Comparing forecast performances among volatility estimation methods in the pricing of european type currency options of USD-TL and Euro-TL
AbstractBy using the daily values of USD-TL and Euro-TL denominated European call and put option contracts, which are traded in the over-the-counter market, this study investigates whether there is a significant difference among the premiums of the contracts forecasted by historical volatility, EWMA(l =0.94 andl =0.97), GARCH(1,1) and EGARCH( p, q) models. In order to test the significance of the difference among particular volatility series forecasted by these different methods, test techniques suggested by Diebold and Mariano (1995) and West (1996) are used. Accordingly, the findings indicate that the differences in the pricing of the USD-TL and Euro-TL denominated call-put option contracts are statistically significant for some volatility forecasting methods.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 34369.
Date of creation: 01 Jan 2011
Date of revision:
Option Pricing; European Type Vanilla Options; Historical Volatility; Volatility Estimation Models; Forecast Comparison;
Find related papers by JEL classification:
- G19 - Financial Economics - - General Financial Markets - - - Other
This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-11-07 (All new papers)
- NEP-FOR-2011-11-07 (Forecasting)
- NEP-ORE-2011-11-07 (Operations Research)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Bollerslev, Tim, 1986.
"Generalized autoregressive conditional heteroskedasticity,"
Journal of Econometrics,
Elsevier, vol. 31(3), pages 307-327, April.
- Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
- 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.
- Benavides, Guillermo & Capistrán, Carlos, 2012.
"Forecasting exchange rate volatility: The superior performance of conditional combinations of time series and option implied forecasts,"
Journal of Empirical Finance,
Elsevier, vol. 19(5), pages 627-639.
- Guillermo Benavides & Carlos Capistrán, 2009. "Forecasting Exchange Rate Volatility: The Superior Performance of Conditional Combinations of Time Series and Option Implied Forecasts," Working Papers 2009-01, Banco de México.
- Pagan, Adrian R. & Schwert, G. William, 1990.
"Alternative models for conditional stock volatility,"
Journal of Econometrics,
Elsevier, vol. 45(1-2), pages 267-290.
- Adrian R. Pagan & G. William Schwert, 1990. "Alternative Models For Conditional Stock Volatility," NBER Working Papers 2955, National Bureau of Economic Research, Inc.
- Pagan, A.R. & Schwert, G.W., 1989. "Alternative Models For Conditional Stock Volatility," Papers 89-02, Rochester, Business - General.
- 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.
- Asger Lunde & Peter Reinhard Hansen, 2001. "A Forecast Comparison of Volatility Models: Does Anything Beat a GARCH(1,1)?," Working Papers 2001-04, Brown University, Department of Economics.
- Chesney, Marc & Scott, Louis, 1989. "Pricing European Currency Options: A Comparison of the Modified Black-Scholes Model and a Random Variance Model," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 24(03), pages 267-284, September.
- Jose A. Lopez, 1995.
"Evaluating the predictive accuracy of volatility models,"
9524, Federal Reserve Bank of New York.
- Lopez, Jose A, 2001. "Evaluating the Predictive Accuracy of Volatility Models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 20(2), pages 87-109, March.
- Ercan Balaban & Asli Bayar & Robert Faff, 2006. "Forecasting stock market volatility: Further international evidence," The European Journal of Finance, Taylor & Francis Journals, vol. 12(2), pages 171-188.
- Clark, Todd E. & West, Kenneth D., 2007.
"Approximately normal tests for equal predictive accuracy in nested models,"
Journal of Econometrics,
Elsevier, vol. 138(1), pages 291-311, May.
- Todd E. Clark & Kenneth D. West, 2005. "Approximately normal tests for equal predictive accuracy in nested models," Research Working Paper RWP 05-05, Federal Reserve Bank of Kansas City.
- Kenneth D. West & Todd Clark, 2006. "Approximately Normal Tests for Equal Predictive Accuracy in Nested Models," NBER Technical Working Papers 0326, National Bureau of Economic Research, Inc.
- Muradoglu, Yaz Gulnur & Metin, Kivilcim, 1996. "Efficiency of the Turkish Stock Exchange with respect to monetary variables: A cointegration analysis," European Journal of Operational Research, Elsevier, vol. 90(3), pages 566-576, May.
- 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.
- Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-70, March.
- repec:wop:humbsf:2001-83 is not listed on IDEAS
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