---
title: Robust Monitoring Machine for R2-Hacking
url: https://www.ml-quant.com/papers/repec/spr-fininn-v-9-y-2023-i-1-d-10-1186-s40854-023-00497-z/
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: RePEc:spr:fininn:v:9:y:2023:i:1:d:10.1186_s40854-023-00497-z
source_url: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Flink.springer.com%2F10.1186%2Fs40854-023-00497-z%3Bh%3Drepec%3Aspr%3Afininn%3Av%3A9%3Ay%3A2023%3Ai%3A1%3Ad%3A10.1186_s40854-023-00497-z
featured: 2023-07-26
citations: unknown
topic: ML & AI Methods
---


# Robust Monitoring Machine for R2-Hacking

The research introduces a method using collective machine learning to prevent data manipulation in test samples, enhancing the accuracy and consistency of stock return predictions and preventing R^2-hacking issues.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Flink.springer.com%2F10.1186%2Fs40854-023-00497-z%3Bh%3Drepec%3Aspr%3Afininn%3Av%3A9%3Ay%3A2023%3Ai%3A1%3Ad%3A10.1186_s40854-023-00497-z
- Identifier: RePEc:spr:fininn:v:9:y:2023:i:1:d:10.1186_s40854-023-00497-z
- Released: 2023-07-26
- First featured: Quant Letter No. 9 (2023-07-26): https://www.ml-quant.com/issues/2023-07-26/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: ML & AI Methods

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