algorithmic-trading-with-python

Overview

This repository contains Python source code for Chris Conlan’s 2020 book Algorithmic Trading with Python. It provides standalone research tools, including performance metrics, Pandas-based technical indicators, ternary trading signals, numeric grid search, portfolio simulation components, and a wrapper for multi-core repeated K-fold cross-validation. It also includes simulated end-of-day stock data and alternative data streams. Some remaining material depends on explanations and context from the book, so the repository is not presented as a complete standalone course.

Key features

• Evaluate trading strategies with performance metrics.
• Calculate common technical indicators using Pandas.
• Convert technical indicators into ternary signals.
• Run numeric grid searches and multi-core repeated K-fold cross-validation.
• Simulate portfolios and explore included simulated stock and alternative data streams. This repository contains Python source code for Chris Conlan’s 2020 book Algorithmic Trading with Python. It provides standalone research tools, including performance metrics, Pandas-based technical indicators, ternary trading signals, numeric grid search, portfolio simulation components, and a wrapper for multi-core repeated K-fold cross-validation. It also includes simulated end-of-day stock data and alternative data streams. Some remaining material depends on explanations and context from the book, so the repository is not presented as a complete standalone course.

Best for

Researchers and Python users exploring algorithmic trading methods who want reusable research components or the accompanying book’s source code. The standalone resources can be used independently; other material requires the book’s explanations and context.