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Optimizing Mixed-Asset Portfolios Involving REITs

Habbab, Fatim and Kampouridis, Michail and Voudouris, Alexandros (2022) Optimizing Mixed-Asset Portfolios Involving REITs. In: IEEE Symposium on Computational Intelligence for Financial Engineering & Economics (CIFEr) 2022, 2022-05-04 - 2022-05-05, Helsinki, Finland/Online. (In Press)

REITs_CIFEr_2022.pdf - Accepted Version

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Real Estate Investment Trusts (REITs) is a popular investment choice as it allows investors to hold shares in real estate rather than investing large sums of money to purchase real estate by themselves. Previous work studied the effectiveness of multi-asset portfolios that include REITs via an efficient frontier analysis. However, the advantages of including (both domestic and international) REITs in multi-asset portfolios, as well as analyzing all the possible combinations of asset classes, has not been investigated before. In this paper, we fill in this gap by performing a thorough investigation across 456 different portfolios to demonstrate the added value of including REITs in mixed-asset portfolios in terms of different important financial metrics. To this end, we use a genetic algorithm approach to maximize the Sharpe ratio of the portfolios. Our results show that optimization via a genetic algorithm outperforms the results obtained from a global minimum variance portfolio. More importantly, our results also show that there can be significant improvements in average returns, risk and Sharpe ratio when including REITs.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: _not provided_
Uncontrolled Keywords: mixed-asset portfolio; genetic algorithm; mini- mum variance; portfolio optimization; risk-adjusted return
Divisions: Faculty of Science and Health
Faculty of Science and Health > Computer Science and Electronic Engineering, School of
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 02 Feb 2022 15:41
Last Modified: 13 Jul 2022 22:19

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