Learn the statistical technique of Cointegration and build your own crypto backtester to create and test a quantitative trading strategy.
This tutorial is in 2 parts — (you can run the backtester as a separate standalone module) :
- Learn the Statistical technique of Cointegration.
- Build a Bitcoin Backtesting engine using Python to analyze the performance of a Cointegration based trading strategy.
Just want the code? click here.
What are we building
October is historically the most volatile month for stocks, but is this a persistent signal or just noise in the data?
Stocks, Significance Testing & p-Hacking.
Over the past 32 years, October has been the most volatile month on average for the S&P500 and December the least, in this article we will use simulation to assess the statistical significance of this observation and to what extent this observation could occur by chance. All code included!
This post is now live on DataCamp — click here!
Our goal:
- Demonstrate how to use Pandas to analyze Time Series
- Understand how to construct a hypothesis test
- Use simulation to perform hypothesis testing
- Show the importance of accounting for multiple comparison bias
Our data:
We will be using Daily…
So you’ve completed Andrew Ng’s Deep Learning course on Coursera,
You know that ForwardProp looks like this:
Patrick David
Machine Learning , Deep Learning, AI, Python, Quant Trading -ML Researcher - follow for walkthroughs, tutorials, proofs, research etc. Also on twitter @pdquant
