649 Open source projects that are alternatives of or similar to Moonshot

A list of online resources for quantitative modeling, trading, portfolio management

A Python-based development platform for automated trading systems - from backtesting to optimisation to livetrading.

The Open-Source Backtesting Engine/ Market Simulator by Bertram Solutions.

Codera Quant is a Java framework for algorithmic trading strategies development, execution and backtesting via Interactive Brokers TWS API or other brokers API

modular quant framework.

Python-based framework for backtesting trading strategies & analyzing financial markets [GUI ]

Python quantitative trading strategies including VIX Calculator, Pattern Recognition, Commodity Trading Advisor, Monte Carlo, Options Straddle, Shooting Star, London Breakout, Heikin-Ashi, Pair Trading, RSI, Bollinger Bands, Parabolic SAR, Dual Thrust, Awesome, MACD

A multi-asset, multi-strategy, event-driven trade execution and management platform for running many algorithms/bots at many venues simultaneously with unified risk management and reporting. Uses MongoDB for storage and Telegram for user notifications/trade consent.

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Open Source algorithmic trading platform in Java / Python

Quantitative analysis, strategies and backtests

How to use the Roq C++20 API for Live Cryptocurrency Algorithmic and High-Frequency Trading as well as for Back-Testing and Historical Simulation

QTPyLib, Pythonic Algorithmic Trading

API for algorithmic and high-frequency trading

Stock indicator technical analysis library package for .NET. Send in historical price quotes and get back desired technical indicators. Nothing more. It can be used in any market analysis software using standard OHLCV price quotes for equities, commodities, forex, cryptocurrencies, and others. We had private trading algorithms, machine learning, and charting systems in mind when originally creating this community library. Current indicators include: Accumulation/Distribution Line (ADL), Aroon Oscillator, Arnaud Legoux Moving Average (ALMA), Average Directional Index (ADX), Average True Range (ATR), Awesome Oscillator (AO), Balance of Power (BOP), Beta Coefficient, Bollinger Bands®, Chaikin Money Flow (CMF), Chaikin Oscillator, Chandelier Exit, Choppiness Index (CHOP), Commodity Channel Index (CCI), ConnorsRSI, Correlation Coefficient, Donchian Channels, Double Exponential Moving Average (DEMA), Elder-ray Index, Exponential Moving Average (EMA), Force Index, Fractal Chaos Bands (FCB), Gator Oscillator, Heikin-Ashi, Hull Moving Average (HMA), Ichimoku Cloud, Kaufman's Adaptive Moving Average (KAMA), KDJ Index, Keltner Channels, Momentum Oscillator, Money Flow Index (MFI), MESA Adaptive Moving Averages (MAMA), Moving Average Convergence/Divergence (MACD), Moving Average Envelopes, On-balance Volume (OBV), Parabolic SAR (stop and reverse), Percentage Volume Oscillator (PVO), Pivot Points and Rolling Pivot Points, Price Channels, Price (Comparative) Relative Strength (PRS), Price Momentum Oscillator (PMO), Rate of Change (ROC), Relative Strength Index (RSI), R-Squared (Coefficient of Determination), Simple Moving Average (SMA), Slope and Linear Regression, Smoothed Moving Average (SMMA), Standard Deviation, Stoller Average Range Channel (STARC) Bands, Stochastic Oscillator, Stochastic RSI, SuperTrend, Tillson T3 Moving Average, Triple Exponential Moving Average (TEMA), Triple EMA Oscillator (TRIX), True Strength Index (TSI), Ulcer Index, Ultimate Oscillator, Volume Simple Moving Average, Volume Weighted Average Price (VWAP), Vortex Indicator (VI), Weighted Moving Average (WMA), Williams %R, Williams Alligator, Williams Fractal, and Zig Zag.

A cryptocurrency trading bot and framework supporting multiple exchanges written in Golang.

Here you can find all the quantitative finance algorithms that I've worked on and refined over the past year!

Framework for algorithmic trading

Cloud-native Financial Reinforcement Learning

An open source library for portfolio optimisation

super-monorepo for machine learning and algorithmic trading

I have been deeply interested in algorithmic trading and systematic trading algorithms. This Repository contains the code of what I have learnt on the way. It starts form some basic simple statistics and will lead up to complex machine learning algorithms.

Courses, Articles and many more which can help beginners or professionals.

A composable, real time, market data and trade execution toolkit. Built with Elixir, runs on the Erlang virtual machine

Backtest and live trading in Python

51bitquant Python数字货币量化交易视频 CCXT框架 爬取交易所数据 比特币量化交易 交易机器人51bitquant tradingbot cryptocurrency quantitative trading btc trading

Low-latency algorithmic trading platform written in Rust

Introducing neural networks to predict stock prices

Algorithmic trading strategies

Qlib is an AI-oriented quantitative investment platform, which aims to realize the potential, empower the research, and create the value of AI technologies in quantitative investment. With Qlib, you can easily try your ideas to create better Quant investment strategies. An increasing number of SOTA Quant research works/papers are released in Qlib.

Notebooks based on financial machine learning.

Financial portfolio optimisation in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity

🚀 Websocket based trading bot for 💰cryptocurrencies 📈

MlFinLab helps portfolio managers and traders who want to leverage the power of machine learning by providing reproducible, interpretable, and easy to use tools.

算法交易系统，支持CTP、XTP、模拟交易及行情网关、回测。不断迭代更新中。

Powerful financial charting library based on R's Quantmod | http://py-quantmod.readthedocs.io/en/latest/

Performance analysis of predictive (alpha) stock factors

Algorithmic trading infrastructure in Python.

Datasets, tools and more from Darwinex Labs - Prop Investing Arm & Quant Team @ Darwinex

Algorithmic trading using machine learning.

PortfolioLab is a python library that enables traders to take advantage of the latest portfolio optimisation algorithms used by professionals in the industry.

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 practical financial machine learning tools and applications.

Master repository for the pandas-ml modules

Use unsupervised and supervised learning to predict stocks

Some notebooks with powerful trading strategies.

A financial trading method using machine learning.

#nontina, #paperhands,, #pwnzebotz, #tradezbyguille

Educational notebooks on quantitative finance, algorithmic trading, financial modelling and investment strategy

convenient script for trading with python.

PandaPy has the speed of NumPy and the usability of Pandas 10x to 50x faster (by @firmai)

Using python and scikit-learn to make stock predictions

Automated Machine Learning [AutoML] with Python, scikit-learn, Keras, XGBoost, LightGBM, and CatBoost

Algorithmic trading and quantitative trading open source platform to develop trading robots (stock markets, forex, crypto, bitcoins, and options).

A master database of securities data for use with the Odin algorithmic trading platform.

Technical Indicators implemented in Python using Pandas

Performance tear sheets and backtest analysis for Moonshot

Common financial technical indicators implemented in Pandas.

A framework for systemic risk valuation and analysis.