---
title: Teach Machine Asset Pricing
url: https://www.ml-quant.com/papers/ssrn/4598745/
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 4598745
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4598745
featured: 2023-10-12
citations: 0
topic: Asset Pricing & Factors
---


# Teach Machine Asset Pricing

Stock Return Prediction: The article discusses how combining finance theories with big data can improve stock return predictions, with theory-guided models outperforming purely data-driven ones.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4598745
- Identifier: SSRN 4598745
- Released: 2023-09-27
- First featured: Quant Letter No. 20 (2023-10-12): https://www.ml-quant.com/issues/2023-10-12/
- Citations (Semantic Scholar): 0
- Published in: not yet
- Topic: Asset Pricing & Factors

## Related

- [A Deep Structural Model for Empirical Asset Pricing](https://www.ml-quant.com/papers/ssrn/4602537/): ML and Theory Integration: The article introduces a new model that merges deep learning and structural models for better prediction of equity returns and covariances, leading to higher returns and sharpe ratios.
- [Generalized Autoregressive Conditional Betas: A New Multivariate Score-Driven Filter](https://www.ml-quant.com/papers/ssrn/4602060/): New: A new asset pricing model, the generalized ACB, is introduced, enhancing the autoregressive conditional beta model by driving dynamic interaction effects among beta coefficients.
- [Dynamic Time Warping for Lead-Lag Relationships in Lagged Multi-Factor Models](https://www.ml-quant.com/papers/arxiv/2309.08800/): A new technique using dynamic time warping has been created to identify lead-lag relationships in multivariate time series systems, demonstrated in financial markets.
- [Bubble economics](https://www.ml-quant.com/papers/arxiv/2311.03638/): Nonstationary Phenomenon: The article discusses the theory of rational asset price bubbles, highlighting that bubbles linked to real assets like stocks and housing are nonstationary phenomena tied to unbalanced growth.
- [The CAPM, APT, and PAPM](https://www.ml-quant.com/papers/ssrn/4566414/): CAPM, APT, and PAPM: The Popularity Asset Pricing Model (PAPM) improves on the Capital Asset Pricing Model (CAPM) by considering investor preferences and beliefs, addressing CAPM's empirical limitations.
- [Machine Learning and the Cross-Section of Emerging Market Corporate Bond Returns](https://www.ml-quant.com/papers/ssrn/4632924/): Machine learning models considering nonlinearities and interactions offer better predictions of corporate bond behavior in emerging markets with high transaction costs, with key predictors tied to low-risk macro and momentum factors.