TY - JOUR ID - 305 TI - A new methodology for deriving the efficient frontier of stocks portfolios: An advanced risk-return model JO - Journal of AI and Data Mining JA - JADM LA - en SN - 2322-5211 AU - Mehrjoo, Sh. AU - Jasemi, M. AU - Mahmoudi, A. AD - Department of Industrial Management, Islamic Azad University, Qazvin Branch, Qazvin, Iran AD - Department of Industrial Engineering, K.N.Toosi University of Technology, Tehran, Iran. AD - Department of Industrial Management, payamenoor University, izeh Branch, izeh, Iran. Y1 - 2014 PY - 2014 VL - 2 IS - 2 SP - 113 EP - 123 KW - efficient frontier KW - portfolio optimization KW - Markowitz model KW - lower partial moment model KW - Genetic Algorithm DO - 10.22044/jadm.2014.305 N2 - In this paper after a general literature review on the concept of Efficient Frontier (EF), an important inadequacy of the Variance based models for deriving EFs and the high necessity for applying another risk measure is exemplified. In this regard for this study the risk measure of Lower Partial Moment of the first order is decided to replace Variance. Because of the particular shape of the proposed risk measure, one part of the paper is devoted to development of a mechanism for deriving EF on the basis of new model. After that superiority of the new model to old one is shown and then the shape of new EFs under different situations is investigated. At last it is concluded that application of LPM of the first order in financial models in the phase of deriving EF is completely wise and justifiable. UR - https://jad.shahroodut.ac.ir/article_305.html L1 - https://jad.shahroodut.ac.ir/article_305_4714edd6861e084ac8b485d5aef88ef3.pdf ER -