Consumer Expenditure-Based Portfolio Optimization
This study examines whether portfolio optimization can be effectively based on annual changes in the harmonized index of consumer prices (HICP) data. Specifically, we assess whether asset allocation based on consumer expenditure can generate superior returns compared to static or equal-weighted asse...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-06-01
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| Series: | International Journal of Financial Studies |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2227-7072/13/2/99 |
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| Summary: | This study examines whether portfolio optimization can be effectively based on annual changes in the harmonized index of consumer prices (HICP) data. Specifically, we assess whether asset allocation based on consumer expenditure can generate superior returns compared to static or equal-weighted asset allocation. To explore this, we use consumer expenditure data from HICP statistics categorized by COICOP. Our findings indicate that this strategy outperforms a buy-and-hold benchmark by 13.32% in terms of the Sharpe Ratio and exceeds an annual equal-weighted rebalancing strategy by 3.11%. Additionally, both the Calmar and Sterling Ratios demonstrate improved performance, further reinforcing the robustness of this approach. Furthermore, a hypothetical scenario where sector weights from the end of the given year—though not yet available during the year—are used suggests even greater improvements in performance. A high-sample bootstrap simulation confirms that the observed performance differences are not random but reflect the independent effectiveness of asset allocation based on consumer expenditure trends. This result strengthens the validity of our backtesting findings, indicating that the examined strategy could generate excess returns compared to passive portfolio managment and fixed-weight rebalancing approaches. The result of the study is therefore the development of an effective portfolio rebalancing strategy. |
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| ISSN: | 2227-7072 |