Can AI Make Money in Crypto? Measuring the Gap from Backtests to Real Markets
cs.AI
Submitted: 2026-09-28
Updated: 2026-09-28
Code: https://github.com/Starlien95/Awesome-TradingAI
Sources
- An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling
- StockBench: Can LLM Agents Trade Stocks Profitably In Real-world Markets?
- AI-Trader: Benchmarking Autonomous Agents in Real-Time Financial Markets
- ADD: Augmented Disentanglement Distillation Framework for Improving Stock Trend Forecasting
- TradingAgents: Multi-Agents LLM Financial Trading Framework
- Instance-wise Graph-based Framework for Multivariate Time Series Forecasting
- HIST: A Graph-based Framework for Stock Trend Forecasting via Mining Concept-Oriented Shared Information
- Qwen3 Technical Report
- FinGPT: Open-Source Financial Large Language Models
- Qlib: An AI-oriented Quantitative Investment Platform
- LiveTradeBench: Seeking Real-World Alpha with Large Language Models
Related papers
- MAVEN-T: Reinforced Heterogeneous Distillation for Real-Time Multi-Agent Trajectory Prediction
- Model Discovery Agent: LLM-assisted Bayesian experiment design for data-efficient discovery of mechanistic world models
- Agents' Last Exam
- The Clinician's Veto: Navigating Trust, Liability, and Uncertainty in Autonomous AI Prescribing
- MindHelper: Closed-Loop Embodied Mental-State Reasoning for Precision Intervention
- Incumbent Advantage: Brand Bias and Cognitive Manipulation Dynamics in LLM Recommendation Systems