Predicting Market Troughs: A Machine Learning Approach with Causal Interpretation

Fuente: arXiv
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Main Authors: Rao, Peilin, Rojas, Randall R.
Format: Preprint
Published: 2025
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author Rao, Peilin
Rojas, Randall R.
author_facet Rao, Peilin
Rojas, Randall R.
contents This paper provides robust, new evidence on the causal drivers of market troughs. We demonstrate that conclusions about these triggers are critically sensitive to model specification, moving beyond restrictive linear models with a flexible DML average partial effect causal machine learning framework. Our robust estimates identify the volatility of options-implied risk appetite and market liquidity as key causal drivers, relationships misrepresented or obscured by simpler models. These findings provide high-frequency empirical support for intermediary asset pricing theories. This causal analysis is enabled by a high-performance nowcasting model that accurately identifies capitulation events in real-time.
format Preprint
id arxiv_https___arxiv_org_abs_2509_05922
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Predicting Market Troughs: A Machine Learning Approach with Causal Interpretation
Rao, Peilin
Rojas, Randall R.
Statistical Finance
Econometrics
Machine Learning
91G80, 62P05
J.4
This paper provides robust, new evidence on the causal drivers of market troughs. We demonstrate that conclusions about these triggers are critically sensitive to model specification, moving beyond restrictive linear models with a flexible DML average partial effect causal machine learning framework. Our robust estimates identify the volatility of options-implied risk appetite and market liquidity as key causal drivers, relationships misrepresented or obscured by simpler models. These findings provide high-frequency empirical support for intermediary asset pricing theories. This causal analysis is enabled by a high-performance nowcasting model that accurately identifies capitulation events in real-time.
title Predicting Market Troughs: A Machine Learning Approach with Causal Interpretation
topic Statistical Finance
Econometrics
Machine Learning
91G80, 62P05
J.4
url https://arxiv.org/abs/2509.05922