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Testing the forward volatility unbiasedness hypothesis in exchange rates under long-range dependence

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  • Pérez-Rodríguez, Jorge V.
  • Andrada-Félix, Julián
  • Rachinger, Heiko

Abstract

This paper analyses the unbiasedness hypothesis between spot and forward volatility, using both the actual and the continuous path of realised volatility, and focusing on long-memory properties. For this purpose, we use daily realised volatility with jumps for the USD/EUR exchange rate negotiated in the FX market and employ fractional integration and cointegration techniques. Both series have long-range dependence, and so does the error correction term of their long-run relationship. Hence, deviations from equilibrium are highly persistent, and the effects of shocks affecting the long-run relationship dissipate very slowly. While for long-term contracts, there is some empirical evidence that the forward volatility unbiasedness hypothesis does not hold – and, thus, that forward implied volatility is a systematically downward-biased predictor of future spot volatility – for short-term contracts, the evidence is mixed.

Suggested Citation

  • Pérez-Rodríguez, Jorge V. & Andrada-Félix, Julián & Rachinger, Heiko, 2021. "Testing the forward volatility unbiasedness hypothesis in exchange rates under long-range dependence," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    • Handle: RePEc:eee:ecofin:v:57:y:2021:i:c:s106294082100067x
    DOI: 10.1016/j.najef.2021.101438
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    1. Søren Johansen & Morten Ørregaard Nielsen, 2012. "Likelihood Inference for a Fractionally Cointegrated Vector Autoregressive Model," Econometrica, Econometric Society, vol. 80(6), pages 2667-2732, November.
    2. Berger, David & Chaboud, Alain & Hjalmarsson, Erik, 2009. "What drives volatility persistence in the foreign exchange market?," Journal of Financial Economics, Elsevier, vol. 94(2), pages 192-213, November.
    3. Andersen T. G & Bollerslev T. & Diebold F. X & Labys P., 2001. "The Distribution of Realized Exchange Rate Volatility," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 42-55, March.
    4. Søren Johansen & Morten Ørregaard Nielsen, 2019. "Nonstationary Cointegration in the Fractionally Cointegrated VAR Model," Journal of Time Series Analysis, Wiley Blackwell, vol. 40(4), pages 519-543, July.
    5. Della Corte, Pasquale & Sarno, Lucio & Tsiakas, Ilias, 2011. "Spot and forward volatility in foreign exchange," Journal of Financial Economics, Elsevier, vol. 100(3), pages 496-513, June.
    6. Søren Johansen & Morten Ørregaard Nielsen, 2018. "Testing the CVAR in the Fractional CVAR Model," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(6), pages 836-849, November.
    7. Anupam Dutta, 2017. "Modeling and forecasting oil price risk: the role of implied volatility index," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 44(6), pages 1003-1016, November.
    8. Ole E. Barndorff-Nielsen & Neil Shephard, 2006. "Econometrics of Testing for Jumps in Financial Economics Using Bipower Variation," Journal of Financial Econometrics, Oxford University Press, vol. 4(1), pages 1-30.
    9. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2007. "Roughing It Up: Including Jump Components in the Measurement, Modeling, and Forecasting of Return Volatility," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 701-720, November.
    10. Haugom, Erik & Langeland, Henrik & Molnár, Peter & Westgaard, Sjur, 2014. "Forecasting volatility of the U.S. oil market," Journal of Banking & Finance, Elsevier, vol. 47(C), pages 1-14.
    11. Johansen, Søren & Nielsen, Morten Ørregaard, 2010. "Likelihood inference for a nonstationary fractional autoregressive model," Journal of Econometrics, Elsevier, vol. 158(1), pages 51-66, September.
    12. Morten Ørregaard Nielsen & Per Frederiksen, 2011. "Fully modified narrow‐band least squares estimation of weak fractional cointegration," Econometrics Journal, Royal Economic Society, vol. 14(1), pages 77-120, February.
    13. Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde & Neil Shephard, 2008. "Designing Realized Kernels to Measure the ex post Variation of Equity Prices in the Presence of Noise," Econometrica, Econometric Society, vol. 76(6), pages 1481-1536, November.
    14. Fulvio Corsi, 2009. "A Simple Approximate Long-Memory Model of Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 7(2), pages 174-196, Spring.
    15. Tsay, Wen-Jen & Chung, Ching-Fan, 2000. "The spurious regression of fractionally integrated processes," Journal of Econometrics, Elsevier, vol. 96(1), pages 155-182, May.
    16. Jorge V. Pérez-Rodríguez, 2020. "Another look at the implied and realised volatility relation: a copula-based approach," Risk Management, Palgrave Macmillan, vol. 22(1), pages 38-64, March.
    17. Engel, Charles, 1996. "The forward discount anomaly and the risk premium: A survey of recent evidence," Journal of Empirical Finance, Elsevier, vol. 3(2), pages 123-192, June.
    18. Andersen, Torben G & Bollerslev, Tim, 1998. "Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 885-905, November.
    19. Ole E. Barndorff‐Nielsen & Neil Shephard, 2002. "Econometric analysis of realized volatility and its use in estimating stochastic volatility models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(2), pages 253-280, May.
    20. Busch, Thomas & Christensen, Bent Jesper & Nielsen, Morten Ørregaard, 2011. "The role of implied volatility in forecasting future realized volatility and jumps in foreign exchange, stock, and bond markets," Journal of Econometrics, Elsevier, vol. 160(1), pages 48-57, January.
    21. Pasquale Della Corte & Lucio Sarno & Ilias Tsiakas, 2009. "An Economic Evaluation of Empirical Exchange Rate Models," The Review of Financial Studies, Society for Financial Studies, vol. 22(9), pages 3491-3530, September.
    22. Cox, Charles C, 1976. "Futures Trading and Market Information," Journal of Political Economy, University of Chicago Press, vol. 84(6), pages 1215-1237, December.
    23. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501.
    24. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Clara Vega, 2003. "Micro Effects of Macro Announcements: Real-Time Price Discovery in Foreign Exchange," American Economic Review, American Economic Association, vol. 93(1), pages 38-62, March.
    25. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    26. Marinucci, D & Robinson, Peter M., 2001. "Semiparametric fractional cointegration analysis," LSE Research Online Documents on Economics 2269, London School of Economics and Political Science, LSE Library.
    27. Federico M. Bandi & Benoit Perron, 2006. "Long Memory and the Relation Between Implied and Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 4(4), pages 636-670.
    28. Marinucci, D. & Robinson, P. M., 2001. "Semiparametric fractional cointegration analysis," Journal of Econometrics, Elsevier, vol. 105(1), pages 225-247, November.
    29. D Marinucci & Peter M Robinson, 2001. "Semiparametric Fractional Cointegration Analysis," STICERD - Econometrics Paper Series 420, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    30. Canina, Linda & Figlewski, Stephen, 1993. "The Informational Content of Implied Volatility," The Review of Financial Studies, Society for Financial Studies, vol. 6(3), pages 659-681.
    31. Luo, Xingguo & Qin, Shihua & Ye, Zinan, 2016. "The information content of implied volatility and jumps in forecasting volatility: Evidence from the Shanghai gold futures market," Finance Research Letters, Elsevier, vol. 19(C), pages 105-111.
    32. Lamoureux, Christopher G & Lastrapes, William D, 1993. "Forecasting Stock-Return Variance: Toward an Understanding of Stochastic Implied Volatilities," The Review of Financial Studies, Society for Financial Studies, vol. 6(2), pages 293-326.
    33. Michael McAleer & Marcelo C. Medeiros, 2011. "Forecasting Realized Volatility With Linear And Nonlinear Univariate Models," Journal of Economic Surveys, Wiley Blackwell, vol. 25(1), pages 6-18, February.
    34. Johansen, SØren, 2008. "A Representation Theory For A Class Of Vector Autoregressive Models For Fractional Processes," Econometric Theory, Cambridge University Press, vol. 24(3), pages 651-676, June.
    35. Granger, Clive W J, 1986. "Developments in the Study of Cointegrated Economic Variables," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 48(3), pages 213-228, August.
    36. James G. MacKinnon & Morten Ørregaard Nielsen, 2014. "Numerical Distribution Functions Of Fractional Unit Root And Cointegration Tests," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(1), pages 161-171, January.
    37. Hualde, J. & Robinson, P.M., 2010. "Semiparametric inference in multivariate fractionally cointegrated systems," Journal of Econometrics, Elsevier, vol. 157(2), pages 492-511, August.
    38. Fama, Eugene F., 1984. "Forward and spot exchange rates," Journal of Monetary Economics, Elsevier, vol. 14(3), pages 319-338, November.
    39. Christensen, B. J. & Prabhala, N. R., 1998. "The relation between implied and realized volatility," Journal of Financial Economics, Elsevier, vol. 50(2), pages 125-150, November.
    40. Christensen, Bent Jesper & Nielsen, Morten Orregaard, 2006. "Asymptotic normality of narrow-band least squares in the stationary fractional cointegration model and volatility forecasting," Journal of Econometrics, Elsevier, vol. 133(1), pages 343-371, July.
    41. Eduardo Rossi & Paolo Santucci de Magistris, 2013. "A No‐Arbitrage Fractional Cointegration Model for Futures and Spot Daily Ranges," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 33(1), pages 77-102, January.
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    More about this item

    Keywords

    Exchange rates; Forward volatility unbiasedness hypothesis; Fractional cointegration;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • F31 - International Economics - - International Finance - - - Foreign Exchange

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