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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/11420

Title: Portfolio Optimization Using Matrix Approach: A Case of Some Stocks on the Ghana Stock Exchange
Authors: Abonongo, John
Anuwoje, Ida Logubayom
Ackora-Prah, Joseph
Keywords: Portfolio Optimization
Efficient frontier
Mean-Variance
Matrix Approach
Issue Date: 2017
Publisher: International Journal of Accounting, Finance and Risk Management
Citation: International Journal of Accounting, Finance and Risk Management 2017; 2(1): 21-30; http://www.sciencepublishinggroup.com/j/ijafrm, doi: 10.11648/j.ijafrm.20170201.14
Abstract: Analyzing risk has been a principal concern of actuarial and insurance professionals which plays a fundamental role in the theory of portfolio selection where the prime objective is to find a portfolio that maximizes expected return while reducing risk. Portfolio optimization has been applied to asset management and in building strategic asset allocation. The purpose of this paper is to construct optimal and efficient portfolios using the matrix approach. This paper used secondary data on 13 stocks (ETI, GCB, GOIL, TOTAL, FML, GGBL, CLYD, EGL, PZC, UNIL, TLW, AGA and BOPP) from the Ghana Stock Exchange (GSE) database comprising the monthly closing prices from the period 02/01/2004 to 16/01/2015. The results revealed that, all the portfolios were optimal and that portfolios 1, 2, 4, 5, 6, 9, 10, 11 and 12 with expected return 2.523, 2.593, 2.827, 3.642, 2.405, 2.812, 5.229, 3.559 and 5.928 respectively were efficient portfolios whereas portfolios 3, 7 and 8 with expected return 0.377, 0.699 and 0.152 respectively were inefficient portfolios with reference to the expected return of the global minimum variance portfolio (2.360). GGBL was seen as the stock with the highest allocation of wealth in most of the portfolios. Six out of the 12 portfolios had CLYD exhibiting the least asset allocation.
Description: An article published in International Journal of Accounting, Finance and Risk Management 2017; 2(1): 21-30; http://www.sciencepublishinggroup.com/j/ijafrm; doi: 10.11648/j.ijafrm.20170201.14
URI: http://hdl.handle.net/123456789/11420
Appears in Collections:College of Science

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