A complete guide to Time Series Momentum (TSMOM) - the strategy that bets on trends continuing. Covers the math, Python implementation from scratch, backtesting, performance metrics, volatility scaling, and common pitfalls. Based on Moskowitz, Ooi & Pedersen (2012). Includes code examples, visualizations, and resources for further learning.
-
Notifications
You must be signed in to change notification settings - Fork 3
A complete guide to Time Series Momentum (TSMOM) - the strategy that bets on trends continuing. Covers the math, Python implementation from scratch, backtesting, performance metrics, volatility scaling, and common pitfalls. Based on Moskowitz, Ooi & Pedersen (2012). Includes code examples, visualizations, and resources for further learning.
mirkovicdev/TSMOM
Folders and files
| Name | Name | Last commit message | Last commit date | |
|---|---|---|---|---|
Repository files navigation
About
A complete guide to Time Series Momentum (TSMOM) - the strategy that bets on trends continuing. Covers the math, Python implementation from scratch, backtesting, performance metrics, volatility scaling, and common pitfalls. Based on Moskowitz, Ooi & Pedersen (2012). Includes code examples, visualizations, and resources for further learning.
Resources
Stars
Watchers
Forks
Releases
No releases published
Packages 0
No packages published