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PyQuant News 🐍 Profile picture
@pyquantnews
Oct 7, 2024 • 10 tweets • 3 min read • Read on X
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A Bloomberg Terminal costs $30,000 per year.

Unaffordable for 99.9% of us.

Reserved for the Wall Street elite to outfox the normal investor.

OpenBB just dropped the $0 cost replacement.

Get 405 free data sources and an AI Copilot.

The 90-second step-by-step guide: OpenBB Terminal Pro
In case you're unfamiliar:

OpenBB is the first AI financial terminal that combines data integration with an AI agent to transform investment research.

• Private (your data is not shared)
• 100s of free data sources
• Custom data backends
• Advanced AI Copilot

How it works:
Set up a custom, local data server with 370 sources of free market data.

No coding required (just double click an icon):
Once the data server is running, add it to the dashboard.

Here's how to do it:
OpenBB's AI copilot can use any data to answer your questions.

Wondering about the crude oil futures curve?

OpenBB Copilot has an answer:
Can't get through the day's news?

OpenBB Copilot can summarize the top news in a single paragraph:
Use pre-built dashboard templates to make your analysis workflow even quicker:
OpenBB Terminal Pro uses the same charts as TradingView.

Get incredible charting capabilities in the same place as your fundamental, news, and economic data:
Select data in a table and generate plots in two clicks.

Then, ask the OpenBB AI Copilot what happened.

Wondering about the trend in Apple's earnings?

Plot it and ask AI:
OpenBB Terminal Pro comes with a simple double-click installation file.

No more virtual environments.

No more dependency hell.

Double click and go: Double click to install

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More from @pyquantnews

PyQuant News 🐍 Profile picture
Sep 6
In the age of AI, Jupyter Notebook is the most powerful tool Python developers have.

But most people don’t know the hidden features.

Need a quick web app?

Or create REST APIs?

Here are the 6 ways to use Jupyter Notebook (you never knew existed): The notebook to rule them all.
Jupyter Notebook is a web app for creating and sharing computational documents.

When I say powerful, here's what I mean:

• It supports 40 languages
• Produces rich, interactive output
• Leverages big data tools like Spark

So, what else can we do with Jupyter Notebook?
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nbdev let's you develop and publish Python packages right from Jupyter Notebook.

It generates documentation and publishes on GitHub Pages. You can also write tests and setup CI with GitHub Actions.

github.com/fastai/nbdev
Read 11 tweets
PyQuant News 🐍 Profile picture
Aug 31
Myth:

You need a computer science degree to get started with Python, NumPy, and pandas.

Reality:

You need these 8 YouTube videos:
"Python Pandas" by Corey Schafer

Learn the basics of creating and manipulating data frames, indexing and selecting data, and cleaning and manipulating data in Pandas.

"NumPy Array Basics" by sentdex

This video covers the basics of working with NumPy arrays, including creating arrays, indexing and slicing, and performing arithmetic operations.

Read 12 tweets
PyQuant News 🐍 Profile picture
Aug 24
Statistical arbitrage is scary sh*t.

That's what I used to think until I spent 25 hours studying pairs trading.

Now I realize it's a great way to get started with algorithmic trading.

Here’s how to build a pairs trading strategy in Python.

Step by step:
By replicating this framework, you’ll be able to:

1. Get stock price data
2. Find cointegrated pairs
3. Model the spread
4. Trade the strategy

What is pairs trading anyway?
Pairs trading is a way of trading an economic relationship between two stocks.

Two companieswith the same supply chain will be impacted by the same economic forces.

Pairs trading tries to model that relationship and make money when the relationship temporarily breaks down.
Read 13 tweets
PyQuant News 🐍 Profile picture
Aug 20
Python is the new Excel.

So don't be the only one stuck with 1,048,576 rows.

6 links to help you quickly get started with Python now: Image
The Ultimate Beginner’s Guide to NumPy

What you'll learn: NumPy is the foundation for all data-driven libraries in Python. Understanding the basics will help you learn other libraries like Pandas and get an edge on your peers.

towardsdatascience.com/the-ultimate-b…
Random Forests for Complete Beginners

What you'll learn: A thorough walkthrough of building and using decision trees and random forest machine learning techniques in Python.

victorzhou.com/blog/intro-to-…
Read 10 tweets
PyQuant News 🐍 Profile picture
Aug 18
You can use options to predict stock price moves.

Here’s how: Image
Options traders are well-informed. Their expectations of future stock price moves are often priced into options. We can use options prices to extract the options market’s expectations of stock price moves.

If we know where to look…
First, download earnings data. Image
Read 8 tweets
PyQuant News 🐍 Profile picture
Aug 12
My PhD professors taught me MATLAB during my master's degree.

So I watched 200 YouTube videos to learn Python

96% of them were a complete waste of time.

But these 8 taught me more than all my PhD professors combined:
Setting up Interactive Brokers API with Python

This video shows how to use Python with the Interactive Brokers API to automate a first strategy—cutting through its complexity in one clear walkthrough.

1,000,000 backtest simulations in 20 seconds with vectorbt

The video explains how parameter tweaking on random noise ruins backtests and shows how vectorbt enables proper walk-forward optimization for pairs trading.

Read 11 tweets

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