Github.com/CryptoSignal - Trading & Technical Analysis Bot - 4,100+ stars, 1,100+ forks cryptobitcointradingcoinbaseethereumtrading-bottrading-strategiestechnical-analysisgdaxalgorithmic-tradingcoinbase-apibittrex-apibinancebinance-apicrypto-signalmamocryptotradingcoinbase-proabenezer-mamocryptosignal ...
We are happy to share this toolkit with the trading community and hope that people will like and contribute to it. As is the case with everything in trading, these strategies are not perfect but they are based on rigorous theory and some great empirical results. Please take care when tradin...
aat is an asynchronous, event-driven framework for writing algorithmic trading strategies in python with optional acceleration in C++. It is designed to be modular and extensible, with support for a wide variety of instruments and strategies, live trading across (and between) multiple exchanges, ful...
\bulletMaxima/Minima - Certain trading strategies make use of extreme values in any time period, such as incorporating the high or low prices in OHLC data. However, since these maximal/minimal values can only be calculated at the end of a time period, a look-ahead bias is introduced if th...
Zipline is a Pythonic algorithmic trading library. It is an event-driven system for backtesting. Zipline is currently used in production as the backtesting and live-trading engine poweringQuantopian-- a free, community-centered, hosted platform for building and executing trading strategies. ...
🔬 A curated list of awesome machine learning strategies & tools in financial market. FinRLPublicForked fromAI4Finance-Foundation/FinRL A Deep Reinforcement Learning Library for Automated Trading in Quantitative Finance. NeurIPS 2020. 🔥 jessePublicForked fromjesse-ai/jesse ...
It is an event-driven system that supports both backtesting and live-trading. Zipline is currently used in production as the backtesting and live-trading engine powering Quantopian -- a free, community-centered, hosted platform for building and executing trading strategies. Join our community!
If you have any questions or need help with setting up or running the strategies or using the Strategy Designer features, please open an issue in the GitHub repository. The community and maintainers are here to help! Thank you for visiting the StockSharp Algorithmic Trading and Strategy Designer...
Part 1: How to Design a Trading Strategy The first part provides a framework for the development of trading strategies driven by machine learning (ML). It focuses on the data that power the ML algorithms and strategies discussed in this book, outlines how ML can be used to derive trading ...
With PyBroker, you'll have all the tools you need to create winning trading strategies backed by data and machine learning. Start using PyBroker today and take your trading to the next level! Installation PyBroker supports Python 3.9+ on Windows, Mac, and Linux. You can install PyBroker us...