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An introduction to the awesome-systematic-trading open-source project on GitHub (5.3K Stars), which curates the market data, backtesting, live trading, AI quant, and risk management tools needed for quantitative trading into a comprehensive navigation index, covering markets such as stocks, futures, options, and cryptocurrencies.
该论文提出一种将情感分析深度融入Actor-Critic类深度强化学习智能体（A2C、PPO、DDPG、TD3、SAC）的股票交易策略，发现结合Q学习的策略优化方法在融合情感信息后能显著提升盈利与风险规避能力。
Quant-Arena introduces an end-to-end benchmark and public leaderboard evaluating whether LLM agents can build profitable trading strategies on historical A-share data that generalize to a sealed future year. Of nine frontier models, GPT-6 Astra scored highest, but none beat an equal-weight market portfolio in 2024.
StochLOB 提出一种仅在训练阶段使用的评分匹配框架，用跳跃 Lévy 噪声和截断 α-stable 噪声替代布朗高斯扩散污染，以更真实地刻画限价订单簿数据的重尾与跳跃特性，从而提升 BTC 及山寨币中价趋势预测在压力窗口下的稳健性。
ResNLS is a hybrid neural network model combining ResNet and LSTM that improves stock price forecasting by emphasizing dependencies between stock prices, achieving at least 20% improvement over baselines and demonstrating practical trading applications.
TradingAgents is an open-source multi-agent framework for AI-driven financial trading, supporting multiple AI models and data sources, with checkpointing functionality.
Mathematician Yilin Wang's work on Loewner energy quantifies how far curves deviate from randomness, aiding Citadel in distinguishing true market signals from noise with $500,000 rewards for precise computation.
The author built an autonomous swing trading pipeline using Hermes AI that screens stocks, tracks performance, and self-validates strategy changes every 48 hours, achieving a 60% win rate over two months.
This GitHub repository named finance-quant-skills provides 13 installable Agent Skills specifically designed for A-share quantitative trading, covering functions such as data acquisition, strategy backtesting, and document query.
Tonghuashun officially open-sources its A-share data service, providing comprehensive market data through a single API Key, with native support for MCP and Agent Skill, facilitating use by AI Agents and quantitative development.
NautilusTrader is a high-performance, open-source trading engine with a Rust core and Python strategy support, enabling seamless transition from backtesting to live trading across multiple assets and exchanges.
This article introduces eight GitHub repositories covering AI side hustles, remote work, quantitative trading, and more, helping users leverage technical resources to increase income.
This article provides a detailed introduction to the InStock stock system, an open-source quantitative investment tool that supports data fetching, technical indicator calculation, K-line pattern recognition, and strategy backtesting, among other functions.
The user is open-sourcing their profitable quantitative trading code and introducing the QTrader platform, which offers strategy management, backtesting, and simulated trading features.
Jane Street, a quantitative trading firm, suffered a $15 billion financial loss following a meltdown incident involving its Situational Awareness system.
This article introduces a GitHub repository called awesome-systematic-trading, which categorizes free open-source quantitative trading libraries and resources by programming language, helping developers quickly find suitable tools.
AQuA is a research system with two independent language-model-driven agents that recursively self-improve in quantitative trading research, achieving strong information coefficients on crypto and US equities while using sealed sandboxes to prevent data leakage.
Introduces a full-stack hands-on Python quantitative trading video tutorial, covering data scraping, machine learning prediction, portfolio optimization, and strategy backtesting, and mentions the open-source quantitative trading execution system Kungfu.
This tweet recommends four high-Star open-source financial analysis tools that can replace Bloomberg Terminal, covering daily briefings, professional terminals, algorithmic trading, and in-depth research, all deployable for free on GitHub.
Vibe-Trading is a personal AI trading agent from the HKUDS team at HKU, supporting natural language generation of quantitative strategies, one-click backtesting, and multi-agent collaboration. It comes with an embedded library of 456 alpha factors and is open-sourced.