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An Application of Fuzzy Set Theory to the Weighted Average Cost of Capital and Capital Structure Decision

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DOI: 10.4236/ti.2010.14032    5,052 Downloads   10,080 Views   Citations


The purpose of this paper is to present the use of fuzzy logic to improve the calculation of weighted average cost of capital (WACC). The fuzzy WACC approach not only allows the pre-tax cost of debt, the effective tax rate, the tax benefit, and cost of equity to be treated as fuzzy numbers, it also offers ranking means to find the optimal debt ratio. This paper contributes to the literature by offering alternative methods to calculate the WACC and the optimal debt ratio for firms under uncertainty. Compared with the traditional WACC, the fuzzy WACC model can overcome the problems pertinent to uncertainty, complexity and imprecision. This paper thus sheds light on capital structure decision making.

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S. Wang and C. Hwang, "An Application of Fuzzy Set Theory to the Weighted Average Cost of Capital and Capital Structure Decision," Technology and Investment, Vol. 1 No. 4, 2010, pp. 248-256. doi: 10.4236/ti.2010.14032.


[1] W. F. Sharpe, “Capital Asset Prices,” Journal of Finance, Vol. 13, No. 3, September 1964, pp. 425-442.
[2] J. Lintner, “The Valuation of Risk Assets and the Selection of Risky Investments in Stock Portfolios and Capital Budgets,” Review of Economics and Statistics, Vol. 47, 1965, pp. 13-37.
[3] R. F. Bruner, K.M. Eades, R.S. Harris and R.C. Higgins, “Best Practices in Estimating the Cost of Capital: Survey and Synthesis,” Financial Practice and Education, 1998, pp. 13-28.
[4] H. J. Bierman, “Capital Budgeting in 1992: A Survey,” Financial Management, Vol. 22, 1993, p. 24.
[5] L. J. Gitman and P. A. Vandenberg, “Cost of Capital Techniques Used by Major US Firms: 1997 vs. 1980,” Financial Practice and Education, Vol. 10, No. 2, Fall/Winter, 2000, pp. 53-68.
[6] J. R. Graham and C. R. Harvey, “The Theory and Practice of Corporate Finance: Evidence from the Field,” Journal of Financial Economics, Vol. 60, 2001, pp. 187-244.
[7] G. Arnold and P. Hatzopoulos, “The Theory-practice Gap in Capital Budgeting: Evidence from the United Kingdom,” Journal of Business Finance and Accounting, Vol. 27, 2000, pp. 603-626.
[8] E. McLaney, J. Pointon, M. Thoma and J. Tucker, “Practitioners' perspectives on the UK cost of capital,” European Journal of Finance, Vol. 10, 2004, pp. 123-138.
[9] D. Brounen, A. De Jong and K. Koedijk, “Corporate Finance in Europe: Confronting Theory with Practice,” Financial Management, Vol. 33, No. 4, 2004, pp. 71-101.
[10] N. Chopra, J. Lakonishok and J. R. Ritter, “Measuring Abnormal Performance: Do Stocks Overreact,” Journal of Financial Economics, Vol. 31, 1992, pp. 235-268.
[11] E. F. Fama and K.R. French, “The Cross-section of Expected Stock Returns,” The Journal of Finance, Vol. 47, 1992, pp. 427- 465.
[12] J.L. Davis, “The Cross-section of Realized Stock Returns: The PRE-COMPUSTAT Evidence,” Journal of Finance, Vol. 49, No. 5, 1994, pp. 1579-1593.
[13] B. M. Barber and J.D. Lyon, “Firm Size, Book-to-market Ratio, and Security Returns: A holdout sample of financial firms,” Journal of Finance, Vol. 52, 1997, PP. 875-883.
[14] R. Roll, “A Critique of the Asset Pricing Theory’s Tests,” Journal of Financial Economics, Vol. 4, No. 2, 1977, pp. 129-176.
[15] F. Black, “Beta and Return,” Journal of Portfolio Management, Vol. 20, No. 1, 1993, pp. 8-18.
[16] S. P. Kothari, J. Shanken and R. G. Sloan, “Another Look at the Cross-section of Expected Returns,” Journal of Finance, Vol. 50, No. 1, 1995, pp. 185-224.
[17] W. F. Sharpe, “Factor Models, CAPMs and the APT,” Journal of Portfolio Management, Vol. 11, 1984, pp. 21-25.
[18] R. Lister, “Cost of Capital is Beyond Our Search,” Accountancy, Vol. 138, No. 1360, 2006, pp. 42-43.
[19] D. Lund, “Taxation, Uncertainty, and the Cost of Equity,” International Tax and Public Finance, 9, 2002, 483-503.
[20] C. Mayer, “Corporation Tax, Finance and the Cost of Capital,” Review of Economic Studies, Vol. 53, No. 1, 1986, pp. 93-112.
[21] S. J. Chen and S.M. Chen, “Fuzzy Risk Analysis Based on the Ranking of Generalized Trapezoidal Fuzzy Numbers,” Applied Intelligence, Vol. 26, No. 1, 2007, pp. 1-11.
[22] C. H. Cheng and D.L. Mon, “Fuzzy System Reliability Analysis by Confidence Interval,” Fuzzy Sets and Systems, Vol. 56, May 1993, pp. 29-35.
[23] C. H. Cheng, “A New Approach for Ranking Fuzzy Numbers by Distance Method,” Fuzzy Sets and Systems, Vol. 95, No. 1, 1998, pp. 307-317.
[24] T.C. Chu, “Ranking Fuzzy Numbers with an Area Between the Centroid Point and Original Point,” Computers and Mathematics with Applications, Vol. 43, 2002, pp. 111-117.
[25] A. Damodaran, “Corporate Finance: Theory and Practice,” John Wiley & Sons, 2001.

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