Financial ML Features

Lesson Overview

In "Machine Learning for Trading" → "Feature Engineering", this lesson "Financial ML Features" builds knowledge you can apply immediately.

Features: lag returns, rolling vol, RSI, day-of-week. Avoid future leak: strict time-based train/test split. Never shuffle time series.

Core Concepts

These points align with the video walkthrough—take notes as you watch.

• ▸Features: lag returns, rolling vol, RSI, day-of-week.
• ▸Avoid future leak: strict time-based train/test split.
• ▸Never shuffle time series.

Practical Application

After studying, complete the companion practice lesson to move from understanding to doing.

• ▸Follow along in Jupyter or VS Code
• ▸Log how parameter changes affect backtest results
• ▸Submit a reproducible analysis notebook

FAQ

• ▸Q: How does this lesson fit the course? A: Part of "Feature Engineering"—follow the curriculum order.
• ▸Q: What do I need? A: Demo account and notes; quant lessons need a Python environment.
• ▸Q: How do I know I've mastered it? A: Pass the quiz and explain three key points of Financial ML Features on your own.