PORTFOLIO OPTIMIZATION FOR SHIPPING & DELIVERY SERVICES WITH R: BEFORE AND AFTER PANDEMIC COVID-19

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Vol. 4 No. 6 (2022): Fair Value: Jurnal Ilmiah Akuntansi dan Keuangan
Published: Jan 28, 2022
Keywords:
stock, portfolio optimization, R programming, courier, expedition, delivery, services, Covid-19

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Dina Anggraeni
Universitas Indonesia
Kris Sugiyanto
University of Indonesia
M. Irwan Zam Zam
University of Indonesia
Harry Patria
University of Indonesia

Abstract

The objective of this research is to construct an optimum investment portfolio of courier services sector stocks during period 2018-2021 using Modern Portfolio Theory model and to analyse risk and return generated by optimal portfolio before and after Covid-19 using R programming. Furthermore, we would also examine the impact of the Covid-19 on stock prices before and after Covid-19 to formulate investment decisions. The sample are 5 biggest courier services stocks (by market capitalization) that are listed consistently and did not stock split or reverse stock and the number of observations in 4825 stocks prices during the period January 2018 to October 2021. Based on the result of optimum investment research, we can observe that the best performing stocks with high tangency is AMZN, in fact way ahead of other sample emitens.  The result will be expected to help investors to bid the best possible portfolio in courier services.

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How to Cite
Anggraeni, D., Sugiyanto, K. ., Zam Zam, M. I. ., & Patria, H. . (2022). PORTFOLIO OPTIMIZATION FOR SHIPPING & DELIVERY SERVICES WITH R: BEFORE AND AFTER PANDEMIC COVID-19. Fair Value: Jurnal Ilmiah Akuntansi Dan Keuangan, 4(6), 550–563. https://doi.org/10.32670/fairvalue.v4i6.847
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References

Amundi (2014). Amundi Asset Management: Investment Strategy Collected Research Papers.

Baganzi, et al (2017). Portfolio Optimization Modelling with R for Enhancing Decision Making and Prediction in Case of Uganda Securities Exchange. Journal of Financial Risk Management, 2017

Bertil Naslund; Andrew Whinston (1964). MODEL OF DECISION MAKING UNDER RISK., 16(2), 81–94. doi:10.1111/j.1467-999x.1964.tb00842.x

Bodie, Z., Kane, A., & Marcus, A. J. (2011). Investments (9th ed.). New York, NY: McGraw-Hill.

Chau Li, Wan; Wu, Yue; Ojiako, Udechukwu (2014). Using portfolio optimisation models to enhance decision making and prediction. Journal of Modelling in Management, 9(1), 36–57. doi:10.1108/jm2-11-2011-0057

Lee, W. (2014). Constraints and Innovations for Pension Investment: The Cases of Risk Parity and Risk Premia Investing. The Journal of Portfolio Management, 40, 12-20.

http://www.bfjlaward.com/pdf/25949/12-20_Lee_JPM_0417.pdf

https://doi.org/10.3905/jpm.2014.40.3.012

Mayanja, F., Mataramvura, S., & Mahera, C. W. (2013). A Mathematical Approach to a Stocks Portfolio Selection: The Case of Uganda Securities Exchange (USE). Journal of Mathematical Finance, 2, 487-501. https://doi.org/10.4236/jmf.2013.34051

Namugaya, Weke, and Charles (2014). Modelling Volatility of Stock Returns: Is GARCH(1,1)

Enough?. http://gssrr.org/index.php?journal=JournalOfBasicAndApplied

Rana, M. E., & Akhter, W. (2015). Performance of Islamic and Conventional Stock Indices: Empirical Evidence from an Emerging Economy. Financial Innovation, 1, 1-17.

https://doi.org/10.1186/s40854-015-0016-3

S. R. Watson and R. V. Brown (1978). The Valuation of Decision Analysis. Journal of the Royal Statistical Society. Series A (General), 141(1), 69–78. doi:10.2307/2344777

Xu, Q., Zhou, Y., Jiang, C., Yu, K., & Niu, X. (2016). A Large CVaR-Based Portfolio Selection Model with Weight Constraints. Economic Modelling, 59, 436-447