Utilizing the real estate investment trusts for portfolio optimisation by application of genetic algorithm
Abstract Complex investment decisions require thorough study. Modern portfolio theory provides some broad guidelines on diversification within this framework, focusing on financial instrument categories. A diverse portfolio and favorable economic conditions are the main factors affecting investor re...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer Nature
2025-04-01
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| Series: | Humanities & Social Sciences Communications |
| Online Access: | https://doi.org/10.1057/s41599-025-04715-0 |
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| Summary: | Abstract Complex investment decisions require thorough study. Modern portfolio theory provides some broad guidelines on diversification within this framework, focusing on financial instrument categories. A diverse portfolio and favorable economic conditions are the main factors affecting investor returns. The research used the RIETS portfolio and genetic algorithm to improve investment portfolio Sharpe ratios. Since 2008, when the financial crisis increased activity, investors and scholars have focused on REITs. REIT investments have gained popularity in recent years due to their long-term stability and consistent profitability. Studies that emphasize management perspectives are valuable, but they also have significant limitations. Asset management’s primary goal is to optimize investor returns. It is imperative to evaluate asset management strategies in order to guarantee the assets’ long-term efficiency. This study examines 456 distinct portfolios in order to rectify this deficiency and demonstrates how the incorporation of REITs into mixed-asset portfolios enhances them in a variety of critical financial metrics. The results of the study suggest that utilizing genetic algorithm optimization outperforms a globally diversified portfolio with the lowest volatility. The data indicates that investing in REITs is a highly effective strategy for improving the Sharpe ratio, average returns, and risk profile. |
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| ISSN: | 2662-9992 |