(ProQuest: ... denotes formulae omitted.)1. IntroductionApplications of Multi-Objective Optimization in banking has already been done by some researchers in the Technical University of Crete. They use their own Multiple Optimal Decision Analysis method, under the name of UTA (Figueira et al., 2005; Zopounidis, Pardalos, 2010). UTA group of methods uses linear programming techniques for optimizing a utility function associated with the preferences of a decision-maker. Variations of UTA are UTADIS and M.H.DIS for classification of alternatives or banks into two classes: healthy or bankrupt banks or firms (Dimitras et al., 1999; Doumpos et al., 2002; Gaganis et al., 2006), or into three classes: acceptable or healthy banks or firms, uncertain and unacceptable banks or firms (Zopounidis & Doumpos, 1999, 2002). Ioannidis et al. (2010) use the same methods but they add a decision tree classification, Euclidean distance to the k-nearest neighbors and stacked generalization. A multi-objective research on client-based variables has been done by Ginevicius & Podvezko (2008).A categorization of banks comprising major types of objectives forms the basis of this paper. A selection is made on the basis of a classification approach, known as CAMEL. CAMEL is very popular with scholars that do research in the areas of banking. It is an abbreviation for Capital adequacy, Asset quality, Management quality, Earnings and Liquidity. This categorization is used by the American Federal Reserve, FDIC (deposit insurance) and the OCC, Office of the Comptroller of the Currency (Podviezko & Ginevicius, 2010). The categorization comprises major types of objectives representing stability of banks. The well known international rating agency, Moody's Investors Inc., uses CAMEL-based objectives (Fanger, 2007).It has also been applied by Bongini et al. (2002), Thomson (1991), Arena (2008), Ozkan-Gunay & Ozkan (2007), Ginevicius & Podviezko (2011). Wheelock & Wilson (2000) and Cole & Gunther (1995) found that CAMEL-based variables strongly correlate with bank failures. Hirtle & Lopez (1999) found that CAMELbased examination of banks contain valuable information on bank condition for a 612 month period.Contrary to the micro-economic approach of CAMEL, another stream of thought focuses on a rather macro-economic way of thinking. Let us recall that micro-economics concerns an individual person, a firm or a government as owner or shareholder of a firm or as a receiver of taxes. On the contrary, macro-economics concerns the general economic welfare in a welfare economy (Pigou, 1950). Gonzalez & Hermosillo (1999) cite as macro-economic factors: cyclical output downturns, adverse terms of trade shocks, declines in asset prices, rising real interest rates, boom-bust cycles in inflation, credit expansion, losses of foreign exchange reserves and capital inflows. With the banking crises in Asian countries of 1996-97, Demirguc et al., (1998) and Hardy & Pazarbasioglu (1998) argue that these models missed these crises. We have not considered a macro-economic approach as the banks we investigate are registered in Lithuania and therefore are operating in the same macro-economic environment governed by the same Law on Banks (Seimas of the Republic of Lithuania, 2004) and the deposits made with these banks are insured by the same State Enterprise Deposit and Investment Insurance. Therefore branches of foreign banks, namely Danske Bank A/S and Nordea Bank Finland Plc are excluded as they are only branches, operating under Danish or Finnish law, respectively. They are registered in Lithuania only as branches, not as separate banks.In this paper, Lithuanian banks, as defined above, are ranked for the recession years 2008-2009 using multi-objective optimization. 2007 is taken as base year as the later years were seriously biased. The years 2008 and 2009 were characterized by a severe recession largely due to sub-prime and bank crisis problems1. …
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Oct 7, 2024
Sabina Račaitė + 1
Open Access
