Algorithmic Trading: Build a Momentum Strategy in Python

Algorithmic Trading: Build a Momentum Strategy in Python | Udemy [Update 10/2025]
English | Size: 3.16 GB
Genre: eLearning

Go from raw data to a fully analyzed, professional-grade trading strategy in Python.

What you’ll learn
Receive a complete, working momentum strategy and a professional library of reusable Python functions for performance analysis (worth the course price alone).
Build a complete, end-to-end algorithmic trading strategy in Python that you can run and test yourself.
Analyze your strategy’s true performance and risk using the same critical metrics (Sharpe, Sortino, Drawdowns) that professional quants rely on.
Write a professional-grade backtesting engine from scratch to realistically simulate portfolio performance, avoiding common “rookie” mistakes.
Go beyond theory: Statistically prove why a momentum strategy works with real-world data (and learn how to test your own future ideas).

Stop guessing and start building. This course is a complete, hands-on guide for finance professionals, data analysts, and Python developers who want to professionally build and test an algorithmic trading strategy. We’re not just talking theory; you will build a complete, data-driven momentum strategy—one of the most robust and academically-proven factors in finance—from the ground up.

First, you’ll learn how to validate a trading idea using data. You’ll test thousands of parameters to statistically prove the strategy has merit, visualizing your results in a professional heatmap before you write a single line of backtest code.

Next, you’ll build the strategy, step-by-step: gathering ETF data from a broad, liquid universe, cleaning it, and generating the core trading signals by ranking and selecting the top performers.

Finally, you will code a complete, realistic backtest that mimics how a real fund would trade, accounting for monthly rebalancing. You’ll go far beyond simple returns by building a professional performance “tear sheet” to analyze risk, drawdowns, Sharpe/Sortino ratios, and market capture.

You’ll walk away with a powerful, working momentum strategy and a reusable library of professional analysis functions that you can use to test any strategy idea. This is the practical, end-to-end blueprint for building with confidence and skill.

Who this course is for:
Aspiring algorithmic traders who want to learn how to build a complete, professional-grade backtest from scratch.
Python Developers curious about applying their coding skills to the financial markets.
Finance professionals, analysts, or students who want to move beyond Excel to build and test trading strategies in Python.
Traders and investors who want to stop guessing and start scientifically testing their own strategy ideas with real data.

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