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Adjusted Evaluation Measures for Asymmetrically Important Data

Author

Listed:
  • Alex Karagrigoriou

    (University of the Aegean)

  • George-Jason Siouris

    (University of the Aegean)

  • Despoina Skilogianni

    (University of the Aegean)

Abstract

In this paper we introduce adjustments for standard evaluation measures appropriate for the analysis of data with asymmetrical importance. In risk analysis, it is understood that the returns of an asset do not all provide the same amount of information. This asymmetry of information is crucial for choosing the most appropriate model and evaluating its forecasting ability. In risk analysis, measures like value at risk (VaR) and expected shortfall (ES) concentrate on the left tail of the distribution of returns so that failures in fitting a model on the right tail are not important. Therefore, when we estimate the VaR of an asset, the days of violations are more important than the days of non-violations. The proposed adjustments take into consideration the asymmetry in importance and are filling the gap in the theory of evaluation of percentiles measures. The measures are divided into fixed partition, based on prior information or the goal of forecasting, and non fixed partition, based on the time proximity of the model failure. The performance of the proposed measures is illustrated with the use of a stock from the industrial metals and minerals index of the American Stock Exchange (NYSE MKT), as well as a warrant, from the Athens Exchange (ATHEX).

Suggested Citation

  • Alex Karagrigoriou & George-Jason Siouris & Despoina Skilogianni, 2019. "Adjusted Evaluation Measures for Asymmetrically Important Data," Econometric Research in Finance, SGH Warsaw School of Economics, Collegium of Economic Analysis, vol. 4(1), pages 41-66, June.
    • Handle: RePEc:sgh:erfinj:v:4:y:2019:i:1:p:41-66
    DOI: 10.33119/ERFIN.2019.4.1.3
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    PVaR; violation ratios; low price effect; low price correction; backtesting; evaluation measures;
    All these keywords.

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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