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A DSS for Designing an MCDA Study with Application in Performance Evaluation of Forecasting Models

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Financial Decision Aid Using Multiple Criteria

Part of the book series: Multiple Criteria Decision Making ((MCDM))

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Abstract

The purpose of this Chapter is to propose a decision support system (DSS) for designing a multicriteria decision analysis (MCDA) study. The proposed DSS is a revised MCDA methodological framework, which consists of a sequential decision making process with feedback adjustment mechanisms and validation sub-processes. We also provide guidelines on how to operationalize it. For illustration purposes, we adapt the proposed DSS to address the problem of performance evaluation of competing forecasting models under multiple criteria, where the variable to forecast is the price of crude oil.

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Notes

  1. 1.

    For more details on MCDA problematics, the reader is referred to Roy (1985, 1996) and Belton and Stewart (2001).

  2. 2.

    For more details on types of criteria, the reader is referred to Roy (1985) and Vincke (1992).

  3. 3.

    For more details on preference structures, the reader is referred to Roy (1977, 1985), Perny and Roy (1992), Vincke (1992, 2001), Tsoukiàs and Vincke (1992, 1997), and Fishburn (1999).

  4. 4.

    For more details on types of orders, the reader is referred to Roy and Vincke (1984, 1987), Fishburn (1985, 1997) and Tsoukiàs and Vincke (2003).

  5. 5.

    For more details on the social choice paradigm, the reader is referred to Arrow (1963), Black (1958), Arrow and Raynaud (1986), Fishburn (1973) and Bouyssou et al. (2006).

  6. 6.

    For more details on the conjoint measurement paradigm, the reader is referred to Raiffa (1969, 1970), Edwards (1971), and Keeney and Raiffa (1976).

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Acknowledgements

Prof. Perez-Gladish would like to thank the Spanish Ministry of Education, Culture and Sport for its financial support within the framework of its International Mobility Program for senior researchers “Salvador de Madariaga” (PRX16-0169).

We gratefully acknowledge the EPSRC for funding this work through its financial support of the ``Low carbon jet fuel through integration of novel technologies for co-valorisation of CO2 and biomass'' (EPSRC Reference: EP/N009924/1). The standard disclaimer applies.

Author information

Authors and Affiliations

  1. University of Edinburgh, Business School, Edinburgh, UK

    Jamal Ouenniche

  2. School of Social Sciences, Heriot-Watt University, Edinburgh, UK

    Bing Xu

  3. Facultad de Economía y Empresa, Departamento de Economía Cuantitativa, Universidad de Oviedo, Oviedo, Spain

    Blanca Pérez-Gladish

Authors
  1. Jamal Ouenniche
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  2. Bing Xu
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  3. Blanca Pérez-Gladish
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Correspondence to Blanca Pérez-Gladish .

Editor information

Editors and Affiliations

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

    Hatem Masri

  2. Department of Quantitative Economics, University of Oviedo, Oviedo, Asturias, Spain

    Blanca Pérez-Gladish

  3. School of Production Engineering and Management, Technical University of Crete, Chania, Greece

    Constantin Zopounidis

Appendix

Appendix

Table 1 Unidimensional rankings of competing forecasting models
Full size table
Table 2 ELECTRE III ranking of competing forecasting models. Weight vector (50,30,20)
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Table 3 PROMETHEE I ranking of competing forecasting models. Weight vector (50,30,20)
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Table 4 PROMETHEE II ranking of competing forecasting models. Weight vector (50,30,20)
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Ouenniche, J., Xu, B., Pérez-Gladish, B. (2018). A DSS for Designing an MCDA Study with Application in Performance Evaluation of Forecasting Models. In: Masri, H., Pérez-Gladish, B., Zopounidis, C. (eds) Financial Decision Aid Using Multiple Criteria. Multiple Criteria Decision Making. Springer, Cham. https://doi.org/10.1007/978-3-319-68876-3_2

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