---
title: From Regimes to Portfolios: An Interpretable Machine-Learning Framework for Strategic and Tactical Cross-Asset Allocation
url: https://www.ml-quant.com/papers/ssrn/7595598/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-10-16
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: SSRN 7595598
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7595598
featured: 2026-10-16
citations: unknown
topic: Portfolio & Allocation
---


# From Regimes to Portfolios: An Interpretable Machine-Learning Framework for Strategic and Tactical Cross-Asset Allocation

An interpretable machine-learning framework linking regime identification to cross-asset portfolio construction earns 0.60 net Sharpe, not significantly different from a 60/40 benchmark.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7595598
- Identifier: SSRN 7595598
- Released: 2026-10-12
- First featured: Quant Letter No. 135 (2026-10-16): https://www.ml-quant.com/issues/2026-10-16/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Portfolio & Allocation
- Authors: Chalam Raja Ankam

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