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

Evaluating the predictive accuracy of volatility models

  • Jose A. Lopez

The volatility forecast evaluations most meaningful to forecast users are those conducted under economically relevant loss functions. Although several such loss functions are proposed in the literature, their implied economic costs are of interest only to specific types of volatility forecast users. A forecast evaluation framework that incorporates a more general class of economic loss functions is proposed. A user's loss function specifies the three key elements of the evaluation framework: the economic events to be forecast, the criterion with which to evaluate these forecasts, and the subsets of the forecasts of particular interest. Volatility forecasts are transformed into probability forecasts of the specified events, and the probability forecasts are evaluated using statistical criteria, such as probability scoring rules, tailored to the user's interests. An empirical example using exchange rates illustrates the procedure and confirms that the choice of loss function directly affects the forecast evaluation results.

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://www.newyorkfed.org/research/staff_reports/research_papers/9524.html
Download Restriction: no

File URL: http://www.newyorkfed.org/research/staff_reports/research_papers/9524.pdf
Download Restriction: no

Paper provided by Federal Reserve Bank of New York in its series Research Paper with number 9524.

as
in new window

Length:
Date of creation: 1995
Date of revision:
Handle: RePEc:fip:fednrp:9524
Contact details of provider: Postal: 33 Liberty Street, New York, NY 10045-0001
Web page: http://www.newyorkfed.org/
Email:


More information through EDIRC

Order Information: Email:


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. Bollerslev, Tim & Ghysels, Eric, 1996. "Periodic Autoregressive Conditional Heteroscedasticity," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(2), pages 139-51, April.
  2. 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.
  3. Diebold & Lopez, . "Modeling Volatility Dynamics," Home Pages _062, University of Pennsylvania.
  4. Benoit Mandelbrot, 1963. "The Variation of Certain Speculative Prices," The Journal of Business, University of Chicago Press, vol. 36, pages 394.
  5. Stockman, Alan C., 1987. "Economic theory and exchange rate forecasts," International Journal of Forecasting, Elsevier, vol. 3(1), pages 3-15.
  6. West, Kenneth D. & Cho, Dongchul, 1995. "The predictive ability of several models of exchange rate volatility," Journal of Econometrics, Elsevier, vol. 69(2), pages 367-391, October.
  7. Harvey, Andrew & Ruiz, Esther & Shephard, Neil, 1994. "Multivariate Stochastic Variance Models," Review of Economic Studies, Wiley Blackwell, vol. 61(2), pages 247-64, April.
  8. 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.
  9. Kroner, Kenneth F. & Kneafsey, Devin P. & Claessens, Stijn & DEC, 1993. "Forecasting volatility in commodity markets," Policy Research Working Paper Series 1226, The World Bank.
  10. Benjamin M. Friedman & Kenneth N. Kuttner, 1988. "Time-Varying Risk Perceptions and the Pricing of Risky Assets," NBER Working Papers 2694, National Bureau of Economic Research, Inc.
  11. 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.
  12. repec:att:wimass:9417 is not listed on IDEAS
  13. Lee, Keun Yeong, 1991. "Are the GARCH models best in out-of-sample performance?," Economics Letters, Elsevier, vol. 37(3), pages 305-308, November.
  14. Pagan, Adrian R. & Schwert, G. William, 1990. "Alternative models for conditional stock volatility," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 267-290.
  15. Jacquier, Eric & Polson, Nicholas G & Rossi, Peter E, 1994. "Bayesian Analysis of Stochastic Volatility Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(4), pages 371-89, October.
  16. Taylor, Stephen J., 1987. "Forecasting the volatility of currency exchange rates," International Journal of Forecasting, Elsevier, vol. 3(1), pages 159-170.
  17. Ray C. Fair, 1993. "Estimating Event Probabilities from Macroeconometric Models Using Stochastic Simulation," NBER Chapters, in: Business Cycles, Indicators and Forecasting, pages 157-178 National Bureau of Economic Research, Inc.
  18. Schwert, G William, 1989. " Why Does Stock Market Volatility Change over Time?," Journal of Finance, American Finance Association, vol. 44(5), pages 1115-53, December.
  19. Ray C. Fair, 1991. "Estimating Event Probabilities from Macroeconomic Models Using Stochastic Simulation," NBER Technical Working Papers 0111, National Bureau of Economic Research, Inc.
  20. 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.
  21. Francis X. Diebold & Robert S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
  22. Kim, Kiwhan & Schmidt, Peter, 1993. "Unit root tests with conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 59(3), pages 287-300, October.
  23. Granger, C. W. J. & White, Halbert & Kamstra, Mark, 1989. "Interval forecasting : An analysis based upon ARCH-quantile estimators," Journal of Econometrics, Elsevier, vol. 40(1), pages 87-96, January.
  24. Robert F. Engle & Victor K. Ng, 1991. "Measuring and Testing the Impact of News on Volatility," NBER Working Papers 3681, National Bureau of Economic Research, Inc.
  25. Engle, Robert F & Gonzalez-Rivera, Gloria, 1991. "Semiparametric ARCH Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(4), pages 345-59, October.
  26. John F. Geweke, 1994. "Bayesian comparison of econometric models," Working Papers 532, Federal Reserve Bank of Minneapolis.
  27. Kenneth D. West, 1994. "Asymptotic Inference About Predictive Ability," Macroeconomics 9410002, EconWPA.
  28. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
  29. Francis X. Diebold & Glenn D. Rudebusch, 1987. "Scoring the leading indicators," Special Studies Papers 206, Board of Governors of the Federal Reserve System (U.S.).
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:fip:fednrp:9524. 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: (Amy Farber)

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.