---
title: Machine Learning for Lag Selection in Finance Research
url: https://www.ml-quant.com/papers/ssrn/4543446/
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 4543446
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4543446
featured: 2023-08-17
citations: unknown
topic: ML & AI Methods
---


# Machine Learning for Lag Selection in Finance Research

Random Regression Forests (RRF) are more effective than traditional methods and other machine learning techniques in choosing optimal lags for forecasting in various data series.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4543446
- Identifier: SSRN 4543446
- Released: 2022-06-01
- First featured: Quant Letter No. 12 (2023-08-17): https://www.ml-quant.com/issues/2023-08-17/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: ML & AI Methods

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