PyQuant News 🐍’s Post

We're finally there! Come with me to conclude my series of posts where a tiny Python project is built to calculate advantages, disadvantages and immunities of Pokémon species from a generation! In this series, I went through many Python base concepts, as I did with some architectural patterns and good practices concepts. Let's have fun mixing Pokémon and Python together!

Create beautiful tear sheets with Pyfolio Reloaded. In 8 minutes with 1 line of Python code: You can check out the full video on YouTube here: https://lnkd.in/eHiBAM2V ~~~ Looking to start using Python for systematic trading? Here's a free Crash Course with everything you need to get started. Join the 1,000s of people who finally started with Python after reading it: https://lnkd.in/eaayJEfj

Model the yield curve's evolution with PCA (and Python). The video demonstrates how to use PCA to model the three factors that drive yield curve changes. And when you're ready... Here's a free Crash Course with everything you need to get started. Join the 1,000s of people who finally started with Python after reading it: https://lnkd.in/eaayJEfj

Legend Jim Simons talking about the secrets that make RenTec successful. ~~~ Looking to start using Python for systematic trading? Here's a free Crash Course with everything you need to get started. Join the 1,000s of people who finally started with Python after reading it: https://lnkd.in/eaayJEfj

What would you do? If you pick the button on the right, it might be time to change your approach. If you need help to get started using Python for algorithmic trading, I got you. Here's a free Ultimate Guide with everything you need to get started. Join the 1,000s of people who finally started with Python after reading it: https://lnkd.in/g6qzjFAD

Two weeks ago we traveled to New York to hang out with the Python community at PyData NYC. It was a blast with awesome people and presentations. Along with the booth we had, I gave a presentation on how we use Rust and Python together to power Bytewax. The talk is now available online for the Rust curious! 🦀 Key takeaways: - PyO3 is the secret! - Rust is not as hard as it looks! - There are plenty of tradeoffs between ergonomics and speed. - Python was built for interfacing with foreign code. https://lnkd.in/g8SV3bcT

Have you ever seen how high-frequency trading actually works? These are milliseconds... ~~~ Looking to start using Python for systematic trading? Here's a free Crash Course with everything you need to get started. Join the 1,000s of people who finally started with Python after reading it: https://lnkd.in/eaayJEfj

The mistake most beginners make: Overfitting their backtests. If you think you're strategy is winning, you might want to double-check. Are you looking to start using Python for algorithmic trading? Here's a free crash course with everything you need to get started. Join the 1,000s of people who finally started with Python after reading it: https://lnkd.in/e-7FkSPP

What is the difference between a Python list and a NumPy array? Answer: Python List: Flexible and can store mixed data types but slower for numerical computations. NumPy Array: Designed for numerical operations, supports vectorized operations, and consumes less memory, making it significantly faster. Example of vectorized operation with NumPy: arr = np.array([1, 2, 3]) result = arr * 2 ( Multiplies each element by 2 )

Do you struggle to make sense of your data with clunky tools? Try Jenny instead! 😊 Simply load your data and enter a short prompt—Jenny takes care of the rest. Jenny will generate the plot, explain how your data was processed, and even create Python code. What are you waiting for? Start your free trial with Jenny today at genofeva.ai!