Code for Machine Learning for Algorithmic Trading, 2nd edition.

Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations

Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.

List of awesome resources for machine learning-based algorithmic trading

Hands-On Machine Learning for Algorithmic Trading, published by Packt

Machine Learning for Algorithmic Trading, Second Edition - published by Packt

Python Fast Dataflow programming framework for Data pipeline work( Web Crawler,Machine Learning,Quantitative Trading.etc)

Stock Indicators for .NET is a C# NuGet package that transforms raw equity, commodity, forex, or cryptocurrency financial market price quotes into technical indicators and trading insights. You'll need this essential data in the investment tools that you're building for algorithmic trading, technical analysis, machine learning, or visual charting.

High frequency trading (HFT) framework built for futures using machine learning and deep learning techniques

MBATS is a docker based platform for developing, testing and deploying Algorthmic Trading strategies with a focus on Machine Learning based algorithms.

A tutorial for algorithmic trading bot using machine learning.

Applying Machine Learning and AI Algorithms applied to Trading for better performance and low Std.

No description available

High(ish) frequency trading bot for cryptocurrencies, using Machine Learning for future price predictions

PyTorch implementation for Paper "StockFormer: Learning Hybrid Trading Machines with Predictive Coding".

A curated list of awesome resources for quantitative investment and trading strategies focusing on artificial intelligence and machine learning applications in finance.

A comprehensive learning roadmap for mastering the core disciplines necessary for successful sole algorithmic trading. This repository serves as a structured template, guiding users through essential topics in software engineering, data science, machine learning, and finance. It combines certifications, curated resources, and hands-on projects.

Advanced SuperTrend trading bot for MetaTrader 5 with Machine Learning clustering🔥

A trading agent AI is an artificial intelligence system that uses computational intelligence methods such as machine learning and deep reinforcement learning to automatically discover, implement, and fine-tune strategies for autonomous adaptive automated trading in financial markets

Boilerplate/Starter code for trading on binance using Machine Learning. Provides a basic pipeline for data gathering, feature creation, training, testing and deployment of ML augmented bots.

Machine learning Options Trading Algorithm. API calls to collect the data from Yahoo Finance, Sentiment Investor, Finta. Encoding financial indicators. Building Logistic regression and Multinomial Machine Lerning models for evaluation. P2.

AI-CryptoTrader is a state-of-the-art cryptocurrency trading bot that uses ensemble methods to make trading decisions based on multiple sophisticated algorithms. Built with the latest machine learning and data science techniques, AI-CryptoTrader provides a powerful toolset and advanced trading stratgies for maximizing your cryptocurrency profits.

Scrape, analyze & visualize stock market data for the S&P500 using Python. Build a basic trading strategy using machine learning to assess company performance and determine buy, sell, hold. Read me & instructions available in Spanish. This is a working repo, with plans to expand the project from technical analysis to fundamental analysis.

Binary Trading AI Bot is a project idea aimed at developing an AI-powered bot for binary trading. The bot utilizes machine learning algorithms to predict the direction of the next candle (whether it will move up or down) with high accuracy.

This is a Python 3 project for analyzing stock prices and methods of stock trading. It uses native Python tools and Google TensorFlow machine learning.

Assignments as part of CS 7646 at GeorgiaTech under Dr. Tucker Balch in Fall 2017

Udacity - Machine Learning for Trading

Awesome machine learning for trading

MBATS is a docker based platform for developing, testing and deploying Algorthmic Trading strategies with a focus on Machine Learning based algorithms. This repository is an advanced version of the MBATS infrastructure without any of the business logic. Compared to MBATs, here are the changes that are made in this version.

Machine-learning based high frequency trading algorithm for altcoin cryptocurrencies [moved to closed source]