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https://github.com/elitequant/elitequant

A list of online resources for quantitative modeling, trading, portfolio management
https://github.com/elitequant/elitequant
algorithmic-trading asset-management asset-pricing machine-learning mathematical-finance portfolio-management quantitative-finance quantitative-trading trading-platform trading-systems
Last synced: 30 days ago
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A list of online resources for quantitative modeling, trading, portfolio management
Host: GitHub
URL: https://github.com/elitequant/elitequant
Owner: EliteQuant
License: apache-2.0
Created: 2017-11-21T05:28:40.000Z (almost 7 years ago)
Default Branch: master
Last Pushed: 2024-06-15T16:17:39.000Z (5 months ago)
Last Synced: 2024-10-14T11:02:39.771Z (30 days ago)
Topics: algorithmic-trading, asset-management, asset-pricing, machine-learning, mathematical-finance, portfolio-management, quantitative-finance, quantitative-trading, trading-platform, trading-systems
Homepage:
Size: 1.2 MB
Stars: 2,930
Watchers: 168
Forks: 571
Open Issues: 10
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project

README

        # EliteQuant

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

There are lots of other valuable online resources. We are not trying to be exhaustive. Please feel free to send a pull request if you believe something is worth recommending. A general rule of thumb for open source projects is having already received 100 stars on github.

* [Quantitative Trading Platform](#quantitative-trading-platform)

* [Trading System](#trading-system)

* [Quantitative Library](#quantitative-library)

* [Quantitative Model](#quantitative-model)

* [Trading API](#trading-api)

* [Data Source](#data-source)

* [Cryptocurrency](#cryptocurrency)

* [Companies](#companies)

* [Fintech](#fintech)

* [Websites Forums Blogs](#websites-forums-blogs)

- - -

## Quantitative Trading Platform

* [awesome-quant](https://github.com/wilsonfreitas/awesome-quant) - Awesome quant is another curated list of quant resources

* [Quantopian](https://www.quantopian.com/) - First Python-based online quantitative trading platform; its core library [zipline](https://github.com/quantopian/zipline) and its performance evaluation library [pyfolio](https://github.com/quantopian/pyfolio); and [alphalens](https://github.com/quantopian/alphalens)

* [QuantConnect](https://www.quantconnect.com/) - C# based online quantitative trading platform; its core library [Lean](https://github.com/QuantConnect/Lean)

* [Quantiacs](https://www.quantiacs.com/) - The Marketplace For Algorithmic Trading Strategies; its [Matlab and Python toolbox](https://github.com/Quantiacs)

* [Numerai](https://numer.ai/) - crowd-sourced trading strategies; its [Python API](https://github.com/uuazed/numerapi/)

* [Collective2](https://trade.collective2.com/) - The platform that allows investors subscribe to top-traders; its [algotrades system](https://www.algotrades.net/)

* [ZuluTrade](https://zulutrade.com) - The platform that allows investors subscribe to top-traders

* [Tradingview](https://www.tradingview.com/chart/) - It provides free widgets used for example [Huobi](https://www.hbg.com/zh-cn/exchange/?s=eos_usdt)

* [Investing.com](https://www.investing.com/indices/us-spx-500-futures-commentary) - Real time multi-assets and markets

* [KloudTrader Narwhal](https://kloudtrader.com/Narwhal) - Trading algorithm [deployment platform](https://www.youtube.com/watch?v=4hfSJ769bDk) with flat-rate commission-free brokerage 

## Trading System

* [MetaTrader 5](https://www.metatrader5.com/) - Multi-Asset trading system

* [TradeStation](https://www.tradestation.com/) - Trading system

* [SmartQuant(OpenQuant)](http://www.smartquant.com/) - C# Trading system

* [RightEdge](https://www.rightedgesystems.com/) - Trading system

* [AmiBroker](https://www.amibroker.com/) - Trading system

* [Algo Terminal](https://www.algoterminal.com/) - C# Trading system

* [NinjaTrader](https://ninjatrader.com/) - Trading system

* [QuantTools](https://quanttools.bitbucket.io/) - Enhanced Quantitative Trading Modelling in R

* [vnpy](https://github.com/vnpy/vnpy) - A popular and powerful trading platform

* [pyalgotrade](https://github.com/gbeced/pyalgotrade) - Python Algorithmic Trading Library

* [finmarketpy](https://github.com/cuemacro/finmarketpy) - Python library for backtesting trading strategies

* [IBridgePy](http://www.ibridgepy.com/) - A Python system derived from zipline

* [Backtrader](https://www.backtrader.com/) - Blog, trading community, and [github](https://github.com/backtrader/backtrader)

* [IbPy](https://github.com/blampe/IbPy) - Interactive Brokers Python API

* [PyLimitBook](https://github.com/danielktaylor/PyLimitBook) - Python implementation of fast limit-order book

* [qtpylib](https://github.com/ranaroussi/qtpylib) - Pythonic Algorithmic Trading via IbPy API and its [Website](https://qtpylib.io/)

* [Quantdom](https://github.com/constverum/Quantdom) - Python-based framework for backtesting trading strategies & analyzing financial markets [GUI]

* [ib_insync](https://github.com/erdewit/ib_insync) - Python sync/async framework for Interactive Brokers API

* [rqalpha](https://github.com/ricequant/rqalpha) - A popular trading platform

* [bt](https://github.com/pmorissette/bt) - flexible backtesting for Python

* [TradingGym](https://github.com/Yvictor/TradingGym) - Trading and Backtesting environment for training reinforcement learning agent or simple rule base algo.

* [btgym](https://github.com/Kismuz/btgym) - Gym-compatible backtesting

* [prophet](https://github.com/Emsu/prophet) - Python backtesting and trading platform

* [OpenHFT](https://github.com/OpenHFT) - Java components for high-frequency trading

* [libtrading](https://github.com/libtrading/libtrading) - C API, low latency, fix support

* [thOth](https://github.com/vermosen/thOth) - open-source high frequency trading library in C++ 11

* [qt_tradingclient](https://github.com/spinlockirqsave/qt_tradingclient_1) - multithreaded Qt C++ trading application, QuantLib-1.2.1, CUDA 5.0

* [SubMicroTrading](https://github.com/gsitgithub/SubMicroTrading) - Java Ultra Low Latency Trading Framework

* [WPF/MVVM Real-Time Trading Application](https://www.codeproject.com/Articles/326641/WPF-MVVM-Real-Time-Trading-Application) - Architechture

* [TradeLink](https://github.com/pracplayopen/core)  - TradeLink, one of the earliest open source trading system

* [Reactive Trader](https://github.com/AdaptiveConsulting) - using reactive Rx framework, includes [Reactive Trader](https://github.com/AdaptiveConsulting/ReactiveTrader) and [Reactive Trader Cloud](https://github.com/AdaptiveConsulting/ReactiveTraderCloud). The demo is [here](https://web-demo.adaptivecluster.com/).

* [QuantTrading](https://github.com/letianzj/QuantTrading) - Pure C# trading system

* [StockTrading](https://github.com/houmie/StockTrading) - C# system utilising WPF, WCF, PRISM, MVVM, Threading

* [Quanter](https://github.com/superquanter/quanter) - StockTrader

* [StockSharp](https://github.com/StockSharp/StockSharp) - C# trading system

* [SharpQuant](https://github.com/smartquant/SharpQuant.QuantStudio) - C# trading system

* [QuantSys](https://github.com/exl3/QuantSys) - C# trading system

* [StockTicker](https://github.com/danielmarbach/StockTicker) - C# trading system

* [gotrade](https://github.com/cyanly/gotrade) - Electronic trading and order management system written in Golang

* [gofinance](https://github.com/aktau/gofinance) - Financial information retrieval and munging in golang

* [goib](https://github.com/gofinance/ib) - Pure Go interface to Interactive Brokers IB API 

* [Matlab Trading Toolbox](https://www.mathworks.com/products/trading.html) - Official toolbox from Matlab; acommpanying [Introduction to Matlab Trading Toolbox](https://www.mathworks.com/matlabcentral/fileexchange/52588-automated-trading-system-development-with-matlab?focused=5253184&tab=example), and [webinar Automated Trading System Development with MATLAB](https://www.mathworks.com/videos/automated-trading-system-development-with-matlab-106851.html), and [webinar Automated Trading with MATLAB](https://www.mathworks.com/videos/automated-trading-with-matlab-81911.html), as well as [webinar A Real-Time Trading System in MATLAB](https://www.mathworks.com/videos/a-real-time-trading-system-in-matlab-92900.html), [Automated Trading with Matlab](https://www.mathworks.com/videos/automated-trading-with-matlab-81911.html), [Commodities Trading with Matlab](https://www.mathworks.com/videos/commodities-trading-with-matlab-81986.html), [Cointegration and Pairs Trading with Econometrics Toolbox](https://www.mathworks.com/videos/cointegration-and-pairs-trading-with-econometrics-toolbox-81799.html)

* [Matlab risk management Toolbox](https://www.mathworks.com/products/risk-management.html) - Official toolbox from Matlab

* [Matlab Walk Forward Analysis Toolbox](https://wfatoolbox.com/) - toolbox for walk-forward analysis

* [IB4m](https://github.com/softwarespartan/IB4m) - matlab interface to interactive broker

* [IB-Matlab](https://undocumentedmatlab.com/ib-matlab/) - introduction to another matlab interface to interactive broker and [demo video](https://undocumentedmatlab.com/ib-matlab/real-time-trading-system-demo)

* [openAlgo Matlab](https://github.com/mtompkins/openAlgo/tree/master/Matlab) - openAlgo's Matlab library

* [MatTest](https://github.com/edisonhyc/MatTest) - Matlab backtest system

## Quantitative Library

* [Quantlib](https://www.quantlib.org/) - famous C++ library for quantitative finance; tranlated into other langugages via Swig

* [TA-Lib](https://github.com/mrjbq7/ta-lib) - Python wrapper for TA-Lib

* [DX Analytics](https://dx-analytics.com/) - Python-based financial analytics library

* [FinMath](http://finmath.net/) - Java analytics library

* [OpenGamma](https://opengamma.com/) - Java analytics library named STRATA

* [Quantiacs](https://github.com/Quantiacs) - [Matlab](https://github.com/Quantiacs/quantiacs-matlab) toolbox

* [pyflux](https://github.com/RJT1990/pyflux) - Open source time series library for Python

* [arch](https://github.com/bashtage/arch) - ARCH models in Python

* [flint](https://github.com/twosigma/flint) - A Time Series Library for Apache Spark

* [Statsmodels](https://www.statsmodels.org) - Statsmodels’s Documentation

## Quantitative Model

* [awesome-deep-trading](https://github.com/cbailes/awesome-deep-trading) - A list of machine learning resources for trading

* [Awesome-Quant-Machine-Learning-Trading](https://github.com/grananqvist/Awesome-Quant-Machine-Learning-Trading) - Another list of machine learning resources for trading

* [awesome-ai-in-finance](https://github.com/georgezouq/awesome-ai-in-finance) - A collection of AI resources in finance

* [deepstock](https://github.com/keon/deepstock) - Technical experimentations to beat the stock market using deep learning

* [qtrader](https://github.com/filangel/qtrader) - Reinforcement Learning for Portfolio Management

* [stockPredictor](https://github.com/Nazanin1369/stockPredictor) - Predict stock movement with Machine Learning and Deep Learning algorithms

* [stock_market_reinforcement_learning](https://github.com/kh-kim/stock_market_reinforcement_learning) - Stock market environment using OpenGym with Deep Q-learning and Policy Gradient

* [deep-algotrading](https://github.com/LiamConnell/deep-algotrading) - deep learning techniques from regression to LSTM using financial data

* [deep_trader](https://github.com/deependersingla/deep_trader) - Use reinforcement learning on stock market and agent tries to learn trading. 

* [Deep-Trading](https://github.com/Rachnog/Deep-Trading) - Algorithmic trading with deep learning experiments

* [Deep-Trading](https://github.com/ha2emnomer/Deep-Trading) - Algorithmic Trading using RNN

* [100 Day Machine Learning](https://github.com/Avik-Jain/100-Days-Of-ML-Code) - Machine Learning tutorial with code

* [Multidimensional-LSTM-BitCoin-Time-Series](https://github.com/jaungiers/Multidimensional-LSTM-BitCoin-Time-Series) - Using multidimensional LSTM neural networks to create a forecast for Bitcoin price

* [QLearning_Trading](https://github.com/ucaiado/QLearning_Trading) - Learning to trade under the reinforcement learning framework

* [bulbea](https://github.com/achillesrasquinha/bulbea) - Deep Learning based Python Library for Stock Market Prediction and Modelling 

* [PGPortfolio](https://github.com/ZhengyaoJiang/PGPortfolio) - source code of "A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem"

* [gym-trading](https://github.com/hackthemarket/gym-trading) - Environment for reinforcement-learning algorithmic trading models

* [Thesis](https://github.com/pnecchi/Thesis) - Reinforcement Learning for Automated Trading

* [DQN](https://github.com/jjakimoto/DQN) - Reinforcement Learning for finance

* [Deep-Trading-Agent](https://github.com/samre12/deep-trading-agent) - Deep Reinforcement Learning based Trading Agent for Bitcoin

* [deep_portfolio](https://github.com/deependersingla/deep_portfolio) - Use Reinforcement Learning and Supervised learning to Optimize portfolio allocation.

* [Deep-Reinforcement-Learning-in-Stock-Trading](https://github.com/shenyichen105/Deep-Reinforcement-Learning-in-Stock-Trading) - Using deep actor-critic model to learn best strategies in pair trading

* [Stock-Price-Prediction-LSTM](https://github.com/NourozR/Stock-Price-Prediction-LSTM) - OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network

* [DeepDow](https://github.com/jankrepl/deepdow) - Portfolio optimization with deep learning

* [Personae](https://github.com/Ceruleanacg/Personae) - Quantitative trading with deep learning

* [tensortrade](https://github.com/tensortrade-org/tensortrade) - Reinforcement learning and trading

* [stockpredictionai](https://github.com/borisbanushev/stockpredictionai) - AI models such as GAN and PPO applied to stock markets

* [machine-learning-for-trading](https://github.com/stefan-jansen/machine-learning-for-trading) - Machine learning for algorithmic trading book

* [algorithmic-trading-with-python](https://github.com/chrisconlan/algorithmic-trading-with-python) - Algorithmic Trading with Python book (2020)

* [machine-learning-asset-management](https://github.com/firmai/machine-learning-asset-management) - Machine Learning in Asset Management by [firmai.org](https://www.firmai.org/)

## Trading API

* [Interactive Brokers](https://www.interactivebrokers.com) - popular among retail trader

* [Bloomberg API](https://www.bloomberg.com/professional/support/api-library/) - from Bloomberg

## Data Source

* [Quandl](https://www.quandl.com/) - free and premium data sources

* [iex](https://iextrading.com/trading/market-data/) - free market data

* [one tick](https://www.onetick.com/) - historical tick data

* [iqfeed](https://www.iqfeed.net/) - real time data feed

* [quantquote](https://quantquote.com/) - tick and live data

* [algoseek](https://www.algoseek.com/) - historical intraday

* [EOD data](https://eoddata.com/) - historical data

* [EOD historical data](https://eodhistoricaldata.com/) - historical data

* [intrinio](https://intrinio.com/) - financial data

* [arctic](https://github.com/manahl/arctic) - High performance datastore from [Man AHL](https://www.ahl.com/) for time series and tick data 

* [SEC EDGAR API](https://sec-api.io/) -- Query company filings on SEC EDGAR

## Cryptocurrency

* [Blockchain-stuff](https://github.com/Xel/Blockchain-stuff) - Blockchain and Crytocurrency Resources

* [cryptrader](https://cryptotrader.org/) - Node.js Bitcoin bot for MtGox/Bitstamp/BTC-E/CEX.IO; [cryptrade](https://github.com/donfanning/cryptrade) 

* [BitcoinExchangeFH](https://github.com/BitcoinExchangeFH/BitcoinExchangeFH) - Cryptocurrency exchange market data feed handler 

* [hummingbot](http://hummingbot.io) - free [open source](https://github.com/CoinAlpha/hummingbot/) crypto trading bot that supports both DEXes and CEXes

* [blackbird](https://github.com/butor/blackbird) - C++ trading system that does automatic long/short arbitrage between Bitcoin exchanges

* [Peatio](https://www.peatio.tech) - An open-source crypto currency exchange on [github](https://github.com/peatio/peatio)

* [Qt Bitcoin Trader](https://github.com/JulyIGHOR/QtBitcoinTrader) - Qt C++ Bitcoin trading

* [ccxt](https://github.com/ccxt/ccxt) - A JavaScript / Python / PHP cryptocurrency trading library with support for more than 130 bitcoin/altcoin exchanges

* [r2](https://github.com/bitrinjani/r2) - Qan automatic arbitrage trading system powered by Node.js + TypeScript

* [bcoin](https://github.com/bcoin-org/bcoin) - Javascript bitcoin library for node.js and [browsers](https://bcoin.io/)

* [XChange](https://github.com/knowm/XChange) - Java library providing a streamlined API for interacting with 60+ Bitcoin and Altcoin exchanges

* [Krypto-trading-bot](https://github.com/ctubio/Krypto-trading-bot) - Self-hosted crypto trading bot (automated high frequency market making) in node.js, angular, typescript and c++

* [freqtrade](https://github.com/freqtrade/freqtrade) - Simple High Frequency Trading Bot for crypto currencies

* [Gekko](https://github.com/askmike/gekko) - A bitcoin trading bot written in node

* [viabtc_exchange_server](https://github.com/viabtc/viabtc_exchange_server) - A trading engine with high-speed performance and real-time notification

* [catalyst](https://github.com/enigmampc/catalyst) - An Algorithmic Trading Library for Crypto-Assets in Python [Enigma](https://enigma.co/)

* [buttercoin](https://github.com/buttercoin/buttercoin) - Opensource Bitcoin Exchange Software

* [zenbot](https://github.com/DeviaVir/zenbot) - A command-line cryptocurrency trading bot using Node.js and MongoDB.

* [tribeca](https://github.com/michaelgrosner/tribeca) - A high frequency, market making cryptocurrency trading platform in node.js

* [rbtc_arbitrage](https://github.com/hstove/rbtc_arbitrage) - A gem for automating arbitrage between Bitcoin exchanges.

* [automated-trading](https://github.com/bevry-trading/automated-trading) - Automated Trading: Trading View Strategies => Bitfinex, itBit, DriveWealth

* [gocryptotrader](https://github.com/thrasher-/gocryptotrader) - A cryptocurrency trading bot and framework supporting multiple exchanges written in Golang

* [btcrobot](https://github.com/philsong/btcrobot) - Golang bitcoin trading bot

* [bitex](https://github.com/blinktrade/bitex) - Open Source Bitcoin Exchange; and its [front-end](https://github.com/blinktrade/frontend)

* [cryptoworks](https://cryptoworks.co/) - A cryptocurrency arbitrage opportunity calculator. Over 800 currencies and 50 markets; [cryptocurrency-arbitrage](https://github.com/manu354/cryptocurrency-arbitrage)

* [crypto-exchange](https://github.com/passabilities/crypto-exchange) - list of crypto exchanges to interact with their API's in a uniform fashion

* [bitcoin-abe](https://github.com/bitcoin-abe/bitcoin-abe) - block browser for Bitcoin and similar currencies

* [MultiPoolMiner](https://github.com/MultiPoolMiner/MultiPoolMiner) - Monitors crypto mining pools in real-time in order to find the most profitable for your machine. Controls any miner that is available via command line

* [tai](https://github.com/fremantle-capital/tai) - An open source, composable, real time, market data and trade execution toolkit. Written in Elixir

* [crypto-signal](https://github.com/CryptoSignal/crypto-signal) - Technical signals for multiple exchanges

## Companies

Not trying to be exhaustive

* [Sell Side](https://en.wikipedia.org/wiki/List_of_investment_banks)

* [FIA PTG](http://www.marketswiki.com/wiki/Principal_Traders_Group) and [FIA Europe](https://www.fia.org/epta-membership)

* [Allston Trading](http://www.marketswiki.com/wiki/Allston_Trading,_LLC)

* [CTC](http://www.marketswiki.com/wiki/Chicago_Trading_Company)

* [Citadel](https://en.wikipedia.org/wiki/Citadel_LLC)

* [D.E. Shaw](https://en.wikipedia.org/wiki/D._E._Shaw_%26_Co.)

* [DRW](http://www.marketswiki.com/wiki/DRW)

* [Flow Traders](https://www.flowtraders.com/)

* [GTS](http://www.gtsx.com/)

* [HRT](https://en.wikipedia.org/wiki/Hudson_River_Trading)

* [IMC](https://en.wikipedia.org/wiki/IMC_Financial_Markets)

* [Infinium](http://www.marketswiki.com/wiki/Infinium_Capital_Management,_LLC)

* [Jane Street](https://en.wikipedia.org/wiki/Jane_Street_Capital)

* [Jump Trading](http://www.marketswiki.com/wiki/Jump_Trading_LLC)

* [Millennium](https://en.wikipedia.org/wiki/Millennium_Management,_LLC)

* [Optiver](https://en.wikipedia.org/wiki/Optiver)

* [Quantlab Financial](https://www.quantlab.com/)

* [Renaissance](https://en.wikipedia.org/wiki/Renaissance_Technologies)

* [Bridgewater Associates](https://en.wikipedia.org/wiki/Bridgewater_Associates)

* [Man Group](https://en.wikipedia.org/wiki/Man_Group), [AHL](https://www.ahl.com/)

* [SIG](https://en.wikipedia.org/wiki/Susquehanna_International_Group)

* [Tower Research](https://en.wikipedia.org/wiki/Tower_Research)

* [Tradebot Systems](https://en.wikipedia.org/wiki/Tradebot)

* [Two Sigma](https://en.wikipedia.org/wiki/Two_Sigma)

* [Virtu Financial](https://en.wikipedia.org/wiki/Virtu_Financial)

* [XR Trading](http://www.xrtrading.com/)

* [XTX Markets](https://en.wikipedia.org/wiki/XTX_Markets)

Commodity Focused

* [Cargill](https://en.wikipedia.org/wiki/Cargill)

* [Glencore](https://en.wikipedia.org/wiki/Glencore)

* [Mercuria](https://en.wikipedia.org/wiki/Mercuria_Energy_Group)

* [Trafigura](https://en.wikipedia.org/wiki/Trafigura)

* [Vigor](https://en.wikipedia.org/wiki/Vitol)

## Fintech

* [Alpaca](https://www.alpaca.ai/)

* [Knesho](https://www.kensho.com/)

* [Neotic](https://neotic.ai/)

* [Numerai](https://en.wikipedia.org/wiki/Numerai)

* [Symphony](https://en.wikipedia.org/wiki/Symphony_Communication)

## Websites Forums Blogs

* [Top Geeky Quant Blogs](https://alphaarchitect.com/2014/10/13/top-geeky-quant-blogs/#.VECOwfldV8E) - A quant blogs check out list

* [Quantocracy](https://quantocracy.com/) - Aggregation of news on quants

* [seekingalpha](https://seekingalpha.com/) - Seeking Alpha community

* [Quantivity](https://quantivity.wordpress.com/) - quantitative and algorithmic trading

* [Wilmott](https://www.wilmott.com/) - quantitative finance community forum

* [Elitetrader](https://www.elitetrader.com/) - trading forum

* [nuclearphynance](https://www.nuclearphynance.com/) - quantitative finance forum

* [Investopedia](https://www.investopedia.com/) - The Encyclopedia of investments

* [Quantpedia](https://www.quantpedia.com/) - The Encyclopedia of Quantitative Trading Strategies

* [EpChan](https://epchan.blogspot.com/) - Dr. Ernie Chan's blog

* [Quantinsti](https://quantra.quantinsti.com/) - Quant Institute

* [QuantStart](https://www.quantstart.com/) - Michael Halls-Moore's quantstart, quant trading 101; its Python backtest platform [qstrader](https://github.com/mhallsmoore/qstrader) and [qsforex](https://github.com/mhallsmoore/qsforex)

* [Algotrading 101](https://algotrading101.com/) - Algo trading 101

* [Systematic Investor](https://systematicinvestor.github.io/)/[old version](https://systematicinvestor.wordpress.com/) - [Michael Kapler](https://www.linkedin.com/in/michael-kapler-mmf-cfa-92a1a02/?ppe=1)'s blog, one of the best R quantitative blog; [Systematic Investor Toolkit](https://github.com/systematicinvestor/SIT)

* [R-Finance](https://github.com/R-Finance) - R-Finance repository. It has backtest [quantstrat](https://github.com/R-Finance/quantstrat), [trade blotter](https://github.com/R-Finance/blotter), famous [performance analytics](https://github.com/R-Finance/PerformanceAnalytics) package, and package [portfolio analytics](https://github.com/R-Finance/PortfolioAnalytics), [portfolio attribution](https://github.com/R-Finance/PortfolioAttribution).

* [quantmod](https://www.quantmod.com/) - R modelling and trading framework

* [r programming](http://www.r-programming.org/papers) - Guy Yollin's R backtesting

* [Seer Trading](http://www.seertrading.com/) - R Backtest and live trading

* [Trading with Python](https://tradingwithpython.blogspot.com/)

* [python programming finance](https://pythonprogramming.net/finance-tutorials/) - python finance tutorial and quantopian toturial

* [python for finance](https://www.pythonforfinance.net/) - python finance

* [Quant Econ](https://quantecon.org/) - open source python and julia codes for economic modeling; and lectures

* [JuliaQuant](https://github.com/JuliaQuant) - Quantitative Finance in Julia

* [Portfolio Effect](https://www.portfolioeffect.com/) - real time portfolio and risk management

* [quant365](http://www.quant365.com/) - Henry Moo's blog and trading system; including Sentosa, [pysentosa binding](https://github.com/henrywoo/pysentosa), rsentosa binding and [qblog](https://github.com/henrywoo/qblog).

* [hpc quantlib](https://hpcquantlib.wordpress.com/) - HPC + QuantLib

* [Quant Corner](https://quantcorner.wordpress.com/)

* [quantstrat trader](https://quantstrattrader.wordpress.com/) - Backtesting trading ideas with R [QuantStrat](https://github.com/R-Finance/quantstrat) package

* [Backtesting Strategies](https://timtrice.github.io/backtesting-strategies/) - Backtesting in R; codes at [Github](https://github.com/timtrice/backtesting-strategies)

* [The Quant MBA](https://thequantmba.wordpress.com/) - good quant blog

* [Foss Trading](http://blog.fosstrading.com/) - Algorithmic trading with free open source software

* [Gekko Quant](http://gekkoquant.com/) - Quantitative Trading

* [Investment Idiocy](https://qoppac.blogspot.com/) - Systematic Trading, Quantitative Finance, Investing, Financial Activism, Economic decision making by Robert Carver; [his book](https://www.amazon.com/Systematic-Trading-designing-trading-investing/dp/0857194453) and [his Python library](https://github.com/robcarver17/pysystemtrade)

* [Quantifiable Edges](https://quantifiableedges.com/blog/)/[old version](https://quantifiableedges.blogspot.com/) - Assessing market action with indicators and history

* [My Simple Quant](http://mysimplequant.blogspot.com/) - Market analysis utilizing historical, back-tessted data

* [Vix and more](https://vixandmore.blogspot.com/) - discussions on Vix

* [Timely Portfolio](https://timelyportfolio.blogspot.com/) - Strategies and tests in R

* [Quantitative Research and Trading](https://jonathankinlay.com/)

* [Qusma](https://qusma.com/) - Quantitative Systematic Market Analysis

* [return and risk](http://www.returnandrisk.com/) - Quantitative finance, analysis, and applications

* [Physics of Finance](https://physicsoffinance.blogspot.com/) - Inspiration from physics for thinking about economics, finance and social systems

* [Quantum Financier](https://quantumfinancier.wordpress.com/) - algorithmic trading

* [Trading the Odds](http://www.tradingtheodds.com/) -- market timing & quantitative analysis

* [CSSA](https://cssanalytics.wordpress.com/) - new concepts in quantitative research

* [The Practical Quant](https://practicalquant.blogspot.com/)

* [Tr8dr](https://tr8dr.github.io/) - strategies, statistics, computer science, numerical techniques

* [Deniz's Note](https://denizstij.blogspot.com/) - blog of a quant Deniz Turan

* [Quant at risk](http://www.quantatrisk.com/) - quantitative analysis and risk management

* [Quant Blog](https://letianzj.github.io/) - Quantitative trading, portfolio management, and machine learning, with [source codes on Github](https://github.com/letianzj/QuantResearch)

* [The R Trader](https://www.thertrader.com/) - Using R in quant finance

* [rbresearch](https://rbresearch.wordpress.com/) - Using R for trading strategy ideas in FX and equity markets

* [NaN Quantivity](https://quantlife.wordpress.com/) - quant trading, statistical learning, coding and brainstorming

* [Factor Investing](https://factorinvestingtutorial.wordpress.com/) - blog on wordpress

* [Meb Faber Research](https://mebfaber.com/)

* [Big Mike Trading](https://www.youtube.com/user/BigMikeTrading/videos) - Youtube chanel in quant trading

* [Mechanical Markets](https://mechanicalmarkets.wordpress.com/)

* [Humble Student of the Markets](https://humblestudentofthemarkets.blogspot.com/)

* [Predict Stock Prices Using RNN](https://lilianweng.github.io/lil-log/2017/07/08/predict-stock-prices-using-RNN-part-1.html)

* [BlackArbs](http://www.blackarbs.com/blog) - blog and [machine learning notebooks on Github](https://github.com/BlackArbsCEO/Adv_Fin_ML_Exercises)