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Options trading profits from correlation forecasts

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  • James Chong
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    Abstract

    This study examines the profitability of trading currency straddles on the basis of the volatility and correlation forecasts derived from various statistical models. There is evidence to demonstrate that for maximum wealth accumulation, a trader should employ sophisticated models like the exponential GARCH for correlation forecasts and simpler ones like the exponential weighted moving average for volatility forecasts. With differing transaction costs structure between traders, the directional bets taken by the models of the market maker for the most part appear successful, reaping large positive returns. This is especially evident for GBP/DEM straddles and to a lesser extent for JPY/DEM straddles. However, the options trading strategy profits of the price taker are insufficient to outweigh transaction costs, a result considered consistent with market efficiency.

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    File URL: http://www.tandfonline.com/doi/abs/10.1080/0960310042000281194
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    Bibliographic Info

    Article provided by Taylor & Francis Journals in its journal Applied Financial Economics.

    Volume (Year): 14 (2004)
    Issue (Month): 15 ()
    Pages: 1075-1085

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    Handle: RePEc:taf:apfiec:v:14:y:2004:i:15:p:1075-1085

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    1. Robert F. Engle & Alex Kane & Jaesun Noh, 1993. "Index-Option Pricing with Stochastic Volatility and the Value of Accurate Variance Forecasts," NBER Working Papers 4519, National Bureau of Economic Research, Inc.
    2. Bollerslev, Tim & Engle, Robert F. & Nelson, Daniel B., 1986. "Arch models," Handbook of Econometrics, in: R. F. Engle & D. McFadden (ed.), Handbook of Econometrics, edition 1, volume 4, chapter 49, pages 2959-3038 Elsevier.
    3. Kenneth D. West & Hali J. Edison & Dongchul Cho, 1992. "A Utility Based Comparison of Some Models of Exchange Rate Volatility," NBER Technical Working Papers 0128, National Bureau of Economic Research, Inc.
    4. Garman, Mark B. & Kohlhagen, Steven W., 1983. "Foreign currency option values," Journal of International Money and Finance, Elsevier, vol. 2(3), pages 231-237, December.
    5. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2002. "Parametric and Nonparametric Volatility Measurement," NBER Technical Working Papers 0279, National Bureau of Economic Research, Inc.
    6. Donald B. Keim & Ananth Madhavan, . "The Cost of Institutional Equity Trades," Rodney L. White Center for Financial Research Working Papers 08-98, Wharton School Rodney L. White Center for Financial Research.
    7. Campa, J.M. & Chang, P.H.K., 1995. "The Forecasting Ability of Correlations Implied in Foreign Exchange Options," Papers 95-26, Columbia - Graduate School of Business.
    8. Robert F. Engle & Che-Hsiung Hong & Alex Kane, 1990. "Valuation of Variance Forecast with Simulated Option Markets," NBER Working Papers 3350, National Bureau of Economic Research, Inc.
    9. Hull, John C & White, Alan D, 1987. " The Pricing of Options on Assets with Stochastic Volatilities," Journal of Finance, American Finance Association, vol. 42(2), pages 281-300, June.
    10. Peter Christoffersen & Kris Jacobs, 2004. "Which GARCH Model for Option Valuation?," Management Science, INFORMS, vol. 50(9), pages 1204-1221, September.
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    Cited by:
    1. M. Brunetti & C. Torricelli, 2007. "The internal and cross market efficiency in index option markets: an investigation of the Italian market," Applied Financial Economics, Taylor & Francis Journals, vol. 17(1), pages 25-33.
    2. Monica Billio & Massimiliano Caporin & Michele Gobbo, 2006. "Flexible Dynamic Conditional Correlation multivariate GARCH models for asset allocation," Applied Financial Economics Letters, Taylor and Francis Journals, vol. 2(2), pages 123-130, March.

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