Volatility Forecast Comparison Using Imperfect Volatility Proxies

By Patton Andrew J.
Journal of Econometrics (2011)

  • Andrew J. Patton

    Duke University

    USA

Created

September 23, 2013

Last update

June 20, 2016

Software

Matlab

Ranking

13

Visits

5106

Downloads

691

Description

This code compares volatility forecasts from two models (A and B). It produces the t-statistics from Diebold–Mariano–West tests of equal predictive accuracy. The null is expressed as follows H0: Loss(model A) - Loss(model B) = 0. The sign of the t-statistics indicates which forecast performs better for each loss function: a positive t-statistic indicates that model A forecast produces larger average loss than the model B forecast, while a negative sign indicates the opposite. The statistics are displayed for various values of the scale parameter b of the loss function (equation 24, page 252), chosen by the user. The cases b = 0 and b = −2 correspond to the MSE and QLIKE loss functions, respectively.

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