Jason Strimpel – Getting Started With Python for Quant Finance – May 2024

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Jason Strimpel – Getting Started With Python for Quant Finance – May 2024

Unlock promotions, career opportunities, and extra income with Python.
Getting Started With Python for Quant Finance has helped 1,000+ students get started with Python and achieve life-changing results.

No theory. No jargon. Just practical Python you can use.

Live Sessions with a Quant

Get your questions answered in real-time so you never get stuck. Live group sessions from a practitioner with 20+ years of experience as a trader and quant.

Working Code Templates

Pre-built templates for algorithmic trading, options pricing, and more. Use them as-is or modify them for your purposes. Code to get started immediately.

Real-World Applicability

You won’t learn a bunch of theory that doesn’t help you in real life. You’ll learn how to use the same tools as the pros so you’re never behind the competition.

You know Python can help in a lot of ways:

• Get a new job
• Stand out at work
• Advance your career
• Earn passive income trading
• Improve your trading performance

You know to unlock these goals, you need Python for data, analysis, and trading.

So you took a $19 online course.

You learned how to build a tic-tac-toe game from someone that has never traded, done financial analysis, or even worked in finance.

Or more useless theory that doesn’t get you any closer to your goals.

I’ve been there.

If you’re new to Python, you probably start by googling “python tutorial.” Then you see the 533,000,000 results, scroll for a few seconds, then jump to the first paid ad you see.

You’ve read the blogs, watched YouTube, and taken all the courses.

But actually using Python for quant finance in real life (and not just for toy examples)?

That can seem like something other people figure out, not you.

Instead, you’re…

• Taking courses with no practical application, examples, or real-world projects
• Wasting time on one-size-fits-all tutorials focused on syntax—not quant finance
• Buying recorded courses that leave you with broken code, “magic solutions,” outdated libraries, and no one to help you
• Totally lost with where to focus your attention to get the concrete skills and experience you want
• Stressing out about actually applying what you learn so you can improve your job prospects (or quit your job altogether)
• Sound about right?

It’s one thing to “learn Python.” But it’s a completely different thing to use Python for quant finance.

For many of us, getting started with Python is a mystery.

You know there is immense power at your finger tips, but you just can’t quite figure out how to go from theory to practice.

Modules, IDEs, swaps, options, Jupyter, functions, automation, backtesting, loops, classes, CVaR, Sharpe, list comprehensions, walk forward analysis…

People may as well be speaking another language.

Hi there, I’m Jason and I’m the creator of Getting Started With Python for Quant Finance.

I can translate that language for you.

I’ve been trading for over 20 years, a quant for 15, and a daily user of Python for 12.

In October 2022, I started helping other people learn how to put the three together.

The course 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.Jason gets straight to the point and avoids all the fluff that other courses use that wastes a tremendous amount of time.

Nick, Active Trader
November Cohort

Over the years, I’ve helped hundreds of finance professionals, developers, and complete beginners use Python for quant finance. I’ve done this through keynote talks, Meetups, Twitter threads, LinkedIn posts, in-depth articles, newsletters, and my course Getting Started With Python for Quant Finance.

But Getting Started With Python for Quant Finance is not actually a course.
It’s not theory.

It’s not jargon.

It’s not printing “Hello World” to the screen.

Included is an entire framework to get you started with Python for quant finance.
It’s a complete set of step-by-step, proven frameworks that gives you:

• Engaging, live group sessions for real-time answers
• An experienced, hands-on instructor to guide you every step
• 1,000s of lines of quant code you can use to kick start your projects
• Industry Speakers from firms like Man Group, SigTech, OpenBB, CrunchDAO, ThetaData, and QuantConnect so you can network with industry practitioners
• A structured, step-by-step path to getting outcomes with Python

So what does all that actually mean?

It means that you won’t waste time learning Python you can’t use. It means you’ll get the skills for a new quant job or to start trading from home.

You get the same quant tools I used to analyze $20 billion of derivatives credit exposure, manage $100 million book of CVA, manage a global team of quant engineers, and trade stocks and options.

So if you’re struggling to get started with Python for quant finance, this course is for you.

What’s Inside
Inside you’ll find real-time answers, code to get you started, and hundreds of people for networking, sharing ideas, and accelerating your progress. To maximize your investment, you’ll also get video replays, a written course curriculum

Onboarding Week:
An entire week of self-paced activity to get ready for the course
Install the Python Quant Stack, download market data, and connect to Interactive Brokers—all with step-by-step instructions.

Live Session 1:
Getting the Python Basics Right

If you’re brand new to Python, you’ll fast-track your learning with exactly what you need to know—no overwhelm, no complexity

Live Session 2:
The Python Quant Stack

Get familiar with the finance-specific Python libraries for algo trading and data analysis so you can work with market data

Live Session #3:
Algorithmic Trading for Non-Professional Traders
Yes! Retail traders can compete. Get a framework to form trading ideas, test them, and get them executed

Live Session #4:
Treat Your Backtest Like an Experiment
Understand why most people get backtesting wrong—and the secret of how to avoid losing money because of a backtest

Live Session #5:
How to Engineer Alpha Factors With Python
Get the tools and techniques professional money managers use to manage portfolios and hedge unwanted risk

Live Session #6:
Prototyping and Optimizing Strategies with VectorBT
Get working code to run millions of simulations to optimize your strategy with the cutting-edge VectorBT backtesting library

Live Session #7:
How to Backtest A Trading Strategy with Zipline Reloaded
Build factor pipelines to screen and sort a universe of 20,000 equities to build and backtest real-life factor portfolios

Live Session #8:
Risk and Performance Analysis with PyFolio and AlphaLens
Get the code to quickly asses strategy risk and performance—including factor performance—and assess alpha decay

Live Session #9:
Automate Trade Execution with Python
Connect to your broker, download market data, and automate your trades so you can get to trading, faster

The Recipe Book
In addition to the Live sessions, written curriculum, and PQN Pro community, you get self-paced code “recipe.” Each one includes a 20-minute video walkthrough and is packed with code designed to get you started ASAP.

The Recipe Book:
19 code templates—each with 20-minute video walkthroughs.
Get code to calculate trading risk metrics, price an option with the Edgeworth model, forecast volatility with GARCH, simulate stock prices with GBM, hedge beta, use PCA for isolate factors, backtest with Zipline, automate trade execution, and tons more.

Code for portfolio risk and performance optimization
6 code templates and video walkthroughs to build the foundational risk and performance metrics for improving your trading performance.

Code to price options and derivatives with Python
4 code templates and video walkthroughs to price options and forecast implied volatility for trading edge.

Code to build factor portfolios and hedge beta
4 code templates and video walkthroughs to reduce risk and build portfolios that make money.

Code to connect to Interactive Brokers and automate trades
5 code templates and video walkthroughs to demonstrate an algo trading system you can modify for your own purposes.

Should you join? Here’s what I think…
Not everyone is right for Getting Started With Python for Quant Finance. And while I offer a full guarantee, I want to make sure I don’t waste your time.

You’ll love this course if:

• You want to use Python for getting market data, analyzing the financial markets, backtesting, and automating trading
• You’re sick of paying Udemy and Datacamp for courses that are irrelevant to your goals
• You want a somewhat opinionated approach to installing Python, writing code, and using the Python Quant Stack
• You’re brand new to Python, quant finance, or both
• You realize that taking tutorial after tutorial does not guarantee success. You want to learn and adopt of framework that will make you successful using Python
• You don’t have time to waste learning a programming language and want to know just want you need
• You want step-by-step guidance and structure from someone who’s been in the industry for 23 years
• You like specific, hands-on instruction and don’t have time for the fluff

Hi! 👋 I’m Jason.
My name is Jason Strimpel and I’m the creator of Getting Started With Python for Quant Finance.I traded my first stock and wrote my first line of code when I was 18.Since then:☀️ 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 $40 billion metals trading business.☀️ I taught myself Python in 2012 to avoid spending $2,000 per year on a MATLAB license after finishing my master’s degree in quant finance.☀️ I trade stocks and options in my free time using Python for data acquisition, automation, and execution.My quant career has allowed me to live and work in 3 countries (the United States, England, and Singapore) and travel to 41.I started PyQuant News in 2015 to share what I knew about Python for quant finance. Seven years later, I’m still at it.

Commonly Asked Questions:

1. Business Model Innovation: Acknowledge the reality of a legitimate enterprise! Our approach involves the coordination of a collective purchase, in which the costs are shared among the participants. We utilize this cash to acquire renowned courses from sale pages and make them accessible to individuals with restricted financial resources. Our clients appreciate the affordability and accessibility we provide, despite the authors’ concerns.
2. Getting Started With Python for Quant Finance Course

• There are no scheduled coaching calls or sessions with the author.
• Access to the author’s private Facebook group or web portal is not permitted.
• No access to the author’s private membership forum.
• There is no direct email support available from the author or their team.