Dynamic rebalancing strategies in multi-asset portfolio optimization: an empirical and data-driven approach
Lo Coco, Angelo (A.A. 2023/2024) Dynamic rebalancing strategies in multi-asset portfolio optimization: an empirical and data-driven approach. Tesi di Laurea in Equity markets and alternative investments, Luiss Guido Carli, relatore Marco Morelli, pp. 85. [Master's Degree Thesis]
Full text for this thesis not available from the repository.
Abstract/Index
Portfolio theory. Modern portfolio theory. Risk parity portfolio. Metrics description. Empirical analysis. Multi-asset portfolios. The origins of multi-asset portfolios. Optimizing risk and return: the strategic foundations of multi-asset portfolios. The framework of economic systems. Composition of the economic cycle-neutral portfolio. Backtesting analysis. Dynamic multi-asset portfolios allocation mechanism. Description of the dataset. Analysis of the covariance matrix. Description of the asset class and the rebalancing model. Examination of results. Portfolio performance analysis. Role of inputs in portfolio rebalancing. Statistical analysis of historical portfolio volatility. Volatility and returns. Key differences between realized, implied, and historical volatility. Dataset analysis. Preliminary tests on returns. Forecasting future returns.
References
Bibliografia: pp. 83-85.
| Thesis Type: | Master's Degree Thesis |
|---|---|
| Institution: | Luiss Guido Carli |
| Degree Program: | Master's Degree Programs > Master's Degree Program in Economics and Finance (LM-56) |
| Chair: | Equity markets and alternative investments |
| Thesis Supervisor: | Morelli, Marco |
| Thesis Co-Supervisor: | Borri, Nicola |
| Academic Year: | 2023/2024 |
| Session: | Extraordinary |
| Deposited by: | Alessandro Perfetti |
| Date Deposited: | 10 Jul 2025 07:47 |
| Last Modified: | 10 Jul 2025 07:47 |
| URI: | https://tesi.luiss.it/id/eprint/42853 |
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