https://www.ml-quant.com/topics/ml-ai-methods/Machine-learning methods applied to finance: deep learning, boosting, RL and new architectures. en https://www.ml-quant.com/papers/arxiv/2609.27051/https://www.ml-quant.com/papers/arxiv/2609.27051/Fri, 25 Sep 2026 07:00:00 +0000Proposes a statistical referee that judges investment factors proposed by language-model agents using out-of-sample market outcomes, ensuring false-discovery control at any stopping time. https://www.ml-quant.com/papers/arxiv/2609.29014/https://www.ml-quant.com/papers/arxiv/2609.29014/Fri, 25 Sep 2026 07:00:00 +0000Proposes a multi-agent system with post-training that automates alpha factor mining locally, using diverse research paths and joint optimization to broaden exploration while maintaining prediction quality. https://www.ml-quant.com/papers/arxiv/2609.28876/https://www.ml-quant.com/papers/arxiv/2609.28876/Fri, 25 Sep 2026 07:00:00 +0000Introduces a replayable environment combining 1,568 resolved prediction-market questions with 18.8M dated news articles to benchmark and train language-model forecasting agents on historical data. https://www.ml-quant.com/papers/ssrn/7515878/https://www.ml-quant.com/papers/ssrn/7515878/Fri, 25 Sep 2026 07:00:00 +0000A survey examines how AI transforms information production, intermediation, and market structure, with implications for efficiency, competition and financial stability. https://www.ml-quant.com/papers/ssrn/7494298/https://www.ml-quant.com/papers/ssrn/7494298/Fri, 25 Sep 2026 07:00:00 +0000Reshaping the prediction target through location, scale and shape transformations raises long-short Sharpe from 0.68 to 1.69, with label choice mattering more than model choice. https://www.ml-quant.com/papers/ssrn/7490302/https://www.ml-quant.com/papers/ssrn/7490302/Fri, 25 Sep 2026 07:00:00 +0000Testing whether a large language model ranks stocks by forecasting or memory, the study finds a significant information-coefficient gap of 0.185 inside versus outside its training window, suggesting substantial look-ahead contamination. https://www.ml-quant.com/papers/ssrn/7485818/https://www.ml-quant.com/papers/ssrn/7485818/Fri, 25 Sep 2026 07:00:00 +0000The study measures recall versus forecasting in an LLM's stock rankings by comparing cross-sectional information coefficients inside and outside the training window. https://www.ml-quant.com/papers/ssrn/7498983/https://www.ml-quant.com/papers/ssrn/7498983/Fri, 25 Sep 2026 07:00:00 +0000The paper builds a closed-loop system where an LLM proposes equity factors penalized for execution costs and shows that accounting for trading costs dramatically improves net performance. https://www.ml-quant.com/papers/repec/nbr-nberwo-35431/https://www.ml-quant.com/papers/repec/nbr-nberwo-35431/Fri, 25 Sep 2026 07:00:00 +0000Optimized AI systems analyzing earnings call transcripts double explained variation in stock returns versus standard benchmarks while improving interpretability through human-readable decision rules. https://www.ml-quant.com/papers/repec/cpr-ceprdp-20439/https://www.ml-quant.com/papers/repec/cpr-ceprdp-20439/Fri, 25 Sep 2026 07:00:00 +0000Tree-based machine learning models predict the full distribution of financial market stress 27% better than traditional time-series methods, with macro uncertainty and monetary policy expectations as key drivers. https://www.ml-quant.com/papers/repec/cpr-ceprdp-20681/https://www.ml-quant.com/papers/repec/cpr-ceprdp-20681/Fri, 25 Sep 2026 07:00:00 +0000Q-learning and large language model investors generate systematically different behaviors in fund redemption settings, with Q-learning showing excessive coordination and amplified fragility under default risk. https://www.ml-quant.com/papers/arxiv/2603.29121/https://www.ml-quant.com/papers/arxiv/2603.29121/Fri, 03 Apr 2026 07:00:00 +0000The paper discusses a model that suggests combining human effort with partial automation is usually cheaper and more effective than fully automating complex tasks. https://www.ml-quant.com/papers/arxiv/2602.22750/https://www.ml-quant.com/papers/arxiv/2602.22750/Wed, 04 Mar 2026 07:00:00 +0000The article explains that the rise of generative AI is changing competition by focusing on ongoing decision-making, which can lead to unfair practices in the market. It suggests a solution called Neutral Inference to promote fairness and transparency. https://www.ml-quant.com/papers/arxiv/2601.20487/https://www.ml-quant.com/papers/arxiv/2601.20487/Mon, 02 Feb 2026 07:00:00 +0000AI agents in group settings can influence cooperation just like humans do, showing that social norms can adjust for both AI and human participants. https://www.ml-quant.com/papers/ssrn/4482553/https://www.ml-quant.com/papers/ssrn/4482553/Sun, 28 Dec 2025 07:00:00 +0000ML for Economics: Gingado is a developing Python library that helps incorporate machine learning into economic research by enhancing datasets and evaluating models. https://www.ml-quant.com/papers/ssrn/4478013/https://www.ml-quant.com/papers/ssrn/4478013/Sun, 28 Dec 2025 07:00:00 +0000Analyzing Japanese stock charts with CNN reveals predictive patterns for returns, independent of common momentum trends. https://www.ml-quant.com/papers/ssrn/4466139/https://www.ml-quant.com/papers/ssrn/4466139/Sun, 28 Dec 2025 07:00:00 +0000The research indicates that social financial advice significantly boosts stock market participation, especially through close social ties. https://www.ml-quant.com/papers/arxiv/2512.15088/https://www.ml-quant.com/papers/arxiv/2512.15088/Fri, 19 Dec 2025 07:00:00 +0000The SigMA neural architecture improves parameter estimation in stochastic differential equations using path signatures and self-attention, outperforming traditional methods across multiple datasets. https://www.ml-quant.com/papers/arxiv/2512.14967/https://www.ml-quant.com/papers/arxiv/2512.14967/Fri, 19 Dec 2025 07:00:00 +0000A new numerical method combines elicitability and deep learning for McKean-Vlasov stochastic equations, enabling efficient training of neural networks without expensive simulations, tested successfully on financial models. https://www.ml-quant.com/papers/arxiv/2512.14991/https://www.ml-quant.com/papers/arxiv/2512.14991/Fri, 19 Dec 2025 07:00:00 +0000An adaptive reinforcement learning algorithm enhances learning in controlled diffusion processes by partitioning state-action spaces, providing theoretical guarantees and effective results in applications like portfolio selection. https://www.ml-quant.com/papers/arxiv/2512.10913/https://www.ml-quant.com/papers/arxiv/2512.10913/Sun, 14 Dec 2025 07:00:00 +0000Reinforcement learning improves financial decision-making by simplifying complex investment problems, emphasizing clear explanations and strong reliability over complex algorithms. https://www.ml-quant.com/papers/arxiv/2512.08424/https://www.ml-quant.com/papers/arxiv/2512.08424/Sun, 14 Dec 2025 07:00:00 +0000AIgenerated explanations can improve decision-making when algorithms are right, but can mislead when they're wrong, highlighting a paradox in AI transparency for doctors. https://www.ml-quant.com/papers/arxiv/2512.08472/https://www.ml-quant.com/papers/arxiv/2512.08472/Sun, 14 Dec 2025 07:00:00 +0000Research indicates that age affects students' interest in computer science more than gender, suggesting educational approaches should consider developmental changes to boost engagement. https://www.ml-quant.com/papers/arxiv/2512.07828/https://www.ml-quant.com/papers/arxiv/2512.07828/Sun, 14 Dec 2025 07:00:00 +0000A study of AI agent use with the Comet browser reveals that personal productivity and learning are the main reasons users interact with these tools. https://www.ml-quant.com/papers/ssrn/4977007/https://www.ml-quant.com/papers/ssrn/4977007/Mon, 01 Dec 2025 07:00:00 +0000The research presents FINDALL, a search engine that effectively identifies relevant stocks for direct indexing, outperforming traditional ETFs with lower costs. https://www.ml-quant.com/papers/arxiv/2511.21975/https://www.ml-quant.com/papers/arxiv/2511.21975/Mon, 01 Dec 2025 07:00:00 +0000Organizations using AI face challenges in traditional ROI calculations due to risks, leading to a new framework that includes risk assessments. https://www.ml-quant.com/papers/arxiv/2511.21901/https://www.ml-quant.com/papers/arxiv/2511.21901/Mon, 01 Dec 2025 07:00:00 +0000The use of AI in regulated industries exposes gaps between technical risk assessments and compliance, prompting a new taxonomy for AI risk evaluation and financial impacts. https://www.ml-quant.com/papers/arxiv/2511.21802/https://www.ml-quant.com/papers/arxiv/2511.21802/Mon, 01 Dec 2025 07:00:00 +0000Research shows that large language models can indirectly collaborate in Dutch auctions to increase prices, influenced by market structure. https://www.ml-quant.com/papers/arxiv/2510.24990/https://www.ml-quant.com/papers/arxiv/2510.24990/Tue, 04 Nov 2025 07:00:00 +0000Lays out data economics: why data is special, documents AI training-data deals, proposes a hierarchy of data units, and lists key research questions. https://www.ml-quant.com/papers/arxiv/2510.24899/https://www.ml-quant.com/papers/arxiv/2510.24899/Tue, 04 Nov 2025 07:00:00 +0000Machine learning on incomplete ESSER plans estimates U.S. school districts spent about $2.2 billion on high‑dosage tutoring during COVID.