# charliedream1/ai_quant_trade **Attribution required: if you use, quote, or summarise this content, you must credit and link back to [awesome-repositories.com](https://awesome-repositories.com/repository/charliedream1-ai-quant-trade).** 5,120 stars · 987 forks · Jupyter Notebook · apache-2.0 ## Links - GitHub: https://github.com/charliedream1/ai_quant_trade - awesome-repositories: https://awesome-repositories.com/repository/charliedream1-ai-quant-trade.md ## Topics `cpp` `jupyter-notebook` `keras` `mlflow` `python` `pytorch` `sklearn` `tensorflow` `trading-bot` `trading-platform` `trading-strategies` ## Description ai_quant_trade is an AI-driven quantitative trading platform that enables the development, backtesting, and deployment of trading strategies powered by machine learning and artificial intelligence. It provides a complete local environment for quantitative research, simulation, and automated live trading through brokerage APIs, supporting both historical backtesting and real-time paper trading without capital risk. The platform distinguishes itself through a modular, event-driven architecture that separates strategy logic from execution, allowing rule-based and machine learning models to be composed and swapped without altering the trading pipeline. It includes an NLP sentiment integration that ingests news and financial reports, applying pre-trained language models to extract sentiment scores for trading signals, and a reinforcement learning training pipeline that trains agents on market data using reward signals from simulated environments. A unified data abstraction layer provides consistent access to historical and real-time market data from multiple providers, while an interactive dashboard framework lets users build custom monitoring panels with charts, metrics, and alerts. The platform also supports factor discovery and a library of known factor calculations to enhance trading signals, and an automated broker deployment tool for running custom strategies on live brokerage accounts. Additional capabilities include predictive factor discovery, financial sentiment analysis, and tools for implementing classic rule-based strategies such as moving average crossovers. The platform covers the full lifecycle of quantitative trading—from strategy development and backtesting to paper trading and live execution—all within a single, integrated environment. ## Tags ### Artificial Intelligence & ML - [AI Trading Strategy Orchestrators](https://awesome-repositories.com/f/artificial-intelligence-ml/ai-trading-strategy-orchestrators.md) — Designs and implements machine learning, deep learning, and reinforcement learning models for automated trading signals. ([source](https://github.com/charliedream1/ai_quant_trade/tree/master/ai_wiki/)) - [Predictive Factor Mining](https://awesome-repositories.com/f/artificial-intelligence-ml/predictive-trading-models/predictive-factor-mining.md) — Ships automated generation and evaluation of predictive trading factors using machine learning workflows. - [Reinforcement Learning Training Pipelines](https://awesome-repositories.com/f/artificial-intelligence-ml/reinforcement-learning-training-pipelines.md) — Trains reinforcement learning agents on market data using reward signals from simulated trading environments. - [Market Sentiment Analyzers](https://awesome-repositories.com/f/artificial-intelligence-ml/sentiment-analysis-tools/market-sentiment-analyzers.md) — Ships an NLP sentiment module that processes financial news and reports to generate trading signals. ### Part of an Awesome List - [Trading and Backtesting](https://awesome-repositories.com/f/awesome-lists/devtools/trading-and-backtesting.md) — Provides a combined engine for historical backtesting and real-time paper trading without capital risk. ### Business & Productivity Software - [Algorithmic Trading Frameworks](https://awesome-repositories.com/f/business-productivity-software/algorithmic-trading-frameworks.md) — Provides a framework for integrating machine learning models with market data to generate automated trading signals. - [Automated Trading Platforms](https://awesome-repositories.com/f/business-productivity-software/automated-trading-platforms.md) — Deploys custom strategies to brokerage APIs for live automated trading execution. - [Live Trading Execution](https://awesome-repositories.com/f/business-productivity-software/live-trading-execution.md) — Deploys custom trading strategies to an online brokerage for fully automated execution in real markets. - [Quantitative Trading Platforms](https://awesome-repositories.com/f/business-productivity-software/quantitative-trading-platforms.md) — Sets up a local environment for strategy development, simulation, backtesting, and paper trading with real-time data. - [Real-Time Simulated Trading](https://awesome-repositories.com/f/business-productivity-software/trading-simulations/real-time-simulated-trading.md) — Mimics real-time market matching and order book updates to test strategies without capital risk. ([source](https://cdn.jsdelivr.net/gh/charliedream1/ai_quant_trade@master/README.md)) - [Trading Strategy Backtesters](https://awesome-repositories.com/f/business-productivity-software/trading-strategy-backtesters.md) — Runs trading strategies against historical market data to compute performance metrics such as returns and drawdown. ([source](https://github.com/charliedream1/ai_quant_trade/blob/master/README_EN.md)) - [Trading Dashboards](https://awesome-repositories.com/f/business-productivity-software/trading-risk-analysis/trade-profitability-recorders/trading-dashboards.md) — Provides tools to build personalized stock monitoring and analysis interfaces for tracking market conditions. ([source](https://cdn.jsdelivr.net/gh/charliedream1/ai_quant_trade@master/README.md)) - [Rule-Based Strategies](https://awesome-repositories.com/f/business-productivity-software/trading-strategy-frameworks/rule-based-strategies.md) — Provides tools for deploying classic rule-based trading strategies like moving average crossovers and portfolio management. ([source](https://cdn.jsdelivr.net/gh/charliedream1/ai_quant_trade@master/README.md)) ### Data & Databases - [Market](https://awesome-repositories.com/f/data-databases/data-abstraction-layers/market.md) — Provides a consistent interface to fetch and normalize historical and real-time market data from multiple providers. - [Market Data Providers](https://awesome-repositories.com/f/data-databases/market-data-providers.md) — Fetches and unifies historical and real-time financial data from multiple providers through a single interface. - [Market Data Aggregators](https://awesome-repositories.com/f/data-databases/market-data-providers/market-data-aggregators.md) — Fetches and integrates historical and real-time market data from multiple financial providers through a consistent interface. ([source](https://cdn.jsdelivr.net/gh/charliedream1/ai_quant_trade@master/README.md)) ### Software Engineering & Architecture - [Backtesting Simulations](https://awesome-repositories.com/f/software-engineering-architecture/event-driven-architectures/backtesting-simulations.md) — Provides an event-driven backtesting simulation that validates trading strategies against historical market data. ### Testing & Quality Assurance - [Trading Strategy Engines](https://awesome-repositories.com/f/testing-quality-assurance/testing-infrastructure-management/multi-engine-execution/trading-strategy-engines.md) — Implements a modular strategy engine that separates trading logic from execution for flexible composition. ### Development Tools & Productivity - [Broker Deployment Automations](https://awesome-repositories.com/f/development-tools-productivity/deployment-automation/broker-deployment-automations.md) — Runs custom trading strategies on an online brokerage platform for automated live trading. ([source](https://cdn.jsdelivr.net/gh/charliedream1/ai_quant_trade@master/README.md)) ### User Interface & Experience - [Interactive Dashboards](https://awesome-repositories.com/f/user-interface-experience/interactive-dashboards.md) — Lets users compose custom monitoring panels with charts, metrics, and alerts for trading performance.