PyQuant News – Python for Quant Finance

What You’ll Learn In Python for Quant Finance

Module #1: Getting the Python Basics Right

We kick off with the very basics of Python. We cover primitive data types, data structures, control statements, functions, and classes. This is a practical but critical introduction to Python!

Module #2: The Python Quant Stack

The most important library you’ll use is Pandas. You can use pandas for 80%+ of all work you’ll do in quant finance. In this module, we dive deep into several practical examples of using pandas for market data analysis.

Module #3: Algorithmic Trading for Non-Professional Traders

The harsh truth is most people get algorithmic trading, backtesting, and strategy formation wrong. In this module, you’ll understand how non-professional investors can compete, how to backtest the right way, and the 8-step process for strategy formation.

Module #4: Treat Your Backtest Like an Experiment

Most people think backtesting is all about optimizing input parameters to maximize profit. That’s exactly the wrong way to backtest. In this module, you’ll see how to statistically test a backtest and shift your framing of backtesting forever.

Module #5: Prototyping and Optimizing Strategies with VectorBT

VectorBT is an advanced vector-based backtesting framework that simulates millions of strategies in seconds. In this module, we’ll analyze our example crack spread trade and optimize the entry and exit z-score signals.

Module #6: How to Engineer Alpha Factors With Python

Most people have heard of alpha. Most people even have a concept of alpha. Few have the technical understanding of alpha. In this module, we’ll define alpha, discuss how to hedge beta to isolate it, and build alpha factors to capture it.

Module #7: How to Backtest A Trading Strategy with Zipline Reloaded

Zipline Reloaded is the most robust event-based backtesting framework available. Zipline Reloaded is great for backtesting portfolio strategies based on alpha factors. In this module, we’ll use Zipline Reloaded to backtest an alpha factor.

Module #8: Risk and Performance Analysis with Pyfolio and Alphalens

Risk and performance analysis is critical. Luckily for us, a suite of tools plays nice with the Zipline Reloaded backtesting framework. In this module, you’ll get intuition on how to use risk and performance metrics to improve your investing and trading.

Module #9: Execute Trades on Interactive Brokers With Python

The last step of the algorithmic trading pipeline is executing trades. Unfortunately, it’s tricky to get right. In this module, we’ll build the basic scaffolding for a trading app using the Interactive Brokers API.

Module #10: Course Wrap-Up and Next Steps

Whether you were writing code every day or missed a few, making it through the course is no easy feat. So, in this final module, we will recap everything we learned and discuss how you can take the next steps to continue your Python journey!

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

You’ll want a refund if:

• You’d prefer to learn the theory behind programming and quant finance and not actually apply anything in practice
• You prefer “figuring it out yourself” with a plethora of lessons with no clear path
• You’re hoping that buying a course like this will give you trading strategies that will print you money
• You’re looking for another Python tutorial that will help you do things like print “Hello World” and the Fibonacci sequence to the screen
• You don’t really need to use Python in your field and probably won’t anytime soon
• You’re OK with using the tools you have (like Excel) and are unwilling to budge in the slightest.
• You’re thinking this course will teach you fundamentals of computer science like memory management.
• You want to use Python to brute force optimize backtests and data mine the market (a bit of an inside joke you’ll understand once you dig into the course!)

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