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Implied Volatility with Time-Varying Regime Probabilities

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  • Lanne, Markku
  • Ahoniemi, Katja

Abstract

This paper presents a mixture multiplicative error model with a time-varying probability between regimes. We model the implied volatility derived from call and put options on the USD/EUR exchange rate. The daily first difference of the USD/EUR exchange rate is used as a regime indicator, with large daily changes signaling a more volatile regime. Forecasts indicate that it is beneficial to jointly model the two implied volatility series: both mean squared errors and directional accuracy improve when employing a bivariate rather than a univariate model. In a two-year out-of-sample period, the direction of change in implied volatility is correctly forecast on two thirds of the trading days.

Suggested Citation

  • Lanne, Markku & Ahoniemi, Katja, 2008. "Implied Volatility with Time-Varying Regime Probabilities," MPRA Paper 23721, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:23721
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    References listed on IDEAS

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    1. Asger Lunde & Peter R. Hansen, 2005. "A forecast comparison of volatility models: does anything beat a GARCH(1,1)?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(7), pages 873-889.
    2. Chris Brooks & M. Currim Oozeer, 2002. "Modelling the Implied Volatility of Options on Long Gilt Futures," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 29(1&2), pages 111-137.
    3. Ederington, Louis & Guan, Wei, 2005. "The information frown in option prices," Journal of Banking & Finance, Elsevier, vol. 29(6), pages 1429-1457, June.
    4. Fulvio Corsi & Stefan Mittnik & Christian Pigorsch & Uta Pigorsch, 2008. "The Volatility of Realized Volatility," Econometric Reviews, Taylor & Francis Journals, vol. 27(1-3), pages 46-78.
    5. Markku Lanne, 2006. "A Mixture Multiplicative Error Model for Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 4(4), pages 594-616.
    6. Robert Engle, 2002. "New frontiers for arch models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 425-446.
    7. Engel, Charles & Hakkio, Craig S, 1996. "The Distribution of Exchange Rates in the EMS," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 1(1), pages 55-67, January.
    8. Markku Lanne & Pentti Saikkonen, 2003. "Modeling the U.S. Short-Term Interest Rate by Mixture Autoregressive Processes," Journal of Financial Econometrics, Oxford University Press, vol. 1(1), pages 96-125.
    9. Bauwens, Luc & Giot, Pierre & Grammig, Joachim & Veredas, David, 2004. "A comparison of financial duration models via density forecasts," International Journal of Forecasting, Elsevier, vol. 20(4), pages 589-609.
    10. 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.
    11. Engle, Robert F. & Gallo, Giampiero M., 2006. "A multiple indicators model for volatility using intra-daily data," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 3-27.
    12. Nicolae Garleanu & Lasse Heje Pedersen & Allen M. Poteshman, 2009. "Demand-Based Option Pricing," The Review of Financial Studies, Society for Financial Studies, vol. 22(10), pages 4259-4299, October.
    13. Franc Klaassen, 2002. "Improving GARCH volatility forecasts with regime-switching GARCH," Empirical Economics, Springer, vol. 27(2), pages 363-394.
    14. Jorion, Philippe, 1995. "Predicting Volatility in the Foreign Exchange Market," Journal of Finance, American Finance Association, vol. 50(2), pages 507-528, June.
    15. Gurdip Bakshi & Nikunj Kapadia, 2003. "Delta-Hedged Gains and the Negative Market Volatility Risk Premium," The Review of Financial Studies, Society for Financial Studies, vol. 16(2), pages 527-566.
    16. Diebold, Francis X & Gunther, Todd A & Tay, Anthony S, 1998. "Evaluating Density Forecasts with Applications to Financial Risk Management," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 863-883, November.
    17. Figlewski, Stephen, 1989. " Options Arbitrage in Imperfect Markets," Journal of Finance, American Finance Association, vol. 44(5), pages 1289-1311, December.
    18. Chris Brooks & M. Currim Oozeer, 2002. "Modelling the Implied Volatility of Options on Long Gilt Futures," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 29(1‐2), pages 111-137.
    19. Campa, Jose M. & Chang, P. H. Kevin & Reider, Robert L., 1998. "Implied exchange rate distributions: evidence from OTC option markets1," Journal of International Money and Finance, Elsevier, vol. 17(1), pages 117-160, February.
    20. Ahoniemi, Katja & Lanne, Markku, 2009. "Joint modeling of call and put implied volatility," International Journal of Forecasting, Elsevier, vol. 25(2), pages 239-258.
    21. Gencay, Ramazan, 1998. "Optimization of technical trading strategies and the profitability in security markets," Economics Letters, Elsevier, vol. 59(2), pages 249-254, May.
    22. Markus Haas, 2004. "A New Approach to Markov-Switching GARCH Models," Journal of Financial Econometrics, Oxford University Press, vol. 2(4), pages 493-530.
    23. Engel, Charles & Hamilton, James D, 1990. "Long Swings in the Dollar: Are They in the Data and Do Markets Know It?," American Economic Review, American Economic Association, vol. 80(4), pages 689-713, September.
    24. Bollen, Nicolas P. B. & Gray, Stephen F. & Whaley, Robert E., 2000. "Regime switching in foreign exchange rates: Evidence from currency option prices," Journal of Econometrics, Elsevier, vol. 94(1-2), pages 239-276.
    25. Nicolas P. B. Bollen & Robert E. Whaley, 2004. "Does Net Buying Pressure Affect the Shape of Implied Volatility Functions?," Journal of Finance, American Finance Association, vol. 59(2), pages 711-753, April.
    26. Bekaert, Geert & Hodrick, Robert J., 1993. "On biases in the measurement of foreign exchange risk premiums," Journal of International Money and Finance, Elsevier, vol. 12(2), pages 115-138, April.
    27. Pong, Shiuyan & Shackleton, Mark B. & Taylor, Stephen J. & Xu, Xinzhong, 2004. "Forecasting currency volatility: A comparison of implied volatilities and AR(FI)MA models," Journal of Banking & Finance, Elsevier, vol. 28(10), pages 2541-2563, October.
    28. Nelson, Daniel B & Cao, Charles Q, 1992. "Inequality Constraints in the Univariate GARCH Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(2), pages 229-235, April.
    29. Kim, Minho & Kim, Minchoul, 2003. "Implied volatility dynamics in the foreign exchange markets," Journal of International Money and Finance, Elsevier, vol. 22(4), pages 511-528, August.
    30. Xu, Xinzhong & Taylor, Stephen J., 1995. "Conditional volatility and the informational efficiency of the PHLX currency options market," Journal of Banking & Finance, Elsevier, vol. 19(5), pages 803-821, August.
    31. Richard T. Baillie & Tim Bollerslev, 1991. "Intra-Day and Inter-Market Volatility in Foreign Exchange Rates," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(3), pages 565-585.
    32. Pesaran, M Hashem & Timmermann, Allan, 1995. "Predictability of Stock Returns: Robustness and Economic Significance," Journal of Finance, American Finance Association, vol. 50(4), pages 1201-1228, September.
    33. David E. Rapach & Jack K. Strauss, 2008. "Structural breaks and GARCH models of exchange rate volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(1), pages 65-90.
    34. Dajiang Guo, 2000. "Dynamic Volatility Trading Strategies in the Currency Option Market," Review of Derivatives Research, Springer, vol. 4(2), pages 133-154, May.
    35. Francis X. Diebold & Jinyong Hahn & Anthony S. Tay, 1999. "Multivariate Density Forecast Evaluation And Calibration In Financial Risk Management: High-Frequency Returns On Foreign Exchange," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 661-673, November.
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    More about this item

    Keywords

    Implied volatility; option markets; multiplicative error models; forecasting;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

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