Papahristodoulou, Christos (2008): A note on the effectiveness of some de-fuzzification measures in a fuzzy pure factors portfolio.
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There are several methods to convert fuzzy or stochastic LP to conventional LP models. In this simple paper we evaluate the effectiveness of three proposed methods, using a numerical example from a pure factors portfolio.
|Item Type:||MPRA Paper|
|Original Title:||A note on the effectiveness of some de-fuzzification measures in a fuzzy pure factors portfolio|
|Keywords:||: fuzzy; stochastic; linear programming; pure factors portfolio|
|Subjects:||C - Mathematical and Quantitative Methods > C0 - General > C02 - Mathematical Methods
C - Mathematical and Quantitative Methods > C6 - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling > C61 - Optimization Techniques; Programming Models; Dynamic Analysis
G - Financial Economics > G3 - Corporate Finance and Governance > G32 - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
G - Financial Economics > G1 - General Financial Markets > G10 - General
|Depositing User:||Christos Papahristodoulou|
|Date Deposited:||04. Nov 2008 00:04|
|Last Modified:||16. Feb 2013 03:30|
Inuiguchi, M. and J. Ramík: Possibilistic linear programming: a brief review of fuzzy mathematical programming and a comparison with stochastic programming in portfolio selection problem, Fuzzy Sets and Systems, 111 (2000), 3-28.
Luhandjula, M.K.: Optimization under hybrid uncertainty, Fuzzy Sets and Systems 146 (2004), 187-203.
Luhandjula, M.K.: Fuzziness and randomness in an optimization framework, Fuzzy Sets and Systems 77 (1996), 291-297.
Grinblatt, M. and S. Titman: Financial Markets and Corporate Strategy, McGraw-Hill, Boston, 1998.
Van Hop, N.: Solving fuzzy (stochastic) linear programming problems using superiority and inferiority measures, Information Sciences, 177 (2007), 1977-91.
Wolfram Research, Mathematica: Fuzzy Logic (2003).