GPT-Signal: Generative AI for Semi-automated Feature Engineering in the Alpha Research Process
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Abstract (arXiv)
In the trading process, financial signals often imply the time to buy and sell assets to generate excess returns compared to a benchmark (e.g., an index). Alpha is the portion of an asset's return that is not explained by exposure to this benchmark, and the alpha research process is a popular technique aiming at developing strategies to generate alphas and gain excess returns. Feature Engineering, a significant pre-processing procedure in machine learning and data analysis that helps extract and create transformed features from raw data, plays an important role in algorithmic trading strategies and the alpha research process. With the recent development of Generative Artificial Intelligence(Gen AI) and Large Language Models (LLMs), we present a novel way of leveraging GPT-4 to generate new return-predictive formulaic alphas, making alpha mining a semi-automated process, and saving time and energy for investors and traders.
Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). First posted on arXiv 24 Oct 2024.
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Citing papers per year: 2024: 1; 2025: 3; 2026: 3.
7 papers.
- 2025Following the Autoregressive Nature of LLM Embeddings via Compression and Alignmentcited by 14
- 2025DLRREC: Denoising Latent Representations via Multi-Modal Knowledge Fusion in Deep Recommender Systemscited by 5
- 2024Enhancing Exchange Rate Forecasting with Explainable Deep Learning Modelscited by 2
- 2026Fin-Bias: Comprehensive Evaluation for LLM Decision-Making under human bias in Finance Domaincited by 1
- 2025Gradient Boosting Decision Tree with LSTM for Investment Predictioncited by 0
- 2026LATTEArena: An Evaluation Framework for LLM-powered Tabular Feature Engineering (Extended Version)cited by 0
- 2026Agentic Empirical Asset Pricing: Methodological Foundationscited by 0
- 2026Agentic Empirical Asset Pricing: Methodological Foundations1 Sep 2026
- 2026LATTEArena: An Evaluation Framework for LLM-powered Tabular Feature Engineering (Extended Version)8 Jun 2026
- 2026Fin-Bias: Comprehensive Evaluation for LLM Decision-Making under human bias in Finance Domain9 May 2026
- 2025DLRREC: Denoising Latent Representations via Multi-Modal Knowledge Fusion in Deep Recommender Systems29 Nov 2025
- 2025Gradient Boosting Decision Tree with LSTM for Investment Prediction29 May 2025
- 2025Following the Autoregressive Nature of LLM Embeddings via Compression and Alignment17 Feb 2025
- 2024Enhancing Exchange Rate Forecasting with Explainable Deep Learning Models25 Oct 2024