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Volatility Forecast Comparison using Imperfect Volatility Proxies

  • Andrew Patton

    (Duke University)

The use of a conditionally unbiased, but imperfect, volatility proxy can lead to undesirable outcomes in standard methods for comparing conditional variance forecasts. We derive necessary and sufficient conditions on functional form of the loss function for the ranking of competing volatility forecasts to be robust to the presence of noise in the volatility proxy, and derive some interesting special cases of this class of “robust” loss functions. We motivate the theory with analytical results on the distortions caused by some widely-used loss functions, when used with standard volatility proxies such as squared returns, the intra-daily range or realised volatility. The methods are illustrated with an application to the volatility of returns on IBM over the period 1993 to 2003.

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File URL: http://www.qfrc.uts.edu.au/research/research_papers/rp175.pdf
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Paper provided by Quantitative Finance Research Centre, University of Technology, Sydney in its series Research Paper Series with number 175.

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Length: 40 pages
Date of creation: 01 May 2006
Date of revision:
Publication status: Published as: Patton, A., 2011, "Volatility Forecast Comparison using Imperfect Volatility Proxies", Journal of Econometrics, 160(1), 246-256.
Handle: RePEc:uts:rpaper:175
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