algobroker

Trading system

An algorithmic trading execution engine

Algo execution engine

GitHub

89 stars
7 watching
24 forks
Language: Python
last commit: over 8 years ago
Linked from 1 awesome list


Backlinks from these awesome lists:

Related projects:

Repository Description Stars
kieran-mackle/autotrader A platform for developing and deploying automated trading systems using Python 994
letianzj/quanttrader A Python-based backtesting and live trading package for quantitative traders. 531
alpacahq/pylivetrader A Python framework for live trading with broker API interface 664
sreenivasdoosa/sdoosa-algo-trade-python A Python-based framework for building algorithmic trading strategies on the Indian stock market 531
tradingstrategy-ai/getting-started A repository providing examples and tools for developing and backtesting algorithmic trading strategies in Python. 59
chicago-joe/cryptocurrency-multi-exchange-arbitrage-strategy Automated trading strategy that exploits price differences across multiple cryptocurrency exchanges using Python and the CCXT library. 45
edtechre/pybroker A Python framework for developing algorithmic trading strategies using machine learning and data science techniques. 2,062
alpacahq/pipeline-live Provides an extension for live trading pipelines using online API data sources. 205
amor71/liualgotrader A framework for developing and deploying algorithmic trading strategies using machine learning and multiple data feeds. 784
snjyor/binance-quant Automated trading system for executing quantified trades on the Binance exchange 13
fremantle-industries/tai A toolkit for building real-time trading systems 466
yubing744/trading-gpt Automates trading decisions using natural language processing and machine learning algorithms 32
51bitquant/51bitquant A full-stack project for building cryptocurrency trading bots using Python and CCXT framework 848
ajhpark/ib_nope Automated trading system for NOPE strategy over IBKR TWS 30
edouardpoitras/nowtrade A Python library for creating and backtesting algorithmic trading strategies using machine learning and technical indicators. 104