This episode features Dr. Yves Hilpisch—the founder of The Python Quants.

TPQ do a lot of good for those involved in quantitative finance, they; frequently host meet-ups and workshops, have developed platforms and analytics libraries, and often contract to exchanges, banks and hedge funds for custom Python development.

Yves is also a three-time published author, with his most notable title probably being “Python for Finance” which was released through O’Reilly. He regularly gives presentations and speaks at events on the subject of quant finance, and lectures at Universities too.

Over the next sixty minutes, you’ll hear us unpack many subjects related to being a quant and why programming in Python can be a useful skill to have in your toolbox.

Note, some of the discussion in the later part may be a little heavy for non-programmers. So if there is something that doesn’t make sense or you’d like more context around, please just write in the comments at the bottom of this page and I’ll do my best to point you in the right direction.

Lessons learned in this interview:

• In case you’re new to this, Yves explains what it means to be a “quant” and how one tries to make sense of markets which varies from other types of participants.
• How a quant looks for opportunities and areas where they can exploit the market. Plus, a brief walk through history; applying quantitative methods to finance.
• Yves shares his thoughts on the effectiveness of machine learning (and similar techniques) and where he sees potential value from social sentiment data.
• Many years ago, Yves started The Python Quants—he speaks about his motives and what goes on inside the events and meet-ups they host in various countries.
• Out of all the programming languages in existence, Yves talks about why Python is his preferred choice for financial applications and it’s overall popularity.
• Yves uses Pandas—a Python library created by a programmer within a large hedge fund—as a paramount example for open-sourced code and value of collaboration.
• A practical way for non-programmers to learn how to code in Python, educational resources, and what sort of commitment is required to become proficient.

Links and resources mentioned:

• Python for Finance: Analyze Big Financial Data by Yves Hilpsih – Published in 2014, this book shows examples of how Python can be used for quant finance.

• Derivatives Analytics with Python by Yves Hilpisch – Published in 2015, this book demonstrates the powerful capabilities of Python for options analytics & hedging.
• TPQ.io – Here’s the center point for everything related to The Python Quants, i.e. educational material, browser-based analytics platforms, training and more.
• Hilpisch.com – Here’s the center point for Yves himself—this is where you can find his Jupyter Notebooks (code), presentations, various projects and more.
• @DYJH – Follow Yves on Twitter, and tweet him about this episode.

How to support this podcast:

• For a quick and easy way to support this free podcast, please write an honest review in iTunes. It’ll take you two minutes, and it helps massively—thank you.