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Yield Curve and Volatility: Lessons from Eurodollar Futures and Options

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  • Ruslan Bikbov
  • Mikhail Chernov

Abstract

We evaluate the statistical and economic differences between affine term-structure models. Despite the voluminous literature on this subject, we have a limited understanding of those structural features of the models that are important in practice. Given that the key distinguishing characteristic of the affine models is the specification of the conditional volatility of the factors, we explore models that have critical differences in this respect: Gaussian (constant volatility) and stochastic volatility models. We estimate the models using the Eurodollar futures and options data as a basis. We subject these models to an exhaustive set of diagnostics. In particular, we develop a finite-sample version of the encompassing test for non-nested models. We find, based on the statistical tests and pricing errors, that there is little difference between the models when the models are estimated using only the yield curve information. Using options data enables us to separate the models very clearly. The stochastic volatility model is the most successful according to our diagnostics. JEL: C1, G12 Copyright The Author 2010. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org, Oxford University Press.

Suggested Citation

  • Ruslan Bikbov & Mikhail Chernov, 2011. "Yield Curve and Volatility: Lessons from Eurodollar Futures and Options," Journal of Financial Econometrics, Oxford University Press, vol. 9(1), pages 66-105, Winter.
  • Handle: RePEc:oup:jfinec:v:9:y:2011:i:1:p:66-105
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    File URL: http://hdl.handle.net/10.1093/jjfinec/nbq019
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    Citations

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    Cited by:

    1. Hideyuki Takamizawa, 2015. "Predicting Interest Rate Volatility Using Information on the Yield Curve," International Review of Finance, International Review of Finance Ltd., vol. 15(3), pages 347-386, September.
    2. Guimarães, Rodrigo, 2014. "Expectations, risk premia and information spanning in dynamic term structure model estimation," Bank of England working papers 489, Bank of England.
    3. Mikhail Chernov & Drew Creal, 2023. "International Yield Curves and Currency Puzzles," Journal of Finance, American Finance Association, vol. 78(1), pages 209-245, February.
    4. Wang, Lijun & An, Haizhong & Liu, Xiaojia & Huang, Xuan, 2016. "Selecting dynamic moving average trading rules in the crude oil futures market using a genetic approach," Applied Energy, Elsevier, vol. 162(C), pages 1608-1618.
    5. Sarno, Lucio & Schneider, Paul & Wagner, Christian, 2012. "Properties of foreign exchange risk premiums," Journal of Financial Economics, Elsevier, vol. 105(2), pages 279-310.
    6. Chernov, Mikhail & Mueller, Philippe, 2012. "The term structure of inflation expectations," Journal of Financial Economics, Elsevier, vol. 106(2), pages 367-394.
    7. Almeida, Caio & Graveline, Jeremy J. & Joslin, Scott, 2011. "Do interest rate options contain information about excess returns?," Journal of Econometrics, Elsevier, vol. 164(1), pages 35-44, September.
    8. Monfort, Alain & Pegoraro, Fulvio & Renne, Jean-Paul & Roussellet, Guillaume, 2017. "Staying at zero with affine processes: An application to term structure modelling," Journal of Econometrics, Elsevier, vol. 201(2), pages 348-366.
    9. Takamizawa, Hideyuki & 高見澤, 秀幸, 2015. "Impact of No-arbitrage on Interest Rate Dynamics," Working Paper Series G-1-5, Hitotsubashi University Center for Financial Research.
    10. Jonathan Hambur & Richard Finlay, 2018. "Affine Endeavour: Estimating a Joint Model of the Nominal and Real Term Structures of Interest Rates in Australia," RBA Research Discussion Papers rdp2018-02, Reserve Bank of Australia.
    11. Anne Lundgaard Hansen, 2018. "Volatility-Induced Stationarity and Error-Correction in Macro-Finance Term Structure Modeling," Discussion Papers 18-12, University of Copenhagen. Department of Economics.
    12. Jonathan Hambur & Qazi Haque, 2023. "Can We Use High-Frequency Yield Data to Better Understand the Effects of Monetary Policy and Its Communication? Yes and No!," CAMA Working Papers 2023-26, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    13. Juneja, Januj, 2012. "Common factors, principal components analysis, and the term structure of interest rates," International Review of Financial Analysis, Elsevier, vol. 24(C), pages 48-56.
    14. Jens H. E. Christensen & Jose A. Lopez & Glenn D. Rudebusch, 2014. "Can Spanned Term Structure Factors Drive Stochastic Yield Volatility?," Working Paper Series 2014-3, Federal Reserve Bank of San Francisco.

    More about this item

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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