trading - doubility-sky/daydayup GitHub Wiki

Trading is the buying and selling of securities, such as stocks, bonds, currencies and commodities, on financial markets with the objective of generating returns that outperform buy-and-hold investing. Trading strategies often utilize technical analysis, chart patterns, and various market indicators to make decisions.

Quantitative Trading is a trading strategy that relies on mathematical and statistical models to identify and execute opportunities. It utilizes quantitative analysis, algorithmic trading systems, and often high-frequency approaches to implement trading strategies.

Learn

Books

Academic

Technical Analysis

Trading Strategies

Risk Management

Automated Trading

Programming

Statistical Models

Communities

Tools

  • TradingView, a charting platform and social network used by 100M+ traders and investors worldwide to spot opportunities across global markets.
  • QuantConnect - 开源的算法交易平台
    • LEAN is an event-driven, professional-caliber algorithmic trading platform built with a passion for elegant engineering and deep quant concept modeling. Out-of-the-box alternative data and live-trading support.
  • Trading Technologies - 专业交易软件
  • MetaTrader - 流行的外汇和CFD交易平台
  • Interactive Brokers - 专业交易者的经纪平台
  • AI Hedge Fund - This is a proof of concept for an AI-powered hedge fund. The goal of this project is to explore the use of AI to make trading decisions. This project is for educational purposes only and is not intended for real trading or investment.

Libraries

  • Alpaca-py - Python股票交易API
  • TA-Lib - 技术分析库，多种编程语言支持
  • Zipline - Quantopian开源的Python算法交易库
  • QuantLib - 金融量化分析的C++库

Crypto Currency

  • CCXT – CryptoCurrency eXchange Trading Library
  • Freqtrade is a free and open source crypto trading bot written in Python. It is designed to support all major exchanges and be controlled via Telegram or webUI. It contains backtesting, plotting and money management tools as well as strategy optimization by machine learning.
  • Hummingbot is an open-source framework that helps you design and deploy automated trading strategies, or bots, that can run on many centralized or decentralized exchanges. Over the past year, Hummingbot users have generated over $34 billion in trading volume across 140+ unique trading venues.
  • Gekko - 比特币交易机器人

Frameworks

  • Qlib is an open-source, AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas to implementing productions. Qlib supports diverse machine learning modeling paradigms, including supervised learning, market dynamics modeling, and reinforcement learning.
  • Jesse is an advanced crypto trading framework that aims to simplify researching and defining YOUR OWN trading strategies for backtesting, optimizing, and live trading.
  • zvt - modular quant framework.
  • Qbot is an AI-oriented automated quantitative investment platform, which aims to realize the potential, empower AI technologies in quantitative investment. Qbot supports diverse machine learning modeling paradigms. including supervised learning, market dynamics modeling, and RL.
  • Basana is a Python async and event driven framework for algorithmic trading, with a focus on crypto currencies.

Backtesting

  • Backtesting.py - Backtest trading strategies with Python.
  • backtrader - Python Backtesting library for trading strategies
  • bt - Flexible Backtesting for Python
  • finmarketpy is a Python based library that enables you to analyze market data and also to backtest trading strategies using a simple to use API, which has prebuilt templates for you to define backtest.

FAQs

Resources

Open Data