arXiv Open Access 2025

Predicting Market Troughs: A Machine Learning Approach with Causal Interpretation

Peilin Rao Randall R. Rojas

Lihat Sumber

Abstrak

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.

Topik & Kata Kunci

q-fin.ST econ.EM stat.ML

Penulis (2)

Peilin Rao

Randall R. Rojas

Format Sitasi

APA MLA BibTeX

Rao, P., Rojas, R.R. (2025). Predicting Market Troughs: A Machine Learning Approach with Causal Interpretation. https://arxiv.org/abs/2509.05922

Akses Cepat

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Informasi Jurnal

Tahun Terbit: 2025
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓