阿布量化交易系统(股票,期权,期货,比特币,机器学习) 基于python的开源量化交易,量化投资架构
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Sep 22, 2019 - Python
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阿布量化交易系统(股票,期权,期货,比特币,机器学习) 基于python的开源量化交易,量化投资架构
A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)
A list of online resources for quantitative modeling, trading, portfolio management
Python quantitative trading strategies including Pattern Recognition, CTA, Monte Carlo, Options Straddle, London Breakout, Heikin-Ashi, Pair Trading, RSI, Bollinger Bands, Parabolic SAR, Dual Thrust, Awesome, MACD
modular quant framework.
Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.
Portfolio analytics for quants, written in Python
Different Types of Stock Analysis in Python, R, Matlab, Excel, Power BI
List of awesome resources for machine learning-based algorithmic trading
Educational notebooks on quantitative finance, algorithmic trading, financial modelling and investment strategy
A stock backtesting engine written in modern Java. And a pairs trading (cointegration) strategy implementation using a bayesian kalman filter model
Developing Options Trading Strategies using Technical Indicators and Quantitative Methods
A curated list of awesome algorithmic trading frameworks, libraries, software and resources
Applying Machine Learning and AI Algorithms applied to Trading for better performance and low Std.
playing idealized trading games with deep reinforcement learning
Python version of Quantiacs toolbox and sample trading strategies
Powerful financial charting library based on R's Quantmod | http://py-quantmod.readthedocs.io/en/latest/
Коннектор к торговому терминалу ARQA QUIK (Квик), который делает доступным весь функционал QLUA из .NET (C#)
Quantitative Interview Preparation Guide, updated version here ==>
Java/MySQL live algorithmic trading using Interactive Brokers API
Algorithmic trading strategies
An API for backtesting trading strategies in JavaScript and TypeScript.
Quantitative systematic trading strategy development and backtesting in Julia
Multi-asset, multi-strategy, event-driven trade execution and management platform (OEMS) for automated buy-side trading of common markets, using MongoDB for storage and Telegram for notifications.
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