Access

You are not currently logged in.

Access your personal account or get JSTOR access through your library or other institution:

login

Log in to your personal account or through your institution.

If you need an accessible version of this item please contact JSTOR User Support

Correcting the Errors: Volatility Forecast Evaluation Using High-Frequency Data and Realized Volatilities

Torben G. Andersen, Tim Bollerslev and Nour Meddahi
Econometrica
Vol. 73, No. 1 (Jan., 2005), pp. 279-296
Published by: The Econometric Society
Stable URL: http://www.jstor.org/stable/3598946
Page Count: 18
  • Read Online (Free)
  • Download ($10.00)
  • Cite this Item
If you need an accessible version of this item please contact JSTOR User Support
Correcting the Errors: Volatility Forecast Evaluation Using High-Frequency Data and Realized Volatilities
Preview not available

Abstract

We develop general model-free adjustment procedures for the calculation of unbiased volatility loss functions based on practically feasible realized volatility benchmarks. The procedures, which exploit recent nonparametric asymptotic distributional results, are both easy-to-implement and highly accurate in empirically realistic situations. We also illustrate that properly accounting for the measurement errors in the volatility forecast evaluations reported in the existing literature can result in markedly higher estimates for the true degree of return volatility predictability.

Page Thumbnails

  • Thumbnail: Page 
279
    279
  • Thumbnail: Page 
280
    280
  • Thumbnail: Page 
281
    281
  • Thumbnail: Page 
282
    282
  • Thumbnail: Page 
283
    283
  • Thumbnail: Page 
284
    284
  • Thumbnail: Page 
285
    285
  • Thumbnail: Page 
286
    286
  • Thumbnail: Page 
287
    287
  • Thumbnail: Page 
288
    288
  • Thumbnail: Page 
289
    289
  • Thumbnail: Page 
290
    290
  • Thumbnail: Page 
291
    291
  • Thumbnail: Page 
292
    292
  • Thumbnail: Page 
293
    293
  • Thumbnail: Page 
294
    294
  • Thumbnail: Page 
295
    295
  • Thumbnail: Page 
296
    296