---
title: Multi-Asset Portfolio Selection with Machine Learning: Long-Run International Evidence
url: https://www.ml-quant.com/papers/ssrn/7610204/
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 7610204
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7610204
featured: 2026-10-16
citations: unknown
topic: Portfolio & Allocation
---


# Multi-Asset Portfolio Selection with Machine Learning: Long-Run International Evidence

Machine learning forecasts of equity, bond, bill and housing returns from 1870-2020 across 16 countries improve Sharpe ratios substantially when trained on pooled cross-country data rather than country-specific samples.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7610204
- Identifier: SSRN 7610204
- Released: 2026-10-15
- 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: Ray Friedenberger, Felix Reichenbach

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