English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 30 Lessons (7h 55m) | 3.32 GB
Go from raw data to a fully analyzed, professional-grade trading strategy in Python.
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.
Table of Contents
Introduction and Primers
1 Course Overview
2 Google Colab Primer
3 Financial Modeling Prep Primer and Storing API Keys
4 Read This Before Continuing!
5 Introduction to Momentum
6 Disclaimers
Understanding Momentum and Why it Works
7 Setting Up the Colab Environment
8 Downloading Pricing Data
9 Analyzing the ETF Universe
10 Filtering the ETF Universe
11 Ranking ETF Performance
12 Calculating Forward Return Deciles
13 Data Visualization I
14 Data Visualization II
15 Data Visualization III
Building the Momentum Strategy and Algorithm
16 Coding the Strategy I
17 Coding the Strategy II
18 Coding the Strategy III
19 Coding the Strategy IV
20 Coding the Strategy V
21 Coding the Strategy VI
The Final Project Building a Pro-Grade Backtest & Tear Sheet
22 Setting up the Pro Backtest I
23 Pro Backtest II
24 Pro Backtest III
25 Pro Backtest IV
26 Pro Backtest V
27 Pro Backtest VI
28 Pro Backtest VII
29 Performance Analysis
What Comes Next
30 Conclusion
Resolve the captcha to access the links!
