Multi-objective possibilistic model for portfolio selection with transaction cost

Jana, Purbita; Roy, Tapan Kumar; Mazumder, Sanat Kumar

doi:10.1016/j.cam.2008.09.008

Cited by 103 publications

(44 citation statements)

References 12 publications

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“…Jana et al (2009) showed that this technique can be applied in portfolio optimization problem. Fuzzy programming technique follows these steps for solving the problem that is shown in Eq.…”

Section: Fuzzy Programming Techniquementioning

confidence: 99%

“…They solved their model using fuzzy mathematical programming. Jana et al (2009) proposed a possibilistic model with transaction cost and entropy function in objective functions. Chang et al (2009) considered different risk measures in their model such as variance, semivariance, variance with skewness and absolute deviation, and solved it using genetic algorithm.…”

Section: Introductionmentioning

confidence: 99%

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A Two-Stage Method for Considering Cardinality in Portfolio Optimization of Mutual Funds

Alimi¹

2015

MAS

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Mutual funds are important financial institutes. There are several methods for performance evaluation of mutual funds such as portfolio optimization. Portfolio optimization has a basic model that has completed up to now. One of completions is adding cardinality constraint to the model. Considering cardinality in portfolio optimization model makes it an integer programming problem that solving it, is hard and makes the efficient frontier discontinuous. In current study in first stage we rank the mutual funds with VIKOR method and based on 5 characteristics: rate of return, variance, semivariance, Treynor ratio and Sharpe ratio. In second stage according to cardinality level best ranked mutual funds are chosen. A mean-semivariance portfolio optimization model is written using chosen funds. This model is solved using fuzzy technique programming and efficient frontier is obtained. Real data from NASDAQ based on 92 mutual funds are used to illustrate the effectiveness of proposed methodology. Results show that the efficient frontier obtained from our methodology is continuous and near to unconstrained efficient frontier.

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“…Jana et al (2009) showed that this technique can be applied in portfolio optimization problem. Fuzzy programming technique follows these steps for solving the problem that is shown in Eq.…”

Section: Fuzzy Programming Techniquementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Two-Stage Method for Considering Cardinality in Portfolio Optimization of Mutual Funds

Alimi¹

2015

MAS

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“…Iš išanalizuotos portfelio optimizavimo literatūros matyti, kad vis dažniau mokslininkai padaro išvadą, kad į investicijų portfelio sudarymo uždavinį prie pelningumo ir rizikos tikslinga įtraukti papildomus parametrus ir kad portfelio optimizavimas turi būti daugiakriterinis (Steuer et al 2007(Steuer et al , 2008. Kaip trečiasis parametras buvo naudojamas likvidumas (Jana et al 2009;Lo et al 2003), asimetrija (Prakash et al 2003;Konno et al 1993;Konno, Yamamoto 2005;Briec et al 2005;Kerstens et al 2008), plotis arba neapibrėžtumas (Smimou et al 2008), sąlyginė rizikuojamoji vertė -CVaR (Aboulaich et al 2010). Kai kuriais atvejais rizikai portfelyje išreikšti naudotas ne klasikinis standartinis nuokrypis, o kiti matai -absoliutus ir semiabsoliutus nuokrypis (Fang et al 2006), rizikuojamoji vertė (VaR) (Soler et al 2010).…”

Section: įVadasunclassified

Investicijų portfelio sudarymas naudojant sprendimų paramos sistemą

Stasytytė

2012

Business: Theory and Practice

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Santrauka. Šiuolaikinėje finansų rinkoje ir finansų mokslo srityje kyla žiniomis pagrįstų ir programiškai aprūpintų sistemų, padedančių investuotojams ir finansų analitikams laiku priimti tinkamus sprendimus, poreikis. Straipsnyje siūloma galima priemonė optimalaus portfelio sudarymo problemai kapitalo rinkoje spręsti -investicijų portfelio sprendimų paramos sistema. Straipsnyje taip pat detaliai aprašoma sistemos struktūra ir pagrindiniai veikimo principai. Sistema paremta adekvačiojo portfelio modeliu, siūlančiu portfelio reikšmes matuoti pagal tris parametrus -pelningumą, patikimumą ir riziką. Taip sprendimų priėmimo posistemyje formuojami du erdviniai paviršiai -galimybių (efektyvusis) paviršius ir naudingumo funkcijų paviršius, kurių susilietimo taške gaunamas optimalus sprendinys -investicijų portfelio struktūra. Pateikiamos galimos sistemos plėtojimo kryptys ir pritaikymo galimybės.Reikšminiai žodžiai: investicijų portfelis, adekvačiojo portfelio modelis, sprendimų paramos sistema, sistemos inžinierius, prognozavimas, monitoringas. INVESTMENT PORTFOLIO FORMATION USING DECISION SUPPORT SYSTEM Viktorija StasytytėVilnius Gediminas Technical University, Saulėtekio al. 11, LT-10223 Vilnius, Lithuania E-mail: viktorija.stasytyte@vgtu .lt Received 01 March 2012; accepted 20 June 2012Abstract. In contemporary financial market and scientific field of finance the demand for knowledge-based and software-supplied systems allowing investors and financial analysts to make proper and timely decisions is rising. The possible instrument for solving the problem of optimal portfolio formation in the capital market is proposed in the paper -the investment portfolio decision support system. The paper also thoroughly describes the structure of the system, as well as its main operation principles. The system is based on the adequate portfolio model, which proposes to express portfolio values in three parameters -profitability, reliability and risk. Thus in decision-making subsystem two surfaces are formed -possibilities (efficient) surface and utility functions' surface, and in their tangency point the optimal decision is found -the structure of investment portfolio. The possible trends of system's development and possibilities of its application are presented.

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“…The possibilistic mean, variance and covariance of fuzzy numbers, defined by Carlsson and Fullér 12 , were used to solve many real world problems. For example, Carlsson et al 16 and Jana et al 17 applied possibilistic mean value and variance to solve Markowitz mean-variance portfolio selection problem under the assumption that the returns of assets were fuzzy numbers. Zhang and Xiao 18 applied weighted possibilistic mean and variance of fuzzy numbers to the decision making.…”

Section: Introductionmentioning

confidence: 99%

Possibility Method for Triangular Intuitionistic Fuzzy Multi-attribute Group Decision Making with Incomplete Weight Information

Wan¹,

Dong²

2014

IJCIS

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Triangular intuitionistic fuzzy numbers (TIFNs) are a special kind of intuitionistic fuzzy sets (IFSs) on a real number set. TIFNs are useful to deal with ill-known quantities in decision data and decision making problems themselves. The purpose of this paper is on developing a new ranking method of TIFNs and application to multiattribute group decision making (MAGDM) problems in which the attribute values are expressed with TIFNs and the information on attribute weights is incomplete. The weighted average operator of TIFNs is defined, the concepts of the possibility mean, variance of TIFNs as well as standard deviation are introduced. Hereby two new ranking indices considering the risk attitude of decision maker are developed to rank TIFNs. In the proposed group decision method, the collective overall attribute values of alternatives are obtained by using the weighted average operator of TIFNs We construct the multi-objective programming of maximizing the ranking indices of membership and non-membership functions on alternative's collective overall attribute values, which is transformed into a single linear programming model by using the membership function based weighted sum approach. Thus, the ranking indices of membership and non-membership functions for the alternatives are derived, which are used to rank the alternatives. A personnel selection example is analyzed to demonstrate the applicability, universality and flexibility of the proposed models and method.

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Multi-objective possibilistic model for portfolio selection with transaction cost

Cited by 103 publications

References 12 publications

A Two-Stage Method for Considering Cardinality in Portfolio Optimization of Mutual Funds

A Two-Stage Method for Considering Cardinality in Portfolio Optimization of Mutual Funds

Investicijų portfelio sudarymas naudojant sprendimų paramos sistemą

Possibility Method for Triangular Intuitionistic Fuzzy Multi-attribute Group Decision Making with Incomplete Weight Information

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