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

journal website: www.elsevier.com/locate/jempfin

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

a

b

Banco de México, Mexico

Bank of America Merrill Lynch, Mexico

article

facts

Article history:

Received twenty six February 2010

Accepted five July 2012

Available online 16 July 2012

Keywords:

Amalgamated forecasts

Forecast evaluation

GARCH

Implied movements

Mexican peso–U. S. dollars exchange price

Regime turning

abstract

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:

C22

C52

C53

G10

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

628

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

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