mlsanityData to 7 Oct 2026

Regression and Forecasting of U.S. Stock Returns Based on LSTM

arXiv 2502.05210 ↗First posted 3 Feb 2025q-fin.ST cs.LGcited by 4

Not on the map. Why?

Abstract (arXiv)

This paper analyses the investment returns of three stock sectors, Manuf, Hitec, and Other, in the U.S. stock market, based on the Fama-French three-factor model, the Carhart four-factor model, and the Fama-French five-factor model, in order to test the validity of the Fama-French three-factor model, the Carhart four-factor model, and the Fama-French five-factor model for the three sectors of the market. French five-factor model for the three sectors of the market. Also, the LSTM model is used to explore the additional factors affecting stock returns. The empirical results show that the Fama-French five-factor model has better validity for the three segments of the market under study, and the LSTM model has the ability to capture the factors affecting the returns of certain industries, and can better regress and predict the stock returns of the relevant industries. Keywords- Fama-French model; Carhart model; Factor model; LSTM model.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 14 of its 42 references that are in the map. First posted on arXiv 3 Feb 2025.

Builds on

14 of 42 references.

References · 14

  1. 2024Agent-Pro: Learning to Evolve via Policy-Level Reflection and Optimizationcited by 93
  2. 2024Self-Contrast: Better Reflection Through Inconsistent Solving Perspectivescited by 71
  3. 2024Attentive Eraser: Unleashing Diffusion Model's Object Removal Potential via Self-Attention Redirection Guidancecited by 63
  4. 2024TextSquare: Scaling up Text-Centric Visual Instruction Tuningcited by 62
  5. 2022Optimal Boxes: Boosting End-to-End Scene Text Recognition by Adjusting Annotated Bounding Boxes via Reinforcement Learningcited by 33
  6. 2021ReLAX: Reinforcement Learning Agent eXplainer for Arbitrary Predictive Modelscited by 25
  7. 2024MT2ST: Adaptive Multi-Task to Single-Task Learningcited by 16
  8. 2025Detection of AI Deepfake and Fraud in Online Payments Using GAN-Based Modelscited by 14
  9. 2020Forecasting directional movements of stock prices for intraday trading using LSTM and random forestscited by 13
  10. 2024Deep Learning for Cross-Border Transaction Anomaly Detection in Anti-Money Laundering Systemscited by 9
  11. 2024A Consolidated Volatility Prediction with Back Propagation Neural Network and Genetic Algorithmcited by 5
  12. 2025Credit Risk Identification in Supply Chains Using Generative Adversarial Networkscited by 5
2 more
  1. 2021Costly Features Classification using Monte Carlo Tree Searchcited by 4
  2. 2024Developing Cryptocurrency Trading Strategy Based on Autoencoder-CNN-GANs Algorithmscited by 3

Built on by

Cited by year

Citing papers per year: 2025: 4.

4 papers.

  1. 2025DREAM: Disentangling Risks to Enhance Safety Alignment in Multimodal Large Language Modelscited by 6
  2. 2025A Comprehensive Review of AI Agents: Transforming Possibilities in Technology and Beyondcited by 6
  3. 2025Meta-Learning for Cold-Start Personalization in Prompt-Tuned LLMscited by 5
  4. 2025Credit Risk Analysis for SMEs Using Graph Neural Networks in Supply Chaincited by 2