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dc.contributor.authorAvrianto, Alam
dc.contributor.authorKurniawan, Deri Alan
dc.contributor.authorGumilar, Irfan Rizki
dc.contributor.authorRismanto, Hilman
dc.date.accessioned2020-01-17T07:20:08Z
dc.date.available2020-01-17T07:20:08Z
dc.date.issued2019
dc.identifier.citationBoard John, Charles S & William Z. 1999. The Application of Operations Research Techniques to Financial Market. Bodie, Zvi. Kane, Alex. & Marcus, Alan J. 2005. Investments, 6th Edition. New York: Mc Graw Hill. Cornuejols Gerard & Reha Tutuncu. 2006. Optimization Methods in Finance. USA: Carnegie Mellon University. Elton, Edwin J. & Gruber, Martin J. 2007. Modern Portfolio Theory and Investment Analysis, Seventh Edition. Singapore : John Wiley and Sons (SEA) Pte. Ltd. Fakhruddin, M. & Sopian, H. 2001. Perangkat dan Model Analisis Investasi di Pasar Modal. Jakarta: Penerbit PT Elex Media Komputindo. Fisher, Donald E and Ronald J, Jordan. 1993. Security Analysis and Portfolio Investment. 3rd Edition. Englemwood, New Jersey: Prentice Hall, Inc. Francis, Jack Clark. 1993. Management of Investment. 3rd Editio . Singapore. Mc Graw-Hill International Edition. Fuad Harianto dan Siswanto Sudomo. 1998. Perangkat dan Teknik Analisis Investasi di Pasar Modal Indonesia. Jakarta: Penerbit PT. Bursa Efek Jakarta. Hartono, J. (2015). Teori Portofolio dan Analisis Investasi. Edisi 10. Yogyakarta: BPFE. Hillier, F. S., Lieberman, G. J., Nag, B., & Basu, P. (2017). Introduction to Operations Research, 10th Edition. India: Mc Graw Hill. Horasanh, Mehmet & Neslihan Fidan. (tanpa tahun). Portfolio Selection by Using Time Varying Covariance Matrices. Journal of Economic and Social Reasearch 9(2). 1-22. Jones, Charles P. 2002. Investments Analysis and Management, 8th Edition. New York : John Wiley and Sons, Inc. Karacabey, A. A. (2007). Risk and Investment Opportunities in Portfolio Optimization. European Journal of Finance and Banking Research. Vol 1 No 1. Kim, J.S. Kim, Y.C. & Shin, K.Y. 2005. An Algorithm for Portfolio Optimization Problems. Informatica. Vol 16. No 1. 93-106. Sharpe, William F. Gordon J. Alexander and Jeffrey V. Bailey. 1999. Investment. 6th Ed. London: Prentice-Hall. Taha, H. A. (2017). Operations Research: An Introduction, 10th Editioin. Pearson. Thian Hin, L. 2002. Panduan Berinvestasi Saham. Jakarta. PT. Elex Media Komputindo Kelompok Gramedia. Wegner, P. 1962. A Quadratic Programming Formulation of the Portofolio Selection Model. JSS 16(6). 468-476. Van De Panne, C & Andrew Whinston. 1964. The Simplex and the Dual Method for Quadratic Programming. Pergamon Press. Vol. 15 pp 335-388.id_ID
dc.identifier.issn2615-1588
dc.identifier.urihttp://hdl.handle.net/11617/11792
dc.description.abstractPortofolio theory emphasizes the search for the optimal combination of investments that gives the maximum profit rate at a particular level of risk. Portfolios are formed by investors in general is a portfolio based on the investor preferences. Portfolios are formed based on the preferences of the portfolio is not really optimal. To determine the composition of shares that must be invested in order to generate optimal portfolios with constraints is by way of optimization techniques. In investing, the investor’s expectation is to obtain a return that is as large as possible or at least greater than the interest rate of deposits. In reducing investment risk, the better investment is done not only in one area. The expectation is if the loss of investment in a field then the loss is expected to be reduced or eliminated from investment in other areas (diversification). When diversifying, investors usually confuse in selecting and determining the proportion of investment he has to do (Optimal). Therefore, investors need to have a grip in diversification so that investor expectations can be fulfilled. One of them is by diversifying with quadratic programming method. Quadratic programming processes conducted based on Markowitz’s model approach using LINGO. The results of this research in the form of investment proportions on some stocks. The research method used is a descriptive and verification method with techniques aimed at sampling such as sampling. The description of the calculations in this study uses secondary data with a sample of historical data shares included in the LQ45 index list during the period February 2004 to July 2009. The data is then processed using the quadratic programming method The results showed that the optimal diversification by using the quadratic programming method will be achieved when the investment made in the shares of Indosat Tbk (ISAT) of 13,2%, Indofood Sukses Makmur Tbk (INDF) of 4,12%, Bank Central Asia Tbk(BBCA) of 37,55%, Astra International Tbk (ASII) of 4,11%, Aneka Tambang (Persero) Tbk (ANTM) of 0,91%, Astra Agro Lestari Tbk (AALI) of 5,73%, Telekomunikasi Indonesia Tbk (TLKM) of 31,9% and shares of Holcim Indonesia Tbk (SMCB) of 2,45%. Risks arising from the limitations of existing investments and amounted to 0,14%.id_ID
dc.language.isootherid_ID
dc.publisherISETH 2019 (International Summit on Science, Technology, and Humanity)id_ID
dc.titleOptimization of Stock Diversification with Quadratic Programming Method Using Lingoid_ID
dc.typeArticleid_ID


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