Decision Sciences Journal
Volume 32, Number 2
Spring 2001
Multicriteria Preference Disaggregation for Classification
Problems with an Application to Global Investing Risk
Michael Doumpos
Technical University of Crete, Dept. of Production Engineering
& Management,
Financial Engineering Laboratory, University Campus, 73100 Chania,
Greece
Stelios H. Zanakis
Florida International University, Decision Sciences & Information
Systems Department, College of Business Administration, Miami,
FL 33199, USA
Constantin Zopounidis
Technical University of Crete, Dept. of Production Engineering
& Management,
Financial Engineering Laboratory, University Campus, 73100 Chania,
Greece
Abstract. Mathematical programming and multicriteria
approaches to classification and discrimination are reviewed,
with an emphasis on preference disaggregation. The latter include
the UTADIS family and a new method, Multigroup Hierarchical DIScrimination
(MHDIS). They are used to assess investing risk in 51 countries
that have stock exchanges, according to 27 criteria. These criteria
include quantitative and qualitative measures of market risk
(volatility and currency fluctuations); range of investment opportunities;
quantity and quality on market information; investor protection
(security regulations treatment of minority shareholders); and
administrative “headaches” (custody, settlement, and
taxes). The model parameters are determined so that the results
best match the risk level assigned to those countries by experienced
international investment managers commissioned by The Wall Street
Journal. Among the six evaluation models developed, one (MHDIS)
classifies correctly all countries into the appropriate groups.
Thus, this model is able to reproduce consistently the evaluation
of the expert investment analysts. The most significant criteria
and their weights for assessing global risk investing are also
presented, along with their marginal utilities, leading to identifiers
of risk groups and global utilities portraying the strength of
each country’s risk classification. The same method, MHDIS,
outperformed the other five methods in a 10-fold validation experiment.
These results are promising for the study of emerging new markets
in fast-growing regions, which present fertile areas for investment
growth but also an abundance of obvious and hidden risks. The
methods presented here can also be used in other real-world sorting
and classification problems, such as country risk, bankruptcies,
and credit scoring.
Subject Areas: Classification, Discriminant Analysis,
Financial DSS, Globalization, Investment Risk, Judgment Analysis,
Mathematical Programming, Multicriteria Decision Making, and
Regression. |