Can Large Language Models Beat Wall Street? Unveiling the Potential of AI in Stock Selection

Bootstrap Methods for Standard Errors, Confidence Intervals, and Other Measures of Statistical Accuracy

Efron, B., & Tibshirani, R. (1986) · Statistical Science · doi:10.1214/ss/1177013815 · Cited by 6,033 · see citing works

Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

Wei, J., Wang, X., Schuurmans, D., Bosma, M., Ichter, B., Xia, F., Chi, E., Le, Q., & Zhou, D. (2022) · arXiv · doi:10.48550/arxiv.2201.11903 · Cited by 4,263 · see citing works

The Efficient Market Hypothesis and Its Critics

Malkiel, B. G. (2003) · Journal of Economic Perspectives · doi:10.1257/089533003321164958 · Cited by 2,161 · see citing works

Experimental evidence on the productivity effects of generative artificial intelligence

Noy, S., & Zhang, W. (2023) · Science · doi:10.1126/science.adh2586 · Cited by 2,150 · see citing works

MPNet: Masked and Permuted Pre-training for Language UnderstandingPreprint

Song, K., Tan, X., Qin, T., Lu, J., & Liu, T. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2004.09297 · Cited by 713 · see citing works

FinBERT: Financial Sentiment Analysis with Pre-trained Language Models

Araci, D. (2019) · arXiv · Cited by 602 · see citing works

Momentum and Autocorrelation in Stock Returns

Lewellen, J. W. (2002) · Review of Financial Studies · doi:10.1093/rfs/15.2.533 · Cited by 491 · see citing works

Can ChatGPT forecast stock price movements? Return predictability and large language models

Lopez-Lira, A., & Tang, Y. (2026) · Journal of Financial Economics · doi:10.1016/j.jfineco.2026.104335 · Cited by 425 · see citing works

BloombergGPT: A Large Language Model for Finance

Wu, S., Irsoy, O., Lu, S., Dabravolski, V., Dredze, M., Gehrmann, S., Kambadur, P., Rosenberg, D., & Mann, G. (2023) · arXiv · Cited by 357 · see citing works

How Close is ChatGPT to Human Experts? Comparison Corpus, Evaluation, and Detection

Guo, B., Zhang, X., Wang, Z., Jiang, M., Nie, J., Ding, Y., Yue, J., & Wu, Y. (2023) · arXiv · doi:10.48550/arxiv.2301.07597 · Cited by 318 · see citing works

A Survey on In-context Learning

Dong, Q., Li, L., Dai, D., Zheng, C., Ma, J., Li, R., Xia, H., Xu, J., Wu, Z., Liu, T., et al. (2023) · arXiv · doi:10.48550/arxiv.2301.00234 · Cited by 248 · see citing works

Harnessing the Power of ChatGPT for Automating Systematic Review Process: Methodology, Case Study, Limitations, and Future Directions

Alshami, A., Elsayed, M., Ali, E., Eltoukhy, A. E. E., & Zayed, T. (2023) · Systems · doi:10.3390/systems11070351 · Cited by 202 · see citing works

Transforming sentiment analysis in the financial domain with ChatGPT

Fatouros, G., Soldatos, J. K., Kouroumali, K., Makridis, G., & Kyriazis, D. (2023) · Machine Learning with Applications · doi:10.1016/j.mlwa.2023.100508 · Cited by 200 · see citing works

Temporal Data Meets LLM - Explainable Financial Time Series ForecastingPreprint

Yu, X., Chen, Z., Ling, Y., Dong, S., Liu, Z., & Lu, Y.-B. (2023) · arXiv.org · doi:10.48550/arxiv.2306.11025 · Cited by 145 · see citing works

Financial Institutions, Markets, and Money.

Gregory, O. K., Kidwell, D. S., & Peterson, R. L. (1982) · The Journal of Finance · doi:10.2307/2327721 · Cited by 131 · see citing works

Value Investing: From Graham to Buffett and Beyond

Greenwald, B. C. N., Kahn, J., Sonkin, P. D., & van Biema, M. (2001) · Medical Entomology and Zoology · Cited by 129 · see citing works

ChatGPT: Unlocking the future of NLP in finance

Zaremba, A., & Demir, E. (2023) · Modern Finance · doi:10.61351/mf.v1i1.43 · Cited by 121 · see citing works

Sentiment trading with large language models

Kirtac, K., & Germano, G. (2024) · Finance Research Letters · doi:10.1016/j.frl.2024.105227 · Cited by 115 · see citing works

Do LLMs Exhibit Human-like Response Biases? A Case Study in Survey Design

Tjuatja, L., Chen, V., Wu, T., Talwalkwar, A., & Neubig, G. (2024) · Transactions of the Association for Computational Linguistics · doi:10.1162/tacl_a_00685 · Cited by 100 · see citing works

Bloated Disclosures: Can ChatGPT Help Investors Process Information?Preprint

Kim, A. G., Muhn, M., & Nikolaev, V. V. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4425527 · Cited by 92 · see citing works

ChatGPT: Unlocking the Future of NLP in FinancePreprint

Zaremba, A., & Demir, E. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4323643 · Cited by 65 · see citing works

ChatGPT Informed Graph Neural Network for Stock Movement PredictionPreprint

Chen, Z., Zheng, L., Cheng, L., Yuan, J., & Zhu, D. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4464002 · Cited by 56 · see citing works

Deep learning enhancing banking services: a hybrid transaction classification and cash flow prediction approach

Kotios, D., Makridis, G., Fatouros, G., & Kyriazis, D. (2022) · Journal Of Big Data · doi:10.1186/s40537-022-00651-x · Cited by 52 · see citing works

The role of Reddit in the GameStop short squeeze

Anand, A., & Pathak, J. (2021) · Economics Letters · doi:10.1016/j.econlet.2021.110249 · Cited by 45 · see citing works

DeepVaR: a framework for portfolio risk assessment leveraging probabilistic deep neural networks

Fatouros, G., Makridis, G., Kotios, D., Soldatos, J. K., Filippakis, M. Ε., & Kyriazis, D. (2022) · Digital Finance · doi:10.1007/s42521-022-00050-0 · Cited by 36 · see citing works

Estimating the impact of good news on stock market volatility

Malik, F. (2011) · Applied Financial Economics · doi:10.1080/09603107.2010.534063 · Cited by 33 · see citing works

Behavioral biases in pension fund trustees’ decision making

Weiss‐Cohen, L., Ayton, P., Clacher, I., & Thoma, V. (2019) · Review of Behavioral Finance · doi:10.1108/rbf-05-2018-0049 · Cited by 16 · see citing works

Can GPT models be Financial Analysts? An Evaluation of ChatGPT and GPT-4 on mock CFA ExamsPreprint

Callanan, E., Mbakwe, A. B., Papadimitriou, A., Pei, Y., Sibue, M., Zhu, X., Ma, Z., Liu, X., & Shah, S. (2023) · RePEc: Research Papers in Economics · doi:10.48550/arxiv.2310.08678 · Cited by 15 · see citing works

Does 0DTE Options Trading Increase Volatility?Preprint

Brogaard, J., Han, J.-H., & Won, P. Y. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4426358 · Cited by 12 · see citing works

Drawdown Measures: Are They All the Same?

Korn, O., Möller, P. M., & Schwehm, C. (2022) · The Journal of Portfolio Management · doi:10.3905/jpm.2022.1.346 · Cited by 7 · see citing works

Fusion-Eval: Integrating Assistant Evaluators with LLMs

Shu, L., Wichers, N., Luo, L., Zhu, Y., Liu, Y., Chen, J., & Meng, L. (2024) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2024.emnlp-industry.18 · Cited by 5 · see citing works

Cognitive Biases in Natural Language: Automatically Detecting, Differentiating, and Measuring Bias in TextPreprint

Atreides, K., & Kelley, D. J. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4568851 · Cited by 2 · see citing works

Fusion-Eval: Integrating Assistant Evaluators with LLMsPreprint

Shu, L., Wichers, N., Luo, L., et al. (2023) · arXiv (Cornell University) · doi:10.48550/arxiv.2311.09204 · Cited by 1 · see citing works

Opportunities and Challenges of Generative-AI in Finance

Desai, A. P., Ravi, T., Luqman, M., Mallya, G., Kota, N., & Yadav, P. (2024) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata62323.2024.10825658 · Cited by 29 · see citing works

Generative AI Solutions to Empower Financial Firms

Dubey, S. S., Astvansh, V., & Kopalle, P. K. (2024) · Journal of Public Policy & Marketing · doi:10.1177/07439156241311300 · Cited by 27 · see citing works

LLM-Powered AI Agent Systems and Their Applications in Industry

Liang, G., & Tong, Q. (2025) · IEEE World AI IoT Congress (AIIoT) · doi:10.1109/aiiot65859.2025.11105299 · Cited by 32 · see citing works

Comparative Investigation of GPT and FinBERT’s Sentiment Analysis Performance in News Across Different Sectors

Kang, J.-W., & Choi, S. (2025) · Electronics · doi:10.3390/electronics14061090 · Cited by 17 · see citing works

AI in Investment Analysis: LLMs for Equity Stock Ratings

Papasotiriou, K., Sood, S., Reynolds, S., & Balch, T. R. (2024) · ACM International Conference on AI in Finance (ICAIF) · doi:10.1145/3677052.3698694 · Cited by 12 · see citing works

Large Language Model Agent in Financial Trading: A Survey

Ding, H., Li, Y., Wang, J., Chen, H., Guo, D., & Zhang, Y. (2026) · Proceedings of the 2026 9th International Conference on Computers in Management and Business · doi:10.1145/3802463.3802475 · Cited by 10 · see citing works

Industrial large model: A survey

Zhou, J., Cao, Y., Lu, Q., Zhang, Y., Liu, C., Zhang, S., & Qu, J. (2024) · MATEC Web of Conferences · doi:10.1051/matecconf/202440110009 · Cited by 5 · see citing works

Toward profitable energy futures trading strategies using reinforcement learning incorporating disagreement and connectedness methods enabled by large language models

Cui, T., Ye, Y., Li, Y., Du, N., Song, X., Zhu, Y., Yang, X., & Štrbac, G. (2025) · Energy and AI · doi:10.1016/j.egyai.2025.100562 · Cited by 6 · see citing works

Emulating fundamental analysts: Analytical stage-based multi-agent framework enhanced with expert guidance and Preference-Anchored Likelihood Adjustment

Xu, T., Piao, Z. H., Mukai, T., Murayama, Y., & Izumi, K. (2025) · Intelligent Systems with Applications · doi:10.1016/j.iswa.2025.200496 · Cited by 4 · see citing works

Reasoning or Overthinking: Evaluating Large Language Models on Financial Sentiment Analysis

Vamvourellis, D., & Mehta, D. B. (2025) · ACM International Conference on AI in Finance (ICAIF) · doi:10.1145/3768292.3770341 · Cited by 2 · see citing works

Comparative Analysis and Evaluation of SLMs and LLMs for Stock Price Movement Prediction

van der Leij, K., Manias, G., Leung, Y. K., & van den Heuvel, W. (2025) · IFIP advances in information and communication technology · doi:10.1007/978-3-031-96235-6_21 · Cited by 1 · see citing works

Quantitative Financial Models with Scenarios from LLM: Temporal Fusion Transformers as Alternative Monte-CarloPreprint

Aldridge, I., & Kim, D. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4999492 · Cited by 1 · see citing works

ВИКОРИСТАННЯ ВЕЛИКИХ МОВНИХ МОДЕЛЕЙ ДЛЯ АНАЛІЗУ ЧАСОВИХ РЯДІВ У РОЗДРІБНІЙ ТОРГІВЛІ: ПЕРСПЕКТИВИ ТА МОЖЛИВОСТІ

Косован, О., & Datsko, M. (2024) · Цифрова економіка та економічна безпека · doi:10.32782/dees.10-35

No matter your financial literacy: Simplicity wins when choosing a fund

Gong, Z. F., & Müller, S. (2026) · Journal of Behavioral and Experimental Finance · doi:10.1016/j.jbef.2026.101188

AI's Impact on Financial Services, Auditing, and Investment Strategies

Irfan, M., Dias, R., Hooda, J., Singh, K. A., & Bang, S. S. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-0129-7.ch008

Generalizable Multi-Agent Framework for Quantitative Trading of US Education Funds

Xu, K., Zhang, Z., Wilson, A., Yu, Q., Zhou, L., & Jiang, Y. (2024) · Innovations in Applied Engineering and Technology · doi:10.62836/iaet.v3i1.362

Predicting Business Angel Early-Stage Decision Making Using AIPreprint

Katcharovski, Y., & Maxwell, A. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5342945

Predicting Business Angel Early-Stage Decision Making using AIPreprint

Katcharovski, Y., & Maxwell, A. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5347382

Mitigating upside gains and downside losses through AI investment and greenness of stocks

Shabbir, B., Ashraf, N., Khurshid, J., Tariq, A., Jamil, L., & Khalid, Z. (2025) · Discover Sustainability · doi:10.1007/s43621-025-01377-5

Dual-Path Transformer: Aligning Text Embeddings with Market Movements for a New Paradigm of Cross-Modal Financial Time Series Prediction

Zhang, H., Kong, H., & Wang, S. (2026) · Lecture notes in computer science · doi:10.1007/978-981-95-4158-4_13

FALLMAS: An LLM-Based Multi-Agent System for Automated Financial Analysis and Strategic Reporting

Bouchtib, H., Tabaa, M., Karboub, K., & Hamlich, M. (2026) · IEEE International Multidisciplinary Conference on Engineering Technology (IMCET) · doi:10.1109/imcet69180.2026.11503762

HumAIne-Chatbot: Real-Time Personalized Conversational AI via Reinforcement Learning for Public-Interest Digital Services

Makridis, G., Fragiadakis, G., Oliveira, J., Saraiva, T., Mavrepis, P., Fatouros, G., & Kyriazis, D. (2026) · Journal of artificial intelligence for sustainable development. · doi:10.69828/4d4kwm

On Advancing Elliott Waves Technical Analysis with AI Agents

Wawer, M., & Chudziak, J. A. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-25029-2_10

AI-Driven Stock Selection and Investment Strategy: Integrating Fundamental Screening and Technical Indicators

Shen, J.-H., & Lu, C.-F. (2026) · Smart innovation, systems and technologies · doi:10.1007/978-3-032-24063-7_11

Generative AI-Enhanced Sector-Based Investment Portfolio Construction

Romanko, O., Voronina, A., Cao, R., Kwon, R. H., & Mendoza‐Arriaga, R. (2026) · Operations Research Forum · doi:10.1007/s43069-026-00686-3

Sentiment-Driven ETF Decision: A Fully LLM-Centric Agent Framework with Dynamic Constraint Prompts

Tan, Z., & Wu, Y. (2026) · Lecture notes in networks and systems · doi:10.1007/978-3-032-23396-7_10

Can Large Language Models beat wall street? Evaluating GPT-4’s impact on financial decision-making with MarketSenseAI

Fatouros, G., Metaxas, K., Soldatos, J. K., & Kyriazis, D. (2024) · Neural Computing and Applications · doi:10.1007/s00521-024-10613-4 · Cited by 30 · see citing works

StockGPT: A GenAI Model for Stock Prediction and TradingPreprint

Mai, D. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4787199 · Cited by 9 · see citing works

Hybrid Sentiment Analysis in Financial Markets: Multi-Stage LLM Integration for Market-Neutral Alpha Generation

Stübinger, J., & Wöhner, L. (2026) · AI · doi:10.3390/ai7040138 · Cited by 1 · see citing works

From text to trade: harnessing the potential of generative AI for investor sentiment analysis in financial markets through large language models

Hicham, N., & Habbat, N. (2025) · International Journal of Information Technology · doi:10.1007/s41870-025-02622-w · Cited by 5 · see citing works

MarketSenseAI 2.0: Enhancing Stock Analysis through LLM AgentsPreprint

Fatouros, G., Metaxas, K., Soldatos, J., & Karathanassis, M. (2025) · RePEc: Research Papers in Economics · doi:10.48550/arxiv.2502.00415 · Cited by 2 · see citing works