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FUZZY ECONOMIC REVIEW

ISSN (print) 1136-0593 · ISSN (online) 2445-4192

FUZZY ECONOMIC REVIEW, Volume XX

ROUGH SETS AND DISCRIMINANT ANALYSIS TECHNIQUES FOR BUSINESS DEFAULT FORECASTING

José David Cabedo. Department of Finance and Accounting, Universitat Jaume I

José Miguel Tirado. Department of Finance and Accounting, Universitat Jaume I

One area for the application of rough sets theory is business failure prediction. Taking a set of financial ratios as the starting point, the decision rules generated from the in-the-sample set of companies can be used to forecast the default/healthy situation of the out-of-the-sample set companies. Some companies, however, cannot…
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FUZZY SIMILARITY AND COUNTERFACTUALS IN THE ASSESSMENT OF DEFAULT RISK: THE EUROZONE CRISIS AND THE ARGENTINEAN SOLUTION

Jorge Pazzi. Economics Department, Universidad Nacional del Sur, 12 de Octubre y San Juan, (8000) Bahia Blanca, Argentina

Fernando Tohmé. Economics Department, Universidad Nacional del Sur, 12 de Octubre y San Juan, (8000) Bahia Blanca, Argentina

We present an approach, based on the notion of fuzzy similarity, to the comparison of economies under default risk. We run a counterfactual analysis of the perspectives of the most troubled countries in the Eurozone compared with Argentina in 2001. This allows us to assess the possibility that these economies…
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ANALYSIS OF RECOMMENDATIONS ABOUT EXPECTED PRICES OF IBEX 35 USING FUZZY NUMBERS

Mario Ravioli. Department of Business Management. Faculty of Business and Economics. Universitat Rovira i Virgili

Laura Fabregat-Aibar. Department of Business Management. Faculty of Business and Economics. Universitat Rovira i Virgili

Predicting the trend of prices of shares is a recurring theme in the financial literature. The predictability allows us to anticipate market movements and therefore to generate higher returns than the market average. Much of the Economics and Finance media include expert predictions on the evolution of prices, at least…
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HOW DO DIFFERENT TIME SPANS AFFECT THE PREDICTION ACCURACY OF BUSINESS FAILURE?

X. Càmara-Turull. Department of Business Management. Faculty of Business and Economics. Universitat Rovira i Virgili

Fernández Izquierdo. Department of Finance and Accounting. Faculty of Law and Economics. Universitat Jaume I

M.T. Sorrosal Forradellas. Department of Business Management. Faculty of Business and Economics. Universitat Rovira i Virgili

The prediction of business failure has been widely studied by many authors. Most of the studies focused on improve the results by applying new methodologies or by using more suitable financial information. This study aims to analyze the impact of the input data timeframe on the prediction accuracy of business…
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ANALYSIS OF BETA COEFICIENTS IN THE BRAZILIAN STOCK MARKET USING FUZZY LINEAR REGRESSION METHODOLOGY

Yanina Laumann. Department of Business Management, Faculty of Business and Economics, Rovira i Virgili University.

With the aim of using all the information provided by the market to determine the systematic risk, we intend to continue the study of Terceño et al. (2011, 2014) using fuzzy linear regression to calculate the sectors betas of the Brazilian Stock Market. The analysis with fuzzy regression can be…
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A METHOD FOR THE EVALUATION AND SELECTION OF AN APPROPRIATE FUZZY IMPLICATION BY USING STATISTICAL DATA

George N Botzoris. Assistant Professor, Department of Civil Engineering, Democritus University of Thrace, Xanthi, Greece.

Kyriakos Papadopoulos. Assistant Professor, American University of the Middle East, Egaila, Kuwait.

Basil K. Papadopoulos. c Professor, Department of Civil Engineering, Democritus University of Thrace, Xanthi, Greece.

In classic logic, there exists an implication of the form p->q=n(p) v q (where n(p) is the negation of p and  the maximum). If we consider the fact that the propositions p and q take only the values 0 and 1, then the values of the classic implication are…
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