FUZZY LOGIC APPLICATION IN EVALUATING FINANCIAL PERFORMANCE: A CASE STUDY OF SERVICES SECTOR IN MALAYSIA

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1 Australian Journal of Business and Economic Studies Volume 1 No. 1 March 2015 FUZZY LOGIC APPLICATION IN EVALUATING FINANCIAL PERFORMANCE: A CASE STUDY OF SERVICES SECTOR IN MALAYSIA Norasyikin Abdullah Fahami, Zati Halwani Abd. Rahim, Farah Waheeda Azhar, Hilwana Abd. Karim MARA University of Technology (Perak), Malaysia ABSTRACT This paper aims to evaluate financial performance of companies from services sector in Malaysia using fuzzy logic approach. Financial data of 22 companies in 2013 are retrieved from Datastream. For the methodology there are three steps involved as in research by Tavakkoli et al (2010) whereby the ultimate finding is the ranking of the companies. The ranking will suggest the investor on which companies to invest based on their financial performance. The results from this research are found to be consistent with the analysis by various investment agencies obtained from the Datastream. Thus, this approach can be used as an alternative to the traditional valuation that has been used before. JEL Classifications: G11, C02 Keywords: financial performance, fuzzy logic, financial ratios Corresponding Author s Address: syikin109@perak.uitm.edu.my INTRODUCTION Investment plays an important role in the life of a person or a company as it means creating more wealth in the future. In finance, investment means purchasing financial asset with the idea that the asset will generate positive return in the future through price appreciation or being sold at the higher price as compared to buying price. The financial assets can be in terms of bonds, shares and real estate property. Shares can be defined as a security that signifies ownership in a corporation which enables the shareholder to claim on company s assets and earnings. While ownership depends on how much shares a person has relative to number of shares outstanding. The profit from shares investment is derived in two ways; dividend received and capital gain which actually selling the shares higher than its buying price. Historically, shares or equity investment has outperformed other kinds of investment in the long run. Investing in share or stock market does not promise big gains unless the investors know the strategy to pick up good stock in their portfolio. The world most widely used strategies are fundamental analysis and technical analysis. Both analyses are rather different but at the end the purpose is to find the worth of the company and decide on which company to invest in. Fundamental analysis involved valuation of a stock based on the information about the economy, industry and company itself. Therefore financial statements are being analyzed using financial tool or commonly known as financial ratios to assess the performance of the corporation. The goal is to find the intrinsic value (true value) of the stock and compare to the value being traded in the marketplace. The rule of decision suggests that one should purchase the share if the intrinsic value is more that its market price and vice versa. On the other hand, technical analysis (also refers to chart analysis) is the study on share price using price charts to forecast future price direction. It is more on the short-term strategy as opposed to fundamental analysis which is meant for long-term strategy. However, Tavakkoli et al (2010) have used different method to evaluate financial performance of a corporation in the analysis. They used fuzzy logic approach to rank the companies with the utilization of financial ratios as factor analysis. The authors conclude the best companies and founds that their analysis were consistent with the financial experts in their home country. Another related research is by Wei, S. (2010), Othman et al (2010) and Othman et al (2012). Financial performance of a company can be analyzed using financial ratios. Gitman and Madura (2001) have divided financial ratios into five basic categories; liquidity ratio, activity ratio, debt ratio, profitability ratio and market ratio. And, some of these ratios are being used as factor analysis in the previous studies. In Malaysia, shares are traded in Bursa Malaysia Stock Exchange where all companies are listed under either Main (for established companies) or ACE market (for technology and highgrowth companies). According to Economic Report 2013/2014 by Bank Negara Malaysia, GDP has expanded by 4.7% in 2013 which was below than 2012 s GDP as it recorded at 5.6% for that year. Growth has been 69

2 driven by services sector particularly, wholesale and retail trade due to strong households spending. The increment also supported by higher sales at departmental store and hypermarket. According to Feldman and Treleavan (1994) many Japanese firms used fuzzy logic approach for the portfolio management. Thus, this paper aims to evaluate financial performance of public-listed companies under services sector in Malaysia using fuzzy logic approach. Another objective of this paper is to recommend the investors on which companies to invest in according to the ranking result. The remainder of this paper is divided into four sections. Section 2 describes on the previous literature; Section 3 briefs on the data and methodology; Section 4 reports on the findings; Section 5 discusses the results and Section 5 ends the paper with a brief discussion on the conclusion and future research directions. LITERATURE REVIEW Financial Ratios as a Tool of Measurement Financial ratios are designed to evaluate financial statement. Financial ratios provide important information for both investors and analysts to identify the position and productivity of the companies within the industries for specific period of time (Gallizo & Salvador, 2003).Ratio analysis involved comparison of one company to another company in the same industry Therefore, an accurate evaluation is critical. The tradition measurement known as accounting based financial performance (AFP) consists of liquidity ratio, financial leverage ratio, profitability ratio, activity ratio and growth ratio is a mechanism to compare and evaluate the financial performance of companies (Yalcin 2012). Fuzzy Logic Lotfi Zadeh introduced fuzzy logic in 1960s as a tool or model to solve the ensured of natural language. According to Zadeh (1965) fuzzy logic theory should not focus on a single theory. Fuzzy logic focused on the process of fuzzification as practice to generalize any specific theory from a crisp (discrete) to a continuous form. Evaluating financial performance deal with multiple indicator, attribute or index used to improve the result. However by using the advancement of fuzzy system, optimum computerized model can be created to help investor or manager to evaluate stock and financial performance more efficient. Feldman and Treleavan (1994) stated that fuzzy logic is a useful method when it related with mode of reasoning that is estimated rather than exact. On the other hand, Lambovska et al (2011) evaluated investment portfolios with theory of confidence intervals and theory of fuzzy subset. The author suggested fuzzy logic can be used as platform for comparison and/or ranking difference portfolios. The author also stated that fuzzy could be universal tool to combine several methods. Kortas et al (2003) also concluded that fuzzy logic users feel more confident in dealing with the complexity and fuzziness of real data rather than non-users and the users will be more satisfied with the final result since fuzzy logic assisted the researchers to make a good decision making. Fuzzy Logic Application in Evaluating Financial Performance There are many studies related to financial performance using fuzzy in several sector. Tavakkoli et al (2010) have conducted a study focused on evaluation of financial performance on Iran drug industry by fuzzy logic. In their study the measurement criteria used is AFP measurement and the selected criteria were chosen by taking view of point of stock market expert such as brokers and investment companies. Based on questionnaire given there are seven criteria selected which is return on investment (ROI), debt ratio, quick ratio, return on equity (ROE), financial leverage index, current ratio, and price earnings ratio (P/E). Yalcin et al (2012) focused on comparing and evaluating financial performance of seven Turkey manufacturing companies by used fuzzy model. The author also aims to measure effectiveness and productivities of the companies. While Othman et al (2012) also evaluated financial performance of healthcare companies in the USA by using fuzzy logic model. The authors developed three stages of methodology in their research and the approach was adapted from Tavakkoli et al (2010) First step was choosing the industry, the second step is choosing the right criteria to select and finally rank the companies according to their financial performance. DATA AND METHODOLOGY This paper also utilizes the fuzzy logic approach adapted from Tavakkoli et al (2010) to prioritize based on their financial performance. The selected industry is services industry as the sector is the major contributor for the Malaysian economy. Twenty two companies from the services sector labeled as C1, C2, C3 C22 are used to determine their financial performance as shown in Table 1. In this research three selected indices from Tavakkoli et al (2010) are also used to evaluate their financial performance as in Table 2. The data which 70

3 consist of financial ratios of the companies in 2013 was obtained from Datastream and has been summarized in Table 3. TABLE 1. SELECTED COMPANIES WITH CODES Name of Service Company Amway (MAL.) Hdg. Bhd. Cheetah Holdings Bhd. Engtex Group Bhd. Fiamma Holdings Bhd. Focus Point Holdings Berhad Hai-O Enterprise Bhd Kamdar Group (M) Bhd KPS Consortium Bhd Luxchem Corporation Bhd MBM Resources Bhd MESB Bhd Malayan United Inds. Bhd PansarBerhad Parkson Holdings Bhd PetronasDaganganBhd PharmaniagaBhd Samchem Holdings Berhad Suiwah Corporation Bhd. Sunzen Biotech Bhd Triumphal Associates Bhd The Store Corporation Voir Holdings Bhd Code of Company C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 C13 C14 C15 C16 C17 C18 C19 C20 C21 C22 TABLE 2. SELECTED INDICES Criteria Types of Fuzzy Number SUP(x) Fuzzy Number ROE Triangle 0.7 x < x 0 x< 0.7 µ ROE = x < 1 Current Ratio Tripezoid 1 x < 2 x 0 x< x < 2 µ CR = 3 x 2 x < 3 Debt Ratio Triangle x = 0.5 2x 0 x< 0.5 µ DR = 2 2x 0.5 x< 2 TABLE 3. NAME OF COMPANIES AND THEIR FINANCIAL PERFORMANCE FOR YEAR 2013 Name of Company Return on Equity (ROE) Current Ratio Debt Ratio Amway (MAL.) Hdg. Bhd Cheetah Holdings Bhd Engtex Group Bhd Fiamma Holdings Bhd Focus Point Holdings Berhad Hai-O Enterprise Bhd Kamdar Group (M) Bhd KPS Consortium Bhd Luxchem Corporation Bhd MBM Resources Bhd MESB Bhd Malayan United Inds. Bhd PansarBerhad Parkson Holdings Bhd PetronasDaganganBhd PharmaniagaBhd Samchem Holdings Berhad

4 Suiwah Corporation Bhd Sunzen Biotech Bhd Triumphal Associates Bhd The Store Corporation Voir Holdings Bhd RESULTS The ranking of the companies is presented in Table 4. TABLE 4. SITUATION OF EACH COMPANY ACCORDING TO SELECTED INDICES AND COMPANIES FINAL RANKING Code of company Return on Equity (ROE) µ ROE Current Ratio C C C C C C C C C C C C C C C C C C C C C C DISCUSSION µ CR Debt Ratio µ DR Min (Degree) Rank The result in Table 4 indicate ranking of the companies based on their financial performance using fuzzy logic approach. Based on the table the top five companies are MESB Bhd, Engtex Group Bhd, Luxchem Corporation Bhd, Pharmaniaga Bhd and MBM Resources Bhd. The researchers have compared the result with the analyses from the Datastreamand from the analysis, it can be concluded that our methodology is rather reliable. To illustrate, Engtex Group s market price is RM1.87 as compared to its intrinsic value which is RM2.00. That indicates buy signal and it is also rank as second company to be recommended by this paper. On the other hand, Pharmaniaga which ranked as number four has also supported by the analysis in the Datastream. According to CIMB Research, it is recommended to add since the intrinsic value is RM6.50 against current market price which is RM5.90. While, Hong Leong Investment suggest a buy signal and assign four stars to Pharmaniaga. According to this study, fifth company is MBM Resources which also have good comments from the analysts. Five out of eight analysts recommend a buy signal towards MBM Resources due to its target price which is RM3.60 as compared to current closing price at RM3.04. Petronas Dagangan Berhad which ranked as number ten has also been substantiated by the analysis from the database. Analysts recommended to sell the share of the Petronas Dagangan as its intrinsic value below its current market price. While, the last five ranking companies are Cheetah Holdings Berhad, Hai-O Enterprise Bhd, Pansa rberhad, Fiamma Holdings Berhad and Sunzen Biotech Bhd have also been verified by the Datastream. There is no recommendation by the analyst due to small value of earnings per share (EPS) for the year before except for Hai-O Enterprise Bhd whereby RHB Research Institute is neutral in its analysis. 72

5 CONCLUSIONS As a conclusion, this research is able to fulfill both objectives, which have been outlined at the beginning of this paper. This study manages to evaluate the financial performance and subsequently rank the companies using fuzzy logic approach. The results from this research are also consistent with the analysis by other investment agencies obtained from the Datastream. Thus, this approach can be used as an alternative to the fundamental and technical valuation which is widely used by the investment analysts. However, further research should be done to another sector to test the viability of the model/method and subsequently improve the model/method used in this study. REFERENCES Feldman, K, and Treleavan, P, 1994 Intelligent Systems in Finance, Applied Mathematical Finance, vol. 1, no. 2, pp Gallizo, JL, and Salvador, M, 2003 Understanding the Behaviour of Financial Ratios: The Adjustment Process, Journal of Economics and Business, Elsevier, vol. 55, no. 3, pp Gitman, LJ, and Madura, J, 2001 Introduction to Finance, Addison Wesley, pp Lambovska, M, and Marchev, A, 2011 A Fuzzy Approach for Expert Evaluation of Investment Portfolios, Ekonomski Horizonti, vol.13, no. 2, pp Metaxiotis, K, Psarras, J, and Samouilidis, E, 2003 Intergrating Fuzzy Logic Into Decision Support System: Current R Research and Future Prospect, Information Management & Computer Security, vol. 11, no. 2, pp Othman, M, Fahami, NA, and Mutalib, HA, 2010 Financial Performance Evaluation of Companies using Fuzzy Logic Approach: A Case Study of Properties Sector in Malaysia, Proceedings of International Conference on Global Business Environment, Bangkok, Thailand, pp Othman, M, Patricia RL, and Alnurlzaros, AR, 2012 Financial Performance Evaluation of Companies using Fuzzy Logic Approach: A Case Study of Healthcare Companies in the USA, International Conference on Management, Economics and Finance Proceeding, Kuching, Sarawak, pp Tavakkoli, M, Jamali, A, and Ebrahimi, A, 2010 New Method to Evaluate Financial Performance of Companies by Fuzzy Logic: Case Study, Drug Industry of Iran, Asia Pacific Journal of Finance and Banking Research, vol. 4, no. 4, pp Yalcin, N, Bayrakdaroglu, A, and Kahraman, C, 2012 Application of Fuzzy Multi-Criteria Decision Making Method for Financial Performance Evaluation of Turkish Manufacturing Industries, Expert System with Application, vol. 39, pp Zadeh, L, 1965 Fuzzy Sets, Information and Control, vol. 8, pp