Backtesting Trading Strategies in Python -- Deep Dive

Transform your trading and take it to the next level!

Backtesting in Python

Learn more from Dr Tom Starke on how to navigate the backtesting world. 

About this course

This Backtesting Deep Dive course offers you a solid foundation in algorithmic trading. We will show you
  • a comprehensive Python backtesting framework,
  • the various types of backtesting,
  • how you can speed up your backtests by 100 times (yes, 2 orders of magnitude),
  • how to sweep and optimise trading parameters to arrive at a sound trading strategy,
  • how to improve your portfolio construction, and 
  • advanced quantitative analysis to evaluate your trading strategy from different perspectives. 
So by the end of the course, you will be able to build fast, efficient trading systems that you have confidence on.
This course teaches you how to see what is hidden. This is how to use systematic trading tools to avoid pitfalls. 

  • $549

Backtesting Trading Strategies in Python - DEEP DIVE

  • Closed
  • 26 Lessons

Rely less on luck, gain control and validate your trading strategies. Taught by specialist in quantitative trading. 
Get access

Dr Tom Starke

CEO of AAA Quants

With Tom's extensive expertise of over 15 years in the field and his valuable collaborations with prestigious hedge funds and proprietary trading firms,
he empowers you to play in the big league of finance too.

Tom has a passion for teaching and sharing his knowledge with others. Drawing from his own experience, he has built AAA Quants Academy as a solution he wished he had when he began his journey.

Now, you too can leverage the condensed
knowledge and expertise on this platform to excel in
quantitative finance and algorithmic trading.
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Contents

Welcome

Course overview
Preview
Python notebook for the course

1. Preparing financial data for backtesting

Resampling for different data frequencies
Filling financial data

2. Different types of backtests

Pandas backtest
Preview
Looping backtest
Vectorised backtest

3. Parameter sweeps to gain insights

An example -- sweeping different moving average windows
Defining a metric
Visualisation -- 3D plots
Visualisation -- contour plots
How to ensure our strategy also delivers for the future?
Assessing the best parameters -- are they viable trades?

4. Basics of portfolio optimisation

Varying asset weightings -- preparation
Randomising asset weightings
Finding the best asset weightings
Evaluating the performance of the optimised portfolio

5. Advanced analysis

Sortino ratio
CAGR (Compound Annual Growth Rate)
Beta
Monte Carlo simulation -- different return paths
Distribution of returns
Assessing the strategy further -- trimming the tails

6. Test your knowledge!

Exercises without answers
Exercises with answers
Explanations