Forecasting Exchange Price Volatility

 Forecasting Exchange Rate Unpredictability Essay

Journal of Empirical Finance 19 (2012) 627–639

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Journal of Empirical Financial

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Forecasting exchange price volatility: The superior efficiency of conditional combinations of the time series and option implied forecasts☆ Guillermo Benavides a, ⁎, Carlos Capistrán n



Banco de México, Mexico

Bank of America Merrill Lynch, Mexico



Article history:

Received twenty six February 2010

Accepted five July 2012

Available online 16 July 2012


Amalgamated forecasts

Forecast evaluation


Implied movements

Mexican peso–U. S. dollars exchange price

Regime turning


This kind of paper gives empirical data that combinations of option implied and time series volatility forecasts that are conditional on current information are statistically superior to person models, absolute, wholehearted combinations, and hybrid predictions. Superior foretelling of performance is achieved by both, taking into account the conditional predicted performance of each and every model given current information, and incorporating individual predictions. The method utilized in this paper to produce conditional combinations stretches the application of conditional predictive potential tests to pick forecast blends. The application is pertaining to volatility forecasts of the Mexican peso–US dollar exchange price, where recognized volatility determined using intraday data is utilized as a serwery proxy for the (latent) daily volatility. © 2012 Elsevier B. Sixth is v. All privileges reserved.

JEL classification:





1 . Introduction

Although several designs are trusted by teachers and practitioners to forecast volatility, nowadays there is no general opinion about which method is excellent in terms of predicting accuracy (Andersen et al., 2006; Poon and Granger, 2003; Taylor swift, 2005). The majority of models can be classified in two classes: models based on time series, and models based on options. There are basically two classes of types used in movements forecasting: designs based on period series, and models depending on options (Poon and Granger, 2003). Among the time series models, there are models based on past volatility, such as historic averages of

☆ We thank Alejandro Díaz de León, Antonio E. Noriega, Carla Ysusi, Carlos Muñoz Hink, the Editor and seminar participants at the 08 Latin American Meeting in the Econometric World at Rj, the XII Meeting of CEMLA's Central Bank Researchers' Network for Banco para España, the 2008 Getting together with of the Contemporary society of Nonlinear Dynamics and Econometrics with the Federal Hold Bank of San Francisco, Banco de México, ITAM, ITESM Campus Cd. de México, and Universidad del Cuenca de México for useful comments. All of us also say thanks to Antonio Sibaja and Pablo Bravo to get helping all of us with the exchange rate intraday data. Donna San Martín, Gabriel López-Moctezuma, Luis Adrián Muñiz, and Sergio Vargas provided excellent research assistance. The final draft of the paper was written whilst Carlos Capistrán was operating at Bajio de México (Central Bank of Mexico). The views expressed in this article are entirely those of the authors and don't necessarily reflect the landscapes of Banco de México or Lender of America Merrill Lynch. ⁎ Corresponding author at: Av your five de Mayo # two, Centro, México, D. Farrenheit., CP. 06059, México. Tel.: +52 55 5237 2000x3877; fax: +52 55 5237 2559. Email-based address: [email protected] org. mx (G. Benavides).

0927-5398/$ – see front matter © 2012 Elsevier B. Versus. All legal rights reserved. doi: 10. 1016/j. jempfin. 2012. 07. 001


G. Benavides, C. Capistrán as well as Journal of Empirical Financial 19 (2012) 627–639

square-shaped price earnings, Autoregressive Conditional Heteroskedasticity-type models (ARCH-Type), such as ARCH, GARCH, and EGARCH, and stochastic volatility types. 1 Among the options centered volatility types, typically named option implied volatilities (IV), there are the Black–Scholes-type types (Black and Scholes, 1973), the...

Referrals: Akgiray, Sixth is v., 1989. Conditional heteroskedasticity with time series of share returns: evidence and predictions. J. Bus. 62, 55–80.

Andersen, Capital t. G., Bollerslev, T., 98. Answering the skeptics: certainly, standard unpredictability models do provide correct forecasts. Int. Econ. Rev. 39, 885–905.

Andersen, To., Bollerslev, Capital t. P., Diebold, F. Back button., Labys, L., 1999. (Understanding, optimizing, using and forecasting) realized unpredictability and correlation. Working Conventional paper,

Northwestern College or university, Duke University or college and University of Pa, pp

Andersen, T. G., Bollerslev, Big t., Christoffersen, G. F., Diebold, F. X., 2006. Volatility and relationship forecasting. In: Elliott, G., Granger, C. W. T., Timmermann, A. (Eds. ),

Handbook of Economic Foretelling of

Bates, M. M., Granger, C. W. J., 69. The mixture of forecasts. Oper. Res. Q. 20, 451–468.

Becker, L., Clemens, A. E., 2008. Are combo forecasts of S& S 500 volatility statistically outstanding? Int. J. Forecast. twenty-four, 122–133.

Benavides, G., 2003. Price unpredictability forecasts to get agricultural goods: an application of historical unpredictability models, choice implieds and composite techniques for

futures and options prices of corn and wheat

Benavides, G., 2006. Volatility forecasts for the Mexican Peso–US Dollar exchange rate: an empirical analysis of GARCH, option intended and amalgamated forecasts


Black, N., Scholes, Meters. S., 1973. The costs of choices and corporate debts. J. Polit. Econ. seventy eight, 637–654 May–June.

Blair, N. J., Poon, S., The singer, S. T., 2001. Forecasting S& S 100 volatility: the gradual information articles of intended volatilities and high-frequency index returns.

Bollerslev, T. L., 1986. General autoregressive conditional heteroskedasticity. L. Econ. 23, 307–327.

Bollerslev, T. G., Engle, L. F., Nelson, D. M., 1994. POSTURE models. In: Engle, 3rd there�s r. F., McFadden, D. M. (Eds. ), Handbook of Econometrics, Volume. 4. Elsevier, Amsterdam.

Bollerslev, T. S., Tauchen, G., Zhou, H., 2009. Predicted stock comes back and difference risk premia. Rev. Financ. Stud. 22, 4463–4492.

Canina, L., Figlewski, S., 1993. The informational content of implied movements. Rev. Financ. Stud. 6th, 659–681.

Clemen, R. Big t., 1989. Merging forecasts: an assessment and annotated bibliography. Int. J. Prediction. 5, 559–583.

Cumby, Ur., Figlewski, S i9000., Hasbrouck, L., 1993. Foretelling of volatilities and correlations with EGARCH designs. J. Deriv. 1, 51–63.

Day, T. E., Lewis, C. Meters., 1992. Currency markets volatility and the information content of inventory index alternatives. J. Econ. 52, 267–287.

Deutsch, Meters., Granger, C. W. L., Terasvirta, Capital t., 1994. The combination of forecasts using changing weights. Int. J. Prediction. 10, 47–57.

Diebold, Farreneheit. X., Mariano, R. H., 1995. Evaluating predictive accuracy and reliability. J. Shuttle bus. Econ. Stat. 13, 253–263.

Ederington, D., Guan, Watts., 2002. Is definitely implied volatility an informationally efficient and effective predictor of future volatility? T. Risk some, 3.

Elliott, G., Timmermann, A., 2006. Optimal prediction combination weights under routine switching. Int. Econ. Revolution. 46, 1081–1102.

Engle, R. F., 1982. Autoregressive conditional heteroskedasticity with estimates in the variance of U. K. inflation. Econometrica 50, 987–1008.

Engle, Ur. F., Ng, V. E., 1993. Measuring and assessment the impact of stories on movements. J. Financial 48, 1749–1778.

Fleming, J., 1998. The quality of market movements forecasts intended by S& P 90 index choice prices. M. Empir. Financ. 5, 317–345.

Fleming, J., Ostdiek, N., Whaley, L. E., 1995. Predicting currency markets volatility: a new measure. T. Futur. Draw. 15, 265–302.

G. Benavides, C. Capistrán / Record of Empirical Finance 19 (2012) 627–639


Garman, M. M., Kohlhagen, H. W., 1983. Foreign currency choice values. J. Int. Money Finance a couple of, 231–237.

Giacomini, R., White-colored, H., 2006. Tests of conditional predictive ability. Econometrica 74, 1545–1578.

Granger, C. W. L., 2003. Very long memory procedure — a great economist is viewpoint. In: Gulats, C., et ing. (Ed. ), Advances in Statistics, Combinations, and Related Areas. Community

Scientific Publishers, pp

Granger, C. W. J., Ramanathan, R., 1984. Improved techniques of combining predictions. J. Outlook. 3, 197–204.

Guidolin, M., Timmermann, A., 2009. Predictions of US Short-term interest rates: a versatile forecast mixture approach. M. Econ. one hundred and fifty, 297–311.

Guo, D., 1996. The predictive power of intended stochastic variance from currency options. J. Futur. Mark. 16, 915–942.

Hansen, L. R., Lunde, A., 2005a. A prediction comparison of unpredictability models: truly does anything conquer a GARCH(1, 1)? M. Appl. Econ. 20, 873–889.

Hansen, G. R., Lunde, A., 2005b. A recognized variance for the entire day depending on intermittent higher frequency data. M. Financ. Econ. 3 (4), 525–554.

Jorion, P., 1995. Predicting unpredictability in the forex trading market. J. Finance 50, 507–528.

Lamoureux, C. G., Lastrapes, Watts. D., 1993. Forecasting share return difference: toward an awareness of stochastic implied volatilities. Rev. Financ. Stud. 6th, 293–326.

Manfredo, M., Leuthold, R. M., Irwin, S i9000. H., 2001. Forecasting funds price movements of given cattle, feeder cattle and corn: period series, intended volatility and composite


Newey, T., West, E., 1987. A basic positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix. Econometrica fifty-five, 703–708.

Noh, J., Engle, R. N., Kane, A., 1994. Foretelling of volatility and option rates of the S& P five-hundred index. T. Deriv. 2, 17–30.

Patton, A. L., 2011. Unpredictability forecast assessment using imperfect volatility unblock proxies. J. Econ. 160 (1), 246–256 (January).

Patton, A. J., Sheppard, K., 2009. Evaluating unpredictability and relationship forecasts. In: Andersen, T. G., Davis, R. A., Kreiss, L. P., Mikosch, T. (Eds. ), Handbook of Financial

Time Series

Pesaran, M. H., Timmermann, A., 2007. Number of estimation windows in the occurrence of fractures. J. Econ. 137, 134–161.

Pong, H., Shackleton, M., Taylor, H., Xu, Back button., 2004. Predicting currency volatility: a comparison of implied volatilities and AR(FI)MA models. L. Bank. Financ. 28 (10),


Poon, S. H., Granger, C. W. J., 2003. Foretelling of volatility in financial markets: a review. J. Econ. Lit. 41, 478–539.

Szakmary, A., Ors, E., Ellie, J. T., Davidson 3, W. M., 2003. The predictive benefits of implied volatility: evidence by 35 futures markets. M. Bank. Financ. 27, 2151–2175.

Taylor, S. J., 1986. Modeling Economical Time Series. Wiley.

Taylor swift, S. L., 2005. Property Price Mechanics, Volatility, and Prediction. Princeton University Press.

Timmermann, A., 2006. Outlook combinations. In: Elliott, G., Granger, C. W. M., Timmermann, A. (Eds. ), Handbook of Economic Foretelling of. North The netherlands, Amsterdam.

Western, K. D., 1996. Asymptotic inference about predictive ability. Econometrica 64, 1067–1084.

Xu, X., Taylor, S. T., 1995. Conditional volatility and the informational performance of the PHLX currency choices market. M. Bank. Financ. 19, 803–821.



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