I have 10+ years of experience in the finance industry. My understanding of systematic trading strategies is high but my programming skills ranges from beginning to intermediate. The end goal of this process is to build my own successful automated trading strategy. After some research, I found it best to start my journey with the book Trading Evolved by Andreas F. Clenow.
As I begin reading the book I have decided to create a resources and scenarios page. The resources page will provide a list of books and articles for anyone interesting in learning more about systematic trading. The scenarios page will provide various trading strategies to test your ability to back test systematic trading strategies. I will continue to build these pages (and likely come up with more pages) as I continue to add blog posts.
- Scenario 1:
- Long only equities
- Holding period = long term capital gains
- Low correlation to equity strategies
- Downside protection
- Purpose of scenario 1:
- Achieve near zero or negative correlation
- Scale to 100s of millions
- Show modest couple of percent per year
- Improve diversification & enhance overall performance
- Scenario 2:
- Stock falls four standard deviations below is 60 day linear regression
- Expectation is that stock will bounce two standard deviations up
- Test variations of the above:
- Change linear regression to 30 or 90 days
- Change bounce to 3 or 5 standard deviations up
- Books:
- Python for Data Analysis
- Python for Finance
- Systematic Trading
- Trading Evolved
And remember, computers are only as smart as the person programming it…