IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this paper or follow this series

General to specific modelling of exchange rate volatility : a forecast evaluation

  • Luc Bauwens

    ()

  • Genaro Sucarrat

    ()

The general-to-specific (GETS) methodology is widely employed in the modelling of economic series, but less so in financial volatility modelling due to computational complexity when many explanatory variables are involved. This study proposes a simple way of avoiding this problem when the conditional mean can appropriately be restricted to zero, and undertakes an out-of-sample forecast evaluation of the methodology applied to the modelling of weekly exchange rate volatility. Our findings suggest that GETS specifications perform comparatively well in both ex post and ex ante forecasting as long as sufficient care is taken with respect to functional form and with respect to how the conditioning information is used. Also, our forecast comparison provides an example of a discrete time explanatory model being more accurate than realised volatility ex post in 1 step forecasting.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://e-archivo.uc3m.es/bitstream/10016/2591/1/we081810.pdf
Download Restriction: no

Paper provided by Universidad Carlos III, Departamento de Economía in its series Economics Working Papers with number we081810.

as
in new window

Length:
Date of creation: Apr 2008
Date of revision:
Handle: RePEc:cte:werepe:we081810
Contact details of provider: Postal: C./ Madrid, 126, 28903 Getafe (Madrid)
Phone: +34-91 6249594
Fax: +34-91 6249329
Web page: http://www.eco.uc3m.es
Email:


More information through EDIRC

References listed on IDEAS
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.:

as in new window
  1. Martin D.D. Evans & Richard K. Lyons, 1999. "Order Flow and Exchange Rate Dynamics," NBER Working Papers 7317, National Bureau of Economic Research, Inc.
  2. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 33(1), pages 125-132.
  3. Kevin D. Hoover & Stephen J. Perez, . "Data Mining Reconsidered: Encompassing And The General-To-Specific Approach To Specification Search," Department of Economics 97-27, California Davis - Department of Economics.
  4. Carlos Santos & David Hendry & Soren Johansen, 2008. "Automatic selection of indicators in a fully saturated regression," Computational Statistics, Springer, vol. 23(2), pages 317-335, April.
  5. Luc, BAUWENS & Dagfinn, RIME & Genaro, SUCARRAT, 2005. "Exchange Rate Volatility and the Mixture of Distribution Hypothesis," Discussion Papers (ECON - Département des Sciences Economiques) 2005043, Université catholique de Louvain, Département des Sciences Economiques.
  6. 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.
  7. 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 863-83, November.
  8. Ole E. Barndorff-Nielsen & Neil Shephard, 2000. "Econometric analysis of realised volatility and its use in estimating stochastic volatility models," Economics Papers 2001-W4, Economics Group, Nuffield College, University of Oxford, revised 05 Jul 2001.
  9. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-38, May.
  10. David Hendry & Hans-Martin Krolzig, 2003. "The Properties of Automatic Gets Modelling," Economics Series Working Papers 2003-W14, University of Oxford, Department of Economics.
  11. Jarque, Carlos M. & Bera, Anil K., 1980. "Efficient tests for normality, homoscedasticity and serial independence of regression residuals," Economics Letters, Elsevier, vol. 6(3), pages 255-259.
  12. Hendry, David F., 2003. "J. Denis Sargan And The Origins Of Lse Econometric Methodology," Econometric Theory, Cambridge University Press, vol. 19(03), pages 457-480, June.
  13. 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.
  14. Tim Bollerslev & Jeffrey M. Wooldridge, 1988. "Quasi-Maximum Likelihood Estimation of Dynamic Models with Time-Varying Covariances," Working papers 505, Massachusetts Institute of Technology (MIT), Department of Economics.
  15. David F. Hendry & Hans-Martin Krolzig, 2004. "We Ran One Regression," Economics Papers 2004-W17, Economics Group, Nuffield College, University of Oxford.
  16. Genaro Sucarrat, 2010. "Econometric reduction theory and philosophy," Journal of Economic Methodology, Taylor & Francis Journals, vol. 17(1), pages 53-75.
  17. Andersen, Torben G. & Bollerslev, Tim & Lange, Steve, 1999. "Forecasting financial market volatility: Sample frequency vis-a-vis forecast horizon," Journal of Empirical Finance, Elsevier, vol. 6(5), pages 457-477, December.
  18. Clive Granger & Allan Timmermann, 1999. "Data mining with local model specification uncertainty: a discussion of Hoover and Perez," Econometrics Journal, Royal Economic Society, vol. 2(2), pages 220-225.
  19. Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
  20. Jose A. Lopez, 1995. "Evaluating the predictive accuracy of volatility models," Research Paper 9524, Federal Reserve Bank of New York.
  21. Sucarrat, Genaro, 2008. "Forecast Evaluation of Explanatory Models of Financial Return Variability," Economics Discussion Papers 2008-18, Kiel Institute for the World Economy.
  22. Jacob A. Mincer & Victor Zarnowitz, 1969. "The Evaluation of Economic Forecasts," NBER Chapters, in: Economic Forecasts and Expectations: Analysis of Forecasting Behavior and Performance, pages 3-46 National Bureau of Economic Research, Inc.
  23. Eilev S. Jansen, 2002. "Statistical Issues in Macroeconomic Modelling-super-," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 29(2), pages 193-213.
  24. Jorion, Philippe, 1995. " Predicting Volatility in the Foreign Exchange Market," Journal of Finance, American Finance Association, vol. 50(2), pages 507-28, June.
  25. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2001. "Modeling and Forecasting Realized Volatility," Center for Financial Institutions Working Papers 01-01, Wharton School Center for Financial Institutions, University of Pennsylvania.
  26. Hansen, Peter Reinhard & Lunde, Asger, 2006. "Consistent ranking of volatility models," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 97-121.
  27. Meddahi, Nour & Mykland, Per & Shephard, Neil, 2011. "Realized Volatility," Journal of Econometrics, Elsevier, vol. 160(1), pages 1-1, January.
  28. Torben G. Andersen & Tim Bollerslev & Nour Meddahi, 2005. "Correcting the Errors: Volatility Forecast Evaluation Using High-Frequency Data and Realized Volatilities," Econometrica, Econometric Society, vol. 73(1), pages 279-296, 01.
  29. Hendry, David F. & Richard, Jean-Francois, 1982. "On the formulation of empirical models in dynamic econometrics," Journal of Econometrics, Elsevier, vol. 20(1), pages 3-33, October.
  30. Andersen, Torben G & Bollerslev, Tim, 1998. "Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 885-905, November.
  31. Gonzalez-Rivera, Gloria & Lee, Tae-Hwy & Mishra, Santosh, 2004. "Forecasting volatility: A reality check based on option pricing, utility function, value-at-risk, and predictive likelihood," International Journal of Forecasting, Elsevier, vol. 20(4), pages 629-645.
  32. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, Elsevier.
  33. Michael P. Clements & David F. Hendry, 2005. "Evaluating a Model by Forecast Performance," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(s1), pages 931-956, December.
  34. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
  35. Hendry, David F., 1995. "Dynamic Econometrics," OUP Catalogue, Oxford University Press, number 9780198283164, March.
  36. Gilbert, Christopher L, 1989. "LSE and the British Approach to Time Series Econometrics," Oxford Economic Papers, Oxford University Press, vol. 41(1), pages 108-28, January.
  37. Lovell, Michael C, 1983. "Data Mining," The Review of Economics and Statistics, MIT Press, vol. 65(1), pages 1-12, February.
  38. David F. Hendry & Hans-Martin Krolzig, 1999. "Improving on 'Data mining reconsidered' by K.D. Hoover and S.J. Perez," Econometrics Journal, Royal Economic Society, vol. 2(2), pages 202-219.
  39. McAleer, Michael, 2005. "Automated Inference And Learning In Modeling Financial Volatility," Econometric Theory, Cambridge University Press, vol. 21(01), pages 232-261, February.
  40. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
  41. Hendry, David F., 1997. "On congruent econometric relations : A comment," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 47(1), pages 163-190, December.
  42. Andersen T. G & Bollerslev T. & Diebold F. X & Labys P., 2001. "The Distribution of Realized Exchange Rate Volatility," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 42-55, March.
  43. Halbert White, 2000. "A Reality Check for Data Snooping," Econometrica, Econometric Society, vol. 68(5), pages 1097-1126, September.
  44. 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.
  45. Hansen, Peter Reinhard, 2005. "A Test for Superior Predictive Ability," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 365-380, October.
  46. Julia Campos & Neil R. Ericsson & David F. Hendry, 2005. "General-to-specific modeling: an overview and selected bibliography," International Finance Discussion Papers 838, Board of Governors of the Federal Reserve System (U.S.).
  47. Ser-Huang Poon & Clive W.J. Granger, 2003. "Forecasting Volatility in Financial Markets: A Review," Journal of Economic Literature, American Economic Association, vol. 41(2), pages 478-539, June.
  48. Sucarrat, Genaro, 2009. "Forecast Evaluation of Explanatory Models of Financial Variability," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy, vol. 3, pages 1-33.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:cte:werepe:we081810. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ()

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.