Portfolio Selection Using Mean-variance Model for Financial Technology Sector in the Australian Market Before and During COVID-19

R. A. Rebualos*, M. N. Young, Y. T. Prasetyo, R. Nadlifatin

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper presents a framework for portfolio selection using the mean-variance model utilizing Australian fintech company stocks before and during the COVID-19 pandemic. The investment pool consisting of fintech companies undergo a series of criteria to be determined. Mean-variance model is applied to identify the optimal portfolio using equally likely historical return estimates. The market was used as a benchmark to compare the portfolio performance. Back-test pre and during COVID show that most portfolios can outperform the benchmark in terms of returns while most portfolios also have a higher risk than the benchmark. The findings of this study may provide an alternative portfolio selection framework for any investor type considering the financial technology sector.

Original languageEnglish
Title of host publicationIEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2022
PublisherIEEE Computer Society
Pages412-416
Number of pages5
ISBN (Electronic)9781665486873
DOIs
Publication statusPublished - 2022
Event2022 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2022 - Kuala Lumpur, Malaysia
Duration: 7 Dec 202210 Dec 2022

Publication series

NameIEEE International Conference on Industrial Engineering and Engineering Management
Volume2022-December
ISSN (Print)2157-3611
ISSN (Electronic)2157-362X

Conference

Conference2022 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2022
Country/TerritoryMalaysia
CityKuala Lumpur
Period7/12/2210/12/22

Keywords

  • COVID-19
  • fintech
  • investment
  • mean-variance
  • portfolio selection

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