Bond risk premia and realized jump risk

Wright, Jonathan H.; Zhou, Hao

doi:10.1016/j.jbankfin.2009.06.010

Cited by 95 publications

(40 citation statements)

References 37 publications

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“…One strand of research relates such variations to forward spreads (Fama and Bliss, 1987;Fama, 2006), yield spreads (Keim and Stambaugh, 1986;Campbell and Shiller, 1991), and forward rates (Cochrane and Piazzesi, 2005;Dahlquist and Hasseltoft, 2013;Zhu, 2015), whereas more recent studies link the predictable component to factors whose variations lie outside the span of current yields. Existing research within this strand has uncovered a wide array of factors including jump risk (Wright and Zhou, 2009), option prices (Almeida, Graveline, and Joslin, 2011), and macroeconomic variables (Ilmanen, 1995;Moench, 2008;Cooper and Priestley, 2009;Ludvigson and Ng, 2009;Wright, 2011;Favero, Niu, and Sala, 2012;Joslin, Priebsch, and Singleton, 2014;Zhou and Zhu, 2015).While existing studies mainly rely on information in the current term structure and business environment to explain variations in the predictable component of bond risk premia, our study takes a forward-looking perspective by studying the link between expected business conditions and bond risk premia using survey forecasts from the Survey of Professional Forecasters (SPF). Albeit empirical studies frequently conclude that macroeconomic fundamentals carry information about bond risk premia not already captured by the yield curve, they rarely account for issues with publication lags and data revisions in macroeconomic time series.…”

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confidence: 99%

Expected Business Conditions and Bond Risk Premia

Eriksen¹

2017

J. Financ. Quant. Anal.

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This paper studies the predictability of bond risk premia by means of expectations to future business conditions using survey forecasts from the Survey of Professional Forecasters. We show that expected business conditions consistently affect excess bond returns and that the inclusion of expected business conditions in standard predictive regressions improve forecast performance relative to models using information derived from the current term structure or macroeconomic variables. The results are confirmed in a real-time out-of-sample exercise, where the predictive accuracy of the models is evaluated both statistically and from the perspective of a mean-variance investor that trades in the bond market.Keywords: Bond risk premia, expected business conditions, predictability, economic value, expectations hypothesis, time-varying risk premia JEL Classification: E43, E44, E47, G11, G12. IntroductionThere is mounting evidence that the risk premia required by investors for holding Treasury bonds contain a time-varying and predictable component. One strand of research relates such variations to forward spreads (Fama and Bliss, 1987;Fama, 2006), yield spreads (Keim and Stambaugh, 1986;Campbell and Shiller, 1991), and forward rates (Cochrane and Piazzesi, 2005;Dahlquist and Hasseltoft, 2013;Zhu, 2015), whereas more recent studies link the predictable component to factors whose variations lie outside the span of current yields. Existing research within this strand has uncovered a wide array of factors including jump risk (Wright and Zhou, 2009), option prices (Almeida, Graveline, and Joslin, 2011), and macroeconomic variables (Ilmanen, 1995;Moench, 2008;Cooper and Priestley, 2009;Ludvigson and Ng, 2009;Wright, 2011;Favero, Niu, and Sala, 2012;Joslin, Priebsch, and Singleton, 2014;Zhou and Zhu, 2015).While existing studies mainly rely on information in the current term structure and business environment to explain variations in the predictable component of bond risk premia, our study takes a forward-looking perspective by studying the link between expected business conditions and bond risk premia using survey forecasts from the Survey of Professional Forecasters (SPF). Albeit empirical studies frequently conclude that macroeconomic fundamentals carry information about bond risk premia not already captured by the yield curve, they rarely account for issues with publication lags and data revisions in macroeconomic time series. As recently demonstrated by Ghysels, Horan, and Moench (2014), such features may drive a wedge between the factor spaces spanned by latent common factors extracted from a panel of revised and non-revised data, respectively, implying that a sizable fraction of the predictability documented by Ludvigson and Ng (2009) may largely be driven by revision and publication lag components that are unavailable to an investor in real-time. Survey forecasts, as a result, provide an ideal data source for studying the predictability of bond risk premia as they are model-free, available in real-time, and not...

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confidence: 99%

Expected Business Conditions and Bond Risk Premia

Eriksen¹

2017

J. Financ. Quant. Anal.

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“…The importance of jumps as an explanatory variable has been convincingly illustrated in Tauchen and Zhou (2011), Wright andZhang et al (2009). Tauchen and Zhou (2011) show that the jump volatility (that is, the volatility ofĴ t defined in Eq.…”

Section: Regression Analysismentioning

confidence: 87%

“…This assumption is clearly not satisfied during the GFC. Another interesting contribution is that of Wright and Zhou (2009) who illustrate the importance of the mean jump size of the 30-year Treasury bond futures to explain the monthly excess return on holding of an n−month maturity bond (with n = 2; 24; 36; 48; 60). The mean value is computed using a 24-month rolling window, thus imposing a constraint on the sample size when applying this methodology.…”

Section: Accepted M Manuscriptmentioning

confidence: 99%

Explaining Credit Default Swap Spreads by Means of Realized Jumps and Volatilities in the Energy Market

2015

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This paper studies the relationship between credit default swap (CDS) spreads for the Energy sector and oil futures dynamics. Using data on light sweet crude oil futures from 2004 to 2013, which contains a crisis period, we examine the importance of volatility and jumps extracted from the futures in explaining CDS spread changes. The analysis is performed at an index level and by rating group; as well as for the pre-crisis, crisis and post-crisis periods. Our findings are consistent with Merton's theoretical framework. At an index level, futures jumps are important when explaining CDS spread changes, with negative jumps having higher impact during the crisis. The continuous volatility part is significant and positive, indicating that futures volatility conveys relevant information for the CDS market. As for the analysis per rating group, negative jumps have an increasing importance as the credit rating deteriorates and during the crisis period, while the results for positive jumps and futures volatility are mixed. Overall, the relation between the CDS market and the futures market is stronger during volatile periods and strengthened after the Global Financial Crisis.JEL Classification: G12, G13, C14

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“…Additionally, we also consider the realized jump means variable (JM) constructed by Wright and Zhou (2009) and extended by Huang and Shi (2011). 17 JM is a measure of the time-varying amplitude of jumps in the US Treasury bond market based on high frequency data on 30-year Treasury bond futures.…”

Section: "Unspanned" Risks and Excess Returns On Bondsmentioning

confidence: 99%

A Robust Analysis of the Risk-Structure of Equilibrium Term Structures of Bond Yields

Singleton

2012

SSRN Journal

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Many equilibrium term structure models (ET SM s) in which the state of the economy z t follows an affine process imply that the variation in expected excess returns on bond portfolio positions is fully spanned by the set of conditional variances ς 2 t of z t . We show that these two assumptions alone-spanning of expected excess returns by the variances ς 2 t of affine processes z t -are sufficient to econometrically identify the quantities of risk that span risk premiums from the term structure of bond yields. Using this result we derive maximum likelihood estimates of ς 2 t and evaluate the goodness-of-fit of the family of affine ET SM s that imply this tight link between premiums and quantities of risk. These assessments are fully robust to the values of the parameters governing preferences and the evolution of the state z t , and to whether or not the economy is arbitrage free. Our findings suggest that, to be consistent with U.S. macroeconomic and Treasury yield data, affine ET SM s should have the features that: (i) the fundamental sources of risks, including consumption growth, inflation, and yield volatilities are driven by distinct economic shocks; (ii) consumption growth risk alone does not fully account for the predictability of excess returns on bonds; and (iii) inflation risk, and not long-run risks or variation in risk premiums arising from habit-based preferences, is a significant (and perhaps the dominant) risk underlying risk premiums in U.S. Treasury markets.

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Bond risk premia and realized jump risk

Cited by 95 publications

References 37 publications

Expected Business Conditions and Bond Risk Premia

Expected Business Conditions and Bond Risk Premia

Explaining Credit Default Swap Spreads by Means of Realized Jumps and Volatilities in the Energy Market

A Robust Analysis of the Risk-Structure of Equilibrium Term Structures of Bond Yields

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