arXiv AI
Jul 8
When do prophets profit in prediction markets?
arXiv:2607. 06166v1 Announce Type: new Abstract: Prediction markets aggregate dispersed beliefs into prices that act as probabilistic forecasts of uncertain events.
Beyond Forecasting: The Belief-to-Trade Layer in Prediction-Market Agents
arXiv:2607. 03015v1 Announce Type: new Abstract: Forecasting future events has attracted growing attention as a testbed for general-purpose AI.
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arXiv Machine Learning
Jul 2
Verifiable Rewards for Calibrated Probabilistic Forecasting
arXiv:2607. 00164v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards can in principle train calibrated probabilistic forecasters, since a proper scoring rule such as the Brier score is computed from outcomes alone and is minimized in expectation by the true probability.
arXiv AI
Jun 2
Bridging the Last Mile of Time Series Forecasting with LLM Agents
arXiv:2606. 02497v1 Announce Type: new Abstract: Time series forecasting has advanced rapidly, especially with the emergence of foundation models that show strong zero-shot performance on numerical extrapolation.
arXiv AI
Jun 18
ForecastBench-Sim: A Simulated-World Forecasting Benchmark
arXiv:2606. 18686v1 Announce Type: new Abstract: Forecasting benchmarks for general-purpose AI systems usually inherit the constraints of the real world: outcomes resolve slowly, tail events are rare, and counterfactual questions are difficult to score.
arXiv AI
Jul 29
AlphaCrafter: Harnessing Multi-Agent Workflows for Cross-Sectional Quantitative Trading
arXiv:2605. 05580v2 Announce Type: replace Abstract: Quantitative trading agents have demonstrated substantial promise in automating factor discovery, signal aggregation, and portfolio execution.
arXiv Machine Learning
Jun 16
Reinforcement Learning for LLM-based Event Forecasting
arXiv:2606. 15917v1 Announce Type: new Abstract: We use Group Relative Policy Optimization (GRPO), a recently devised sample and memory efficient reinforcement learning method, to finetune pretrained LLMs in the range of 1.
arXiv Machine Learning
Jul 21
FinBench: Time-Gated Calibration and Uncertainty Benchmarking for Agentic Financial Forecasting
arXiv:2607. 16229v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as components of agentic systems that observe, plan, and act.
arXiv Machine Learning
Jul 20
CLaC@FinMMEval 2026 Task 3: Sentiment-Augmented Deep Reinforcement Learning for Active Trading -- An Alpha-Reward Approach
arXiv:2607. 16028v1 Announce Type: new Abstract: This paper presents our system for Task 3 of the CLEF 2026 FinMMEval Lab, which requires daily long, flat, or short trading decisions for Bitcoin (BTC) and Tesla (TSLA) using news and historical market data.
arXiv Machine Learning
Jun 25
From Forecasting Leaderboards to Deployment Decisions: A Fail-Closed Certification Protocol
arXiv:2606. 24996v1 Announce Type: new Abstract: Forecasting leaderboards rank models by predictive quality, but their winners are often read as deployment-ready top-1 advice.
arXiv AI
Jul 14
NextFund: A Unified Performance Tracking Platform for Agentic Portfolio Management
arXiv:2607. 11141v1 Announce Type: new Abstract: Large language models (LLMs) based agents are beginning to participate in portfolio construction and market analysis, where decisions must be justified under evolving information and risk constraints.
arXiv Machine Learning
1d ago
Learning Stock Trading Policies via Barycenter-Based Adversarial Inverse Reinforcement Learning
arXiv:2608. 15770v1 Announce Type: new Abstract: Designing effective trading strategies using reinforcement learning remains challenging due to delayed and noisy rewards, poor exploration, and the difficulty of enforcing explicit risk constraints.
arXiv AI
Jun 11
Forecasting Future Behavior as a Learning Task
arXiv:2606. 11445v1 Announce Type: new Abstract: Trust in an AI system is often anchored by explanations of how it works, which one then uses to forecast its behavior on new inputs.