IDEAS home Printed from https://ideas.repec.org/p/bcb/wpaper/454.html
   My bibliography  Save this paper

Expected Currency Returns and Volatility Risk Premia

Author

Listed:
  • José Renato Haas Ornelas

Abstract

This paper addresses the predictive ability of currency volatility risk premium - the difference between an implied and a realized volatility - over US dollar exchange rates using a time-series perspective. The intuition is that, when risk aversion sentiment increases, the market quickly discounts the currency, and later this discount is “accrued”, leading to a future currency appreciation. Based on two different samples with a diversified set of 32 currencies, I document a positive relationship between currency volatility risk premium and future currency returns. Results remain robust even after controlling for traditional fundamental predictors like Purchase Power Parity and interest rate differential.

Suggested Citation

  • José Renato Haas Ornelas, 2017. "Expected Currency Returns and Volatility Risk Premia," Working Papers Series 454, Central Bank of Brazil, Research Department.
  • Handle: RePEc:bcb:wpaper:454
    as

    Download full text from publisher

    File URL: https://www.bcb.gov.br/content/publicacoes/WorkingPaperSeries/wps454.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Francis X. Diebold, 2015. "Comparing Predictive Accuracy, Twenty Years Later: A Personal Perspective on the Use and Abuse of Diebold-Mariano Tests," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(1), pages 1-1, January.
    2. Cheung, Yin-Wong & Chinn, Menzie D. & Pascual, Antonio Garcia, 2005. "Empirical exchange rate models of the nineties: Are any fit to survive?," Journal of International Money and Finance, Elsevier, vol. 24(7), pages 1150-1175, November.
    3. Ornelas, José Renato Haas & Mauad, Roberto Baltieri, 2019. "Volatility risk premia and future commodity returns," Journal of International Money and Finance, Elsevier, vol. 96(C), pages 341-360.
    4. Menkhoff, Lukas & Sarno, Lucio & Schmeling, Maik & Schrimpf, Andreas, 2012. "Currency momentum strategies," Journal of Financial Economics, Elsevier, vol. 106(3), pages 660-684.
    5. Ornelas, José Renato Haas, 2016. "The Forecast Ability of Option-implied Densities from Emerging Markets Currencies," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 36(1), March.
    6. Peter Christoffersen & Stefano Mazzotta, 2005. "The Accuracy of Density Forecasts from Foreign Exchange Options," Journal of Financial Econometrics, Oxford University Press, vol. 3(4), pages 578-605.
    7. Jiang, Chun & Li, Xiao-Lin & Chang, Hsu-Ling & Su, Chi-Wei, 2013. "Uncovered interest parity and risk premium convergence in Central and Eastern European countries," Economic Modelling, Elsevier, vol. 33(C), pages 204-208.
    8. Della Corte, Pasquale & Ramadorai, Tarun & Sarno, Lucio, 2016. "Volatility risk premia and exchange rate predictability," Journal of Financial Economics, Elsevier, vol. 120(1), pages 21-40.
    9. Tim Bollerslev & George Tauchen & Hao Zhou, 2009. "Expected Stock Returns and Variance Risk Premia," The Review of Financial Studies, Society for Financial Studies, vol. 22(11), pages 4463-4492, November.
    10. 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.
    11. Bollerslev, Tim & Marrone, James & Xu, Lai & Zhou, Hao, 2014. "Stock Return Predictability and Variance Risk Premia: Statistical Inference and International Evidence," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 49(3), pages 633-661, June.
    12. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    13. Carr, Peter & Wu, Liuren, 2007. "Stochastic skew in currency options," Journal of Financial Economics, Elsevier, vol. 86(1), pages 213-247, October.
    14. Aloosh, Arash, 2014. "Global Variance Risk Premium and Forex Return Predictability," MPRA Paper 59931, University Library of Munich, Germany.
    15. Bekaert, Geert & Hoerova, Marie, 2014. "The VIX, the variance premium and stock market volatility," Journal of Econometrics, Elsevier, vol. 183(2), pages 181-192.
    16. Mayfield, E. Scott & Murphy, Robert G., 1992. "Interest rate parity and the exchange risk premium Evidence from panel data," Economics Letters, Elsevier, vol. 40(3), pages 319-324, November.
    17. Mr. Dennis P Botman & Mr. Irineu E de Carvalho Filho & Mr. Waikei R Lam, 2013. "The Curious Case of the Yen as a Safe Haven Currency: A Forensic Analysis," IMF Working Papers 2013/228, International Monetary Fund.
    18. Ichiue, Hibiki & Koyama, Kentaro, 2011. "Regime switches in exchange rate volatility and uncovered interest parity," Journal of International Money and Finance, Elsevier, vol. 30(7), pages 1436-1450.
    19. Ornelas, José Renato Haas & Mauad, Roberto Baltieri, 2019. "Implied volatility term structure and exchange rate predictability," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1800-1813.
    20. José Renato Haas Ornelas & Roberto Baltieri Mauad, 2017. "Volatility risk premia and future commodities returns," BIS Working Papers 619, Bank for International Settlements.
    21. 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.
    22. Li, Dandan & Ghoshray, Atanu & Morley, Bruce, 2012. "Measuring the risk premium in uncovered interest parity using the component GARCH-M model," International Review of Economics & Finance, Elsevier, vol. 24(C), pages 167-176.
    23. Meese, Richard A. & Rogoff, Kenneth, 1983. "Empirical exchange rate models of the seventies : Do they fit out of sample?," Journal of International Economics, Elsevier, vol. 14(1-2), pages 3-24, February.
    24. Londono, Juan M. & Zhou, Hao, 2017. "Variance risk premiums and the forward premium puzzle," Journal of Financial Economics, Elsevier, vol. 124(2), pages 415-440.
    25. Jegadeesh, Narasimhan & Titman, Sheridan, 1993. "Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency," Journal of Finance, American Finance Association, vol. 48(1), pages 65-91, March.
    26. Barroso, Pedro & Santa-Clara, Pedro, 2015. "Beyond the Carry Trade: Optimal Currency Portfolios," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 50(5), pages 1037-1056, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ornelas, José Renato Haas & Mauad, Roberto Baltieri, 2019. "Volatility risk premia and future commodity returns," Journal of International Money and Finance, Elsevier, vol. 96(C), pages 341-360.
    2. Chamizo, Álvaro & Novales, Alfonso, 2020. "Looking through systemic credit risk: Determinants, stress testing and market value," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 64(C).
    3. Alfonso Novales & Alvaro Chamizo, 2019. "Splitting Credit Risk into Systemic, Sectorial and Idiosyncratic Components," JRFM, MDPI, vol. 12(3), pages 1-33, August.
    4. Gordon Schulze, 2021. "Carry Trade Returns and Segmented Risk Pricing," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 49(1), pages 23-40, March.
    5. Jaqueline Terra Moura Marins, 2020. "Option-Based Risk Aversion Indicators for Predicting Currency Crises in Emerging Markets," Working Papers Series 515, Central Bank of Brazil, Research Department.
    6. Finta, Marinela Adriana & Ornelas, José Renato Haas, 2022. "Commodity return predictability: Evidence from implied variance, skewness, and their risk premia☆☆," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
    7. Ornelas, José Renato Haas & Mauad, Roberto Baltieri, 2019. "Implied volatility term structure and exchange rate predictability," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1800-1813.
    8. José Renato Haas Ornelas & Roberto Baltieri Mauad, 2017. "Volatility risk premia and future commodities returns," BIS Working Papers 619, Bank for International Settlements.
    9. Lycheva, Maria & Mironenkov, Alexey & Kurbatskii, Alexey & Fantazzini, Dean, 2022. "Forecasting oil prices with penalized regressions, variance risk premia and Google data," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 68, pages 28-49.
    10. Marinela Adriana Finta & José Renato Haas Ornelas, 2018. "Commodity Return Predictability: evidence from implied variance, skewness and their risk premia and their risk premia," Working Papers Series 479, Central Bank of Brazil, Research Department.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jamali, Ibrahim & Yamani, Ehab, 2019. "Out-of-sample exchange rate predictability in emerging markets: Fundamentals versus technical analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 61(C), pages 241-263.
    2. Marinela Adriana Finta & José Renato Haas Ornelas, 2018. "Commodity Return Predictability: evidence from implied variance, skewness and their risk premia and their risk premia," Working Papers Series 479, Central Bank of Brazil, Research Department.
    3. Ornelas, José Renato Haas & Mauad, Roberto Baltieri, 2019. "Implied volatility term structure and exchange rate predictability," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1800-1813.
    4. Matthew Greenwood-Nimmo & Daan Steenkamp & Rossouw van Jaarsveld, 2022. "CaninformationonthedistributionofZARreturnsbeusedtoimproveSARBsZARforecasts," Working Papers 11035, South African Reserve Bank.
    5. Finta, Marinela Adriana & Ornelas, José Renato Haas, 2022. "Commodity return predictability: Evidence from implied variance, skewness, and their risk premia☆☆," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
    6. Pyun, Sungjune, 2019. "Variance risk in aggregate stock returns and time-varying return predictability," Journal of Financial Economics, Elsevier, vol. 132(1), pages 150-174.
    7. Cheung, Yin-Wong & Wang, Wenhao, 2022. "Uncovered interest rate parity redux: Non-uniform effects," Journal of Empirical Finance, Elsevier, vol. 67(C), pages 133-151.
    8. Kruse, Robinson & Leschinski, Christian & Will, Michael, 2016. "Comparing Predictive Accuracy under Long Memory - With an Application to Volatility Forecasting," Hannover Economic Papers (HEP) dp-571, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    9. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    10. Ornelas, José Renato Haas & Mauad, Roberto Baltieri, 2019. "Volatility risk premia and future commodity returns," Journal of International Money and Finance, Elsevier, vol. 96(C), pages 341-360.
    11. Wilms, Ines & Rombouts, Jeroen & Croux, Christophe, 2021. "Multivariate volatility forecasts for stock market indices," International Journal of Forecasting, Elsevier, vol. 37(2), pages 484-499.
    12. Morales-Arias, Leonardo & Moura, Guilherme V., 2013. "Adaptive forecasting of exchange rates with panel data," International Journal of Forecasting, Elsevier, vol. 29(3), pages 493-509.
    13. Engel, Charles, 2014. "Exchange Rates and Interest Parity," Handbook of International Economics, in: Gopinath, G. & Helpman, . & Rogoff, K. (ed.), Handbook of International Economics, edition 1, volume 4, chapter 0, pages 453-522, Elsevier.
    14. Juan M. Londono & Nancy R. Xu, 2019. "Variance Risk Premium Components and International Stock Return Predictability," International Finance Discussion Papers 1247, Board of Governors of the Federal Reserve System (U.S.).
    15. Andersen, Torben G. & Todorov, Viktor & Ubukata, Masato, 2021. "Tail risk and return predictability for the Japanese equity market," Journal of Econometrics, Elsevier, vol. 222(1), pages 344-363.
    16. Slim, Skander & Dahmene, Meriam & Boughrara, Adel, 2020. "How informative are variance risk premium and implied volatility for Value-at-Risk prediction? International evidence," The Quarterly Review of Economics and Finance, Elsevier, vol. 76(C), pages 22-37.
    17. Suk Joon Byun & Bart Frijns & Tai‐Yong Roh, 2018. "A comprehensive look at the return predictability of variance risk premia," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(4), pages 425-445, April.
    18. Bams, Dennis & Blanchard, Gildas & Honarvar, Iman & Lehnert, Thorsten, 2017. "Does oil and gold price uncertainty matter for the stock market?," Journal of Empirical Finance, Elsevier, vol. 44(C), pages 270-285.
    19. Aloosh, Arash, 2014. "Global Variance Risk Premium and Forex Return Predictability," MPRA Paper 59931, University Library of Munich, Germany.
    20. Kaminska, Iryna & Roberts-Sklar, Matt, 2015. "A global factor in variance risk premia and local bond pricing," Bank of England working papers 576, Bank of England.

    More about this item

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • F37 - International Economics - - International Finance - - - International Finance Forecasting and Simulation: Models and Applications

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bcb:wpaper:454. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Rodrigo Barbone Gonzalez (email available below). General contact details of provider: https://www.bcb.gov.br/en .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.