đź‘‹ Hey, I'm Jason
15+ years coding with Python
20+ years trading stocks and options
Photo of Jason, set against a transparent background.
In 1999 when I was 18, I made two decisions that changed my life:

I learned how to code and traded my first stock.

The code was PHP—and it was awful. The stock was MSFT—and I lost money.

But I was hooked.

I knew that I HAD to somehow combine coding and trading.

But how?

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!

I was just starting to explore Python for computational finance, algorithmic trading, and derivatives pricing.

But nothing I was learning was sticking.

The courses were theoretical and the videos superficial.

It was time to make a change.

$2,000 for MATLAB?
By the time I finished my master’s degree, I was obsessed with quant finance, the markets, and programming.

I learned MATLAB during my master’s degree and never even considered paying for it.

When I finished, I went to download it and they asked me for my credit card.

$2,000 per year!

The last thing I wanted to do was pay $2,000 for an annual license!

So I became obsessed with Python. I kept taking tutorial after tutorial after tutorial only to be in the same place I started. I got frustrated and quit.

I was completely overwhelmed with the academic papers, tutorials, and YouTube videos.

I was frustrated with taking courses that taught beginner-level material I couldn’t even use.

I was frustrated with running into bugs and other issues and not being able to get help.

I wanted nothing more than to be a quant. To leverage my experience with this powerful tool.

But I was stuck!
The conversation I'll never forget
I was stuck.

I was burning out. Afraid my $90,000 master’s degree was a waste.

It wasn’t until one of my professors and quant at UBS O’Connor said something to me that changed my life:

“Just learn enough Python to solve one goal and make progress. You’re not a computer scientist or a professional developer. Python is just a tool to get the job done.”

I was dumbstruck. It was so obvious that I could barely consider it.

Then I tried it.

And I learned just enough Python to build a simple backtesting framework.

And guess what?

It worked!

Gone was my imposter syndrome.

Gone was being overwhelmed with where to start.

Gone was getting stuck in Tutorial Hell.

And the best part?

I learned just enough Python to apply it to a real-life problem I had.

I had a clear goal in mind and regained the momentum to get started with Python for quant finance.

Fast forward to today, and I’ve lived and worked in 3 countries as a quant.

I traded professionally for a hedge fund and an energy derivatives trading firm in Chicago wracking up several millions of dollars in profit.

I was a credit quant looking after $20 billion in credit exposure and managing $100 million of CVA exposure.

I managed a global, quant engineering team that built all the market risk analytics for a $7 billion derivatives trading business.

I built and led the data engineering and quant-analyst team for a $60 billion metals trading business.

And I started PyQuant News in 2015 to share what I was learning about Python and quant finance.

In October 2022 I launched Getting Started With Python for Quant Finance and have taught 1,000+ people the frameworks I’ve learned over 20 years of trial and error.

And I’m sharing them with you now!

The origins of PyQuant News

In 2015, I looked at my list of bookmarks.

There were hundreds, if not thousands, of articles, blogs, papers, videos, and code repos for algo trading, derivatives pricing, and data analysis with Python.

I started pyquantnews.com and started publishing links as I came across them. I hooked the site up to Twitter to automatically post tweets with the same link.

I did it as a way to build accountability for keeping up with the latest trends is Python and trading.

I managed the website for 7 years, posting links—and tweets—a few times a month.

Fast forward to October 2022. I had taught myself Python over the years and built amazing frameworks that started helping other people. I had 50K+ Twitter followers and 10K newsletter subscribers. I was posting content every day and writing a newsletter every week. I was talking to dozens of people of DM, email, and even Zoom.

Turns out a lot of people had the same problem I had—they wanted to get started with Python, but were spinning their wheels. And since I experienced firsthand the power of the frameworks I built, I felt obligated to help as many others do it too.

So in October 2022, I sent this tweet:
Introducing Getting Started With Python for Quant Finance.  A cohort-based course and community that will take you from complete beginner to up and running with Python for quant finance in 30 days.  The first cohort starts 13 November with limited spots.
‍The tweet that changed lives

20 days after that tweet, 234 people signed up and committed to learning Python every day for 30 days.

Learning, iterating, building friendships, and having a damn good time doing it.

I spent those 30 days talking to every person in the cohort. I soaked in everything I could about the problems they faced, what they had tried in the past, and the reasons they wanted to get started with Python. And I learned exactly what did and didn’t work for helping people start using Python for quant finance every day.

Then on December 19, Nick left this public testimonial:
Gave me the materials I needed with a mentor to guide me along the way to achieve my end goal of landing an active trader role.
‍Nick landed a new job thanks to the course.

That’s when I knew something was working.

18 months and 1,000+ students later, Getting Started With Python for Quant Finance has evolved into an immersive, cohort-based course and community. I have packed everything I know about building habits into over 20 hours of curriculum. I’ve built templates and guides to help anyone, no matter their level of experience, get started.

And I’ve built a rich, diverse community of like-minded finance professionals, Python developers, and complete beginners all with the same goal.

So what’s next?

What's next for PyQuant News

My vision for Getting Started With Python for Quant Finance is to build the best digital community on the internet for finance professionals, Python developers, and complete beginners to get started with Python for quant finance. Not only that, but to make money doing it. Whether it’s a new job, a promotion, or quitting your job completely, I want to be here to help.

And unlike most programs, my idea of success is not one-dimensional.

I am not going to sell you a “get rich quick” trading scheme. In fact, I don’t teach any strategies. I teach frameworks for you to build your own.

People get started with Python for different reasons.

Some get started to automate manual tasks. Some get started to backtest trading strategies. Some get started to download and analyze financial market data. Some get started to get a new job.

Whatever your reason is for getting started with Python for quant finance, I want to help you get there faster.

So, what’s my vision for the future?

Help anyone who wants to learn Python for quant finance get started.

And experience a life-changing outcome.

If that sounds like the journey you want to be on, then you’re in the right place.
Man with glasses and a wristwatch, wearing a white shirt, looking thoughtfully at a laptop with a data screen in the background.