A machine learning approach to risk based asset allocation in portfolio optimization
Sanjay Agal, Krishna Raulji, Niyati Dhirubhai Odedra · 2025
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Description
This paper introduces a novel machine learning framework for dynamic risk-based asset allocation that addresses fundamental limitations in traditional portfolio optimization methods. The proposed architecture integrates Long Short-Term Memory networks for volatility forecasting with differentiable risk budgeting layers and regime-switching mechanisms, enabling end-to-end training of portfolio weights under adaptive risk constraints.
Catalog record
| CREATOR | Sanjay Agal, Krishna Raulji, Niyati Dhirubhai Odedra |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 90 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |