222 Open source projects that are alternatives of or similar to Optimalportfolio

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

QTPyLib, Pythonic Algorithmic Trading

Vectorized backtester and trading engine for QuantRocket

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

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

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

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

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

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

A financial trading method using machine learning.

A curated list of practical financial machine learning tools and applications.

Performance tear sheets and backtest analysis for Moonshot

Notebooks based on financial machine learning.

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

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.

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

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

Some notebooks with powerful trading strategies.

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

modular quant framework.

Quantitative analysis, strategies and backtests

super-monorepo for machine learning and algorithmic trading

Cloud-native Financial Reinforcement Learning

Introducing neural networks to predict stock prices

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.

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

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

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

Using python and scikit-learn to make stock predictions

Use unsupervised and supervised learning to predict stocks

Predicting price trends in cryptomarkets using an lstm-RNN for the use of a trading bot

Slide show presentations regarding data driven investing.

A grid trading strategy and trading-bot for Binance Exchange. 币安交易所的网格交易

API for algorithmic and high-frequency trading

PyTrendFollow - systematic futures trading using trend following

A web application to explore currently hyped stocks on Reddit

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

💹 openAlgo is a public repository for various work product relavant to algorithms and the high frequency low latency electronic trading space with a bias toward market microstructure as well as exchange traded futures and options.

(no longer maintained) A simple yet robust (stock+options) API client for Robinhood

Algorithmic trading strategies

This repository contains three ways to obtain arbitrage which are Dual Listing, Options and Statistical Arbitrage. These are projects in collaboration with Optiver and have been peer-reviewed by staff members of Optiver.

Unofficial Documentation of Robinhood Trade's Private API

Source code for my personal blog

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.

GPU-accelerated Factors analysis library and Backtester

hummingbot中文资源

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

event-driven backtesting framework written in golang

Deep learning for forecasting company fundamental data

Wrapper library for algorithmic trading in Python 3, providing DMA/STP access to Darwinex liquidity via a ZeroMQ-enabled MetaTrader Bridge EA.

Zipline, a Pythonic Algorithmic Trading Library

Quantitative Interview Preparation Guide, updated version here ==>

Statistical and Algorithmic Investing Strategies for Everyone

🐗 🐻 Deep Learning based Python Library for Stock Market Prediction and Modelling

Asynchronous, event-driven algorithmic trading in Python and C++

An Algorithmic Trading Library for Crypto-Assets in Python

🚀 Websocket based trading bot for 💰cryptocurrencies 📈

Quantitative systematic trading strategy development and backtesting in Julia

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。