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Volatility forecasts evaluation and comparison

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Abstract This article surveys the most important developments in volatility forecast comparison and model selection. We review a number of evaluation methods and testing procedures for predictive accuracy based on statistical loss functions. We also review recent contributions on the admissible form of loss functions ensuring consistency of the ordering when forecast performances are evaluated with respect to an imperfect volatility proxy. The techniques discussed are illustrated using artificial and EUR/USD exchange rate data. WIREs Comp Stat 2012, 4:1–12. doi: 10.1002/wics.190 This article is categorized under: Statistical Models > Time Series Models Data: Types and Structure > Time Series, Stochastic Processes, and Functional Data Applications of Computational Statistics > Computational Finance

EUR/USD exchange rate returns in percentage on the period January 1999 to April 2011.

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Ranking implied by Log‐MSE and MSE‐SD. Ranking based on avg. performances (left) and avg. loss differentials from nagarch (right).

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Ranking implied by MSE and QLIKE. Ranking based on avg. performances (left) and avg. loss differentials from nagarch (right).

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Statistical Models > Time Series Models
Data: Types and Structure > Time Series, Stochastic Processes, and Functional Data
Applications of Computational Statistics > Computational Finance

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