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"Best book I've found on Algorithmic Trading with Python"
- Acquire free market data with the OpenBB Platform
- Build a research environment and populate it with financial market data
- Use machine learning to identify alpha factors and engineer them into signals
- Use VectorBT to find strategy parameters using walk-forward optimization
- Build production-ready backtests with Zipline Reloaded and evaluate factor performance
- Set up the code framework to connect and send an order to Interactive Brokers
Yahoo! Finance and MSN Feature Jason Strimpel of PyQuant News
But Python is the most popular and accessible of all programming languages.
And you're not building GenAIÂ apps with Excel...
Python is the new Excel.
Read the full article.
When I was 18 I made two decisions that changed my life: I learned how to code and traded my first stock.
For the next 10 years, I followed the conventional advice:
• Get a degree in business (double major in finance and econ)
• Get industry experience (I traded for a hedge fund and a bank)
• Get a master’s degree (I got a $90,000 master’s degree in finance)
The problem?
I didn’t have a Ph.D., I didn’t have a computer science degree, and I thought I needed both to get into quant finance.
I was overwhelmed with the amount of information available, intimidated by the caliber of talent in the market, and had no confidence in myself!
And worse of all:
Nothing I was learning was sticking because it was all theory.
Then in 2012, I got great advice that I should use Python as a tool to get the job done—I don’t have to be a programmer.
That kick-started my journey into Python.
In October 2022 I launched Getting Started With Python for Quant Finance to help others use Python to accomplish their goals faster.
I packed everything I know about using Python for algo trading, data analysis, and derivatives into the course.
And I’ve built a rich, diverse community of like-minded finance professionals, Python developers, and complete beginners all with the same goal: