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StockSharp - Algorithmic trading and quantitative trading open source platform to develop trading robots (stock markets, forex, bitcoins and options)
StockSharp (shortly S#) – are free set of programs for trading at any markets of the world (American, European, Asian, Russian, stocks, futures, options, Bitcoins, forex, etc.). You will be able to trade manually or automated trading (algorithmic trading robots, conventional or HFT).Available connections: FIX/FAST, LMAX, Rithmic, Fusion/Blackwood, Interactive Brokers, OpenECry, Sterling, IQFeed, ITCH, FXCM, QuantHouse, E*Trade, BTCE, BitStamp and many other. Any broker or partner broker (benefits).
stocksharp hft trading-strategies trading-robots trading-platform algorithmic-trading-engine forex bitcoins c-sharp broker markets nasdaq quantitative-finance trading fixprotocol finance hft-trading iqfeed interactive-brokers fxcm bitcointribeca - A high frequency, market making cryptocurrency trading platform in node.js
tribeca is a very low latency cryptocurrency market making trading bot with a full featured web client, backtester, and supports direct connectivity to several cryptocoin exchanges. On modern hardware, it can react to market data by placing and canceling orders in under a millisecond. Runs on the latest node.js (v7.8 or greater). Persistence is acheived using mongodb. Installation is recommended via Docker, but manual installation is also supported.
trading trading-bot market-maker bitcoin cryptocurrency exchange docker trade hft-trading hftalgotrading - Algorithmic trading framework for cryptocurrencies.
Algotrading Framework is a repository with tools to build and run working trading bots, backtest strategies, assist on trading, define simple stop losses and trailing stop losses, etc. This framework work with data directly from Crypto exchanges API, from a DB or CSV files. Can be used for data-driven and event-driven systems. Made exclusively for crypto markets for now and written in Python.
bot framework crypto trading realtime trading-bot trading-api cryptocurrency algotrading trading-algorithms cryptocurrencies hft hft-trading algorithmic-trading trading-simulator backtesting-trading-strategies backtest high-frequency-trading cryptocurrency-exchanges crypto-algotradingcrypto-algotrading - Algorithmic trading framework for cryptocurrencies.
Crypto AlgoTrading Framework is a repository with tools to build and run working trading bots, backtest strategies, assist on trading, define simple stop losses and trailing stop losses, etc. This framework work with data directly from Crypto exchanges API, from a DB or csv files. Can be used for data-driven and event-driven systems. Made exclusively for crypto markets for now and written in Python. In realtime, Trading Bot operates in real time, with live data from exchanges APIs. It doesn't need pre stored data or DB to work. In this mode, bot can trade real money, simulate or alert user when is time to buy or sell, based on entry and exit strategies defined by user. Can also simulate user's strategies and present the results in real time.
crypto cryptocurrency cryptocurrencies cryptocurrency-exchanges algorithmic-trading algotrading framework hft hft-trading bot backtest backtesting-trading-strategies backtesting-frameworks realtime trading trading-bot trading-algorithms trading-simulator trading-apicrypto-database - Database for crypto data, supporting several exchanges
Database to store all data from crypto exchanges, currently working with Binance, Bittrex, Cryptopia and Poloniex. Can be used for technical analysis, bots, backtest, realtime trading, etc.
technical-analysis fundamental-analysis database crypto cryptocurrency-exchanges cryptocoins bittrex bitcoin binance cryptopia poloniex ripple ethereum trading trading-bot hft hft-trading high-frequency-tradingexample-hftish - Example Order Book Imbalance Algorithm
The aim of this algorithm is to capture slight moves in the bid/ask spread as they happen. It is only intended to work for high-volume stocks where there are frequent moves of 1 cent exactly. It is one of the trading strategies based on order book imbalance. For more details about it, please refer to Darryl Shen, 2015 or other online articles. This algorithm will make many trades on the same security each day, so any account running it will quickly encounter PDT rules. Please make sure your account balance is well above $25,000 before running this script in a live environment.
finance trading trading-algorithms alpaca nats-streaming python3 numpy orderbook real-time hft-trading hft async asyncioneural-finance - Neural Network for HFT-trading [experimental]
Neural Network for High Frequency Trading. Right now there is no doc. If you found something useful for you - star this repo. I really appreciate it.
deep-learning finance hft-trading data-analysis recurrent-neural-networks neural-network finance-notes trading machine-learningLightMatchingEngine - A very light matching engine in Python.
A light matching engine written in Python. The objective is to provide a easy interface for users on the standard price-time priority matching algorithm among different instruments.
trading order hft-trading matching-engine orderbook
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