Yetkin ÇINAR

Baskınlık ve Sosyal Seçim Kurallarına Bağlı Çok Kriterli Modelleme: Hisse Senedi Seçimi Problemi için bir Karar Destek Sistemi Önerisi

Çok kriterli sıralama veya seçim problemi, çağımızda alternatif sayısındaki artış nedeniyle daha da karmaşıklaşmıştır. Telafi edici olarak anılan çok kriterli karar yöntemleri, kriterler için “ağırlık” bilgisinin elde edilmesini ve alternatiflerin kriterlere göre alacağı değerler için hassas (oransal) ölçümler yapılmasını gerektirirler. Örneğin karar vericiden bunun için alternatif sayısına bağlı olarak yüzlerce ikili karşılaştırma yapması talep edilebilir. Bu nedenle bu yöntemlerin çoğu, sadece az sayıda alternatif içeren ve sayısal ölçüm değerleri anlamlı derecede hassas problemler için uygundur. Büyük alternatif kümeleri söz konusu olduğunda daha az bilgi gerektiren, alternatifler arasındaki baskınlık ilişkileri temeline dayalı basit yöntemleri kullanmak iyi bir yoldur. Klasik-sosyal seçim teorisi, telafi edici olmayan çok-kriterli modeller ve bunların çok aşamalı biçimleri de bu problemin çözümünde uygun bir altyapı sunar. Böyle bir metodolojinin gerçek veri kümeleri üzerinde kullanıldığı çalışmaların azlığı nedeniyle yapılan bu çalışmada, yöntemlerin Borsa İstanbul’da (BİST) hisse senedi seçim ve sıralama problemine uygulanabilirliği gösterilmiş; benzer problemlerde kullanımları için bir Karar Destek Sistemi önerilmiştir.

Multi Criterial Modelling based on Dominance and Social Choice Rules: A DSS Proposal for Stock Selection Problem

The problem of multicriterial ranking or choice has become more complicated because of the existence of large number of available alternatives, in the new era. The compensatory methods require to determine criteria “weights” and to make exact value or utility estimates for the alternatives w.r.t. criteria. For this aim, sometimes they demand decision maker to make hundreds of pairwise comparisons between alternatives. Therefore, most of them are only applicable for the problems consist of small sets of alternatives and precise measurements. For large sets, using simple procedures that require less information is a suitable way. Such techniques stem from the classical -social- choice theory, non-compensatory multicriterial models and their multistage structures. Since the studies that employ these methods on real data sets are very rare, this study illustrates their applicability on the stock selection and ranking problem in Istanbul Stock Exchange (ISE), Turkey. A DSS is proposed for their usage on similar problems.

Keywords:

Multi Criteria Decision Making, Dominance Relations, Social Choice Models Stock Selection,

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