---
title: Machine Learning in Empirical Asset Pricing
url: https://www.ml-quant.com/papers/ssrn/5212620/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: SSRN 5212620
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5212620
featured: 2025-04-16
citations: unknown
topic: Asset Pricing & Factors
---


# Machine Learning in Empirical Asset Pricing

The paper suggests a regime switching model to estimate beta and volatility, addressing traditional event study methodology's limitations during volatility shifts.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5212620
- Identifier: SSRN 5212620
- Released: 2025-03-14
- First featured: Quant Letter No. 93 (2025-04-16): https://www.ml-quant.com/issues/2025-04-16/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Asset Pricing & Factors

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