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Ranking econometric techniques using geometrical Benefit of Doubt

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Abstract

A large part of economies around the world rely on stock markets. To predict stock prices or commodities, econometric techniques are used. Analysts choose the suitable econometric technique according to error measures which may create confusion, especially in the case where there is no preference amongst error measures. Therefore, there is no unique score to rank econometric techniques based on multiple error measures. To bridge this gap, we propose, a MCDM like methodology [geometrical Benefit of Doubt (BoD)] that considers econometric techniques as alternatives and error measures as criteria. A real application with 194 econometric techniques and 8 error measures is presented. The efficiency scores derived from geometrical BoD model provide better discrimination and experiemental results indicate that ARMA and ARCH models are ranked higher. The proposed geometrical BoD model is compared to similar geometrical MCDM formulations.

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Authors and Affiliations

  1. College of Business Administration, University of Bahrain, Sakhir, Kingdom of Bahrain

    Hatem Masri

  2. Department of Business Administration, University of Macedonia, 546 36, Thessaloniki, Greece

    Konstantinos Petridis

  3. Department of Applied Informatics, University of Macedonia, 546 36, Thessaloniki, Greece

    Nikolaos E. Petridis

  4. AI Data Science and Business Area of Excellence, Neoma Business School, Mont-Saint-Aignan, France

    Fouad Ben Abdelaziz

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  1. Konstantinos Petridis
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  2. Nikolaos E. Petridis
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  3. Fouad Ben Abdelaziz
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  4. Hatem Masri
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Correspondence to Hatem Masri.

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Petridis, K., Petridis, N.E., Abdelaziz, F.B. et al. Ranking econometric techniques using geometrical Benefit of Doubt. Ann Oper Res 330, 411–430 (2023). https://doi.org/10.1007/s10479-022-04573-y

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