Browse > Article
http://dx.doi.org/10.13106/jafeb.2021.vol8.no5.0839

Optimum Risk-Adjusted Islamic Stock Portfolio Using the Quadratic Programming Model: An Empirical Study in Indonesia  

MUSSAFI, Noor Saif Muhammad (Department of Mathematics, UIN Sunan Kalijaga)
ISMAIL, Zuhaimy (Department of Mathematical Sciences, Universiti Teknologi Malaysia)
Publication Information
The Journal of Asian Finance, Economics and Business / v.8, no.5, 2021 , pp. 839-850 More about this Journal
Abstract
Risk-adjusted return is believed to be one of the optimal parameters to determine an optimum portfolio. A risk-adjusted return is a calculation of the profit or potential profit from an investment that takes into account the degree of risk that must be accepted to achieve it. This paper presents a new procedure in portfolio selection and utilizes these results to optimize the risk level of risk-adjusted Islamic stock portfolios. It deals with the weekly close price of active issuers listed on Jakarta Islamic Index Indonesia for a certain time interval. Overall, this paper highlights portfolio selection, which includes determining the number of stocks, grouping the issuers via technical analysis, and selecting the best risk-adjusted return of portfolios. The nominated portfolio is modeled using Quadratic Programming (QP). The result of this study shows that the portfolio built using the lowest Value at Risk (VaR) outperforms the market proxy on a risk-adjusted basis of M-squared and was chosen as the best portfolio that can be optimized using QP with a minimum risk of 2.86%. The portfolio with the lowest beta, on the other hand, will produce a minimum risk that is nearly 60% lower than the optimal risk-adjusted return portfolio. The results of QP are well verified by a heuristic optimizer of fmincon.
Keywords
Islamic Stock Portfolio; Risk-Adjusted Return; Technical Analysis; Portfolio Optimization; Quadratic Programming;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Brandimarte, P. (2013). Numerical methods in finance and economics: A MATLAB-based introduction. New York: John Wiley & Sons.
2 Elton, E. J., Gruber, M. J., Brown, S. J., & Goetzmann, W. N. (2014). Modern portfolio theory and investment analysis (9th ed.). New York: John Wiley & Sons. https://doi.org/10.1017/CBO9781107415324.004   DOI
3 Gilli, M., & Schumann, E. (2012). Heuristic optimization in financial modeling. Annals of Operations Research, 193(1), 129-158. https://doi.org/10.1007/s10479-011-0862-y   DOI
4 Ginting, J., Ginting, N. W., Putri, L., & Nidar, S. R. (2021). Optimal portfolio models for an inefficient Market. Journal of Asian Finance, Economics, and Business, 8(2), 57-64. https://doi.org/10.13106/jafeb.2021.vol8.no2.0057   DOI
5 Hartono, J. (2013). Portfolio theory and investment analysis (8th ed.). Yogyakarta: BPFE.
6 Ho, C. S. F., Abd Rahman, N. A., Yusuf, N. H. M., & Zamzamin, Z. (2014). Performance of global Islamic versus conventional share indices: International evidence. Pacific-Basin Finance Journal, 28, 110-121. https://doi.org/10.1016/j.pacfin.2013.09.002   DOI
7 Hsieh, H. H. (2013). A review of performance evaluation measures for actively-managed portfolios. Journal of Economics and Behavioral Studies, 5(12), 815-824. https://doi.org/10.22610/jebs.v5i12.455   DOI
8 Hussain, M., Shahmoradi, A., & Turk, R. (2015). An overview of Islamic finance (Working Paper WP/015/20). International Monetary Fund. https://www.imf.org/external/pubs/ft/wp/2015/wp15120.pdf
9 Jorion, P. (2007). Value at risk: The new benchmark for managing financial risk (3rd ed.). New York: McGraw-Hill.
10 Karim, B. A., Datip, E., & Shukri, M. H. M. (2014). Islamic stock market versus the conventional stock market. International Journal of Economics, Commerce and Management, II(11), 1-9.
11 Moh'd Mahmoud, A., Waleed, H., & Wafaa, M. (2012). The impact of the global financial crisis 2008 on the Amman stock exchange. Journal of Distribution Science, 10(7), 13-22. https://doi.org/10.15722/jds.10.7.201207.13   DOI
12 Khan, A. H., Cao, X., Katsikis, V. N., Stanimirovic, P., Brajevic, I., Li, S., & Nam, Y. (2020). Optimal portfolio management for engineering problems using nonconvex cardinality constraint: A computing perspective. IEEE Access, 8, 57437-57450. https://doi.org/10.1109/ACCESS.2020.2982195   DOI
13 Kare, K. R., & Fu, M. (2014). Do shariah compliant stocks perform better than conventional stocks? A comparative study of stocks listed on the Australian stock exchange. Asian Journal of Finance & Accounting, 6(2), 155. https://doi.org/10.5296/ajfa.v6i2.6072   DOI
14 MathWorks Inc. (2020). Global optimization toolbox user's guide R2020a. Natick, MA: Global Publishers.
15 Mokhtar, S. B., & Hanif, D. S. C. M. S. (2006). Nonlinear programming: Theory and algorithms (3rd ed.). New York: John Wiley & Sons, Inc.
16 Morales, J. E L. (2012). A sequential quadratic programming algorithm with an additional equality constrained phase. IMA Journal of Numerical Analysis, 17(1), 553-579. https://doi.org/10.1093/imanum/drq037   DOI
17 Mussafi, N. S. M. (2012). Optimization of the risk portfolio using the Markowitz MVO model. AdMathEdu: Jurnal Ilmiah Pendidikan Matematika, Ilmu Matematika Dan Matematika Terapan, 1(1), 1-8. https://doi.org/10.12928/admathedu.v1i1.4879   DOI
18 Nguyen, N., Nguyen, T., Tran, T., & Mai, A. (2020). Shrinkage model selection for portfolio optimization on Vietnam stock market. Journal of Asian Finance, Economics, and Business, 7(9), 135-145. https://doi.org/10.13106/JAFEB.2020.VOL7.NO9.135   DOI
19 Pratiwi, D. A., & Yunita, I. (2015). Optimal portfolio construction: A case study of LQ45 Index in Indonesia Stock Exchange). International Journal of Science and Research (IJSR), 4(6), 2525-2530. https://www.ijsr.net/get_abstract.php?paper_id=SUB155903
20 Otoritas Jasa Keuangan (OJK). (2019). Shariah mutual fund statistics. https://www.Ojk.Go.Id/Id/Kanal/Syariah/Data-Dan-Statistik/Reksa-Danayariah/Pages/Statistik-ReksadanaSyariah-- -Desember-2018.Aspx
21 Sarykalin, S., Serraino, G., & Uryasev, S. (2008). Value-at-risk vs. conditional value-at-risk in risk management and optimization. State-of-the-Art Decision-Making Tools in the InformationIntensive Age, 5(11), 270-294. https://doi.org/10.1287/educ.1080.0052   DOI
22 Setiawan, C., & Kanila Wati, N. P. (2019). Factors affecting the performance of sharia equity funds in Indonesia. Iranian Journal of Management Studies, 12(4), 481-508. https://doi.org/10.22059/ijms.2019.263411.673253   DOI
23 Shadkam, E. (2014). FC approach in portfolio selection of Tehran's stock market. Journal of Asian Finance, Economics, and Business, 1(2), 31-37. https://doi.org/10.13106/jafeb.2014.vol1.no2.31   DOI
24 Skrinjaric, T., & Sego, B. (2019). Using grey incidence analysis approach in portfolio selection. International Journal of Financial Studies, 7(1), 46-63. https://doi.org/10.3390/ijfs7010001   DOI
25 Taylor, J. R. (1997). An introduction to error analysis. Sausalito, CA: University Science Books.
26 Yousfat, A. (2015). The portfolio selection by using quadratic programming approach case study of Malaysia stock exchange. International Journal of Engineering and Technology, 7(4), 1361-1369. http://www.enggjournals.com/ijet//docs/IJET15-07-04-328.pdf
27 Bhati, M. T., & Parashar, P. (2019). M 2: An inclusive measure of portfolio risk-adjusted return. IOSR Journal of Engineering, 9(5), 37-42. http://iosrjen.org/Papers/vol9_issue5/Series-13/6.%2037-42.pdf
28 Alam, M. M., Akbar, C. S., Shahriar, S. M., & Elahi, M. M. (2017). The Islamic shariah principles for investment in the stock market. Qualitative Research in Financial Markets, 9(2), 132-146. https://doi.org/10.1108/QRFM-09-2016-0029   DOI