recent data available, and it also includes the crash year of 2008 and the recovery period following it. Our results reveal a trade-off effect between the government yield curve, which is a better predictor for long-term forecasting, and the corporate yield curves, which are better predictors for short-term predictions. In addition, we show that both the government and corporate yield curves are more effective in predicting negative rather than positive economic changes.

Parsimonious modeling and forecasting of corporate yield curve

AbstractThis paper investigates the sensitivity of out‐of‐sample forecasting performance over a span of different parameters of l in the dynamic Nelson–Siegel three‐factor AR(1) model. First, we find that the ad hoc selection of l is not optimal. Second, we find a substantial difference in factor dynamics between investment‐grade and speculative‐grade corporate bonds from 1994:12 to 2006: 4. Third, we suggest that the three‐factor model is sufficient to explain the main variations of corporate yield changes. Finally, the parsimonious Nelson–Siegel three‐factor AR(1) model remains competitive in the out‐of‐sample forecasting of corporate yields. Copyright © 2008 John Wiley & Sons, Ltd.

Multiscale Intensity Models for Single Name Credit Derivatives

We study the pricing of defaultable derivatives, such as bonds, bond options, and credit default swaps in the reduced form framework of intensity‐based models. We use regular and singular perturbation expansions on the intensity of default from which we derive approximations for the pricing functions of these derivatives. In particular, we assume an Ornstein‐Uhlenbeck process for the interest rate, and a two‐factor diffusion model for the intensity of default. The approximation allows for computational efficiency in calibrating the model. Finally, empirical evidence on the existence of multiple scales is presented by the calibration of the model on corporate yield curves. Work partially supported by NSF grants DMS‐0306357 and DMS‐0456195.

Multiscale Intensity Models for Single Name Credit Derivatives

We study the pricing of defaultable derivatives, such as bonds, bond options, and credit default swaps in the reduced form framework of intensity-based models. We use regular and singular perturbation expansions on the intensity of default from which we derive approximations for the pricing functions of these derivatives. In particular, we assume an Ornstein-Uhlenbeck process for the interest rate, and a two-factor diffusion model for the intensity of default. The approximation allows for computational efficiency in calibrating the model. Finally, empirical evidence on the existence of multiple scales is presented by the calibration of the model on corporate yield curves.

FRS17 and the Sterling Double A Corporate Yield Curve

Abstract: We argue that the appropriate discount rate used to report defined benefit pension plan liabilities in the financial statements is a yield derived from an estimate of a double A corporate yield curve. We show that parsimonious yield curve techniques are easily applicable to the sterling double A corporate bond market. Moreover, we find that with a careful selection of the data an objective and reliable yield curve can be obtained. In all we find that using a yield from a sterling double A corporate yield curve to obtain the value of defined benefit pension plan liabilities is a feasible alternative to the current recommendations of FRS17.

Estimating Corporate Yield Curves

Tests of arbitrage-free pricing models show that we can expect less reliable corporate yield curve estimates than Treasury yield curve estimates. An examination of the structure of errors produced by common statistical yield curve models indicates that even with careful data selection, significant liquidity and tax-induced errors remain. It is a welcome result that the extent of the errors due to liquidity and tax effects is modest. Moreover, pooling bonds by broad rating category produces no significant deterioration in yield curve estimates.