Share this page!

PyQuant News 🐍 Profile picture
Twitter logo
Nov 23 • 22 tweets • 6 min read
Skip the quant finance degree.

Dive into 17 code repos that will teach you more than all your professors at school.

All without costing you $90,000:
OpenBB Terminal

Terminal for investment research for everyone.

github.com/OpenBB-finance…
PyQL

QuantLib's Python port.

github.com/enthought/pyql
vollib

vollib is a Python library for calculating option prices, implied volatility, and greeks.

github.com/vollib/vollib
QuantPy

A framework for quantitative finance In python.

github.com/jsmidt/QuantPy
Finance-Python

Python tools for Finance.

github.com/alpha-miner/Fi…
ffn

A financial function library for Python.

github.com/pmorissette/ffn
pynance

Lightweight Python library for assembling and analysing financial data.

github.com/GriffinAustin/…
pysabr

SABR model Python implementation.

github.com/ynouri/pysabr
FinancePy

A Python Finance Library that focuses on the pricing and risk-management of Financial Derivatives, including fixed-income, equity, FX and credit derivatives.

github.com/domokane/Finan…
gs-quant

Python toolkit for quantitative finance.

github.com/goldmansachs/g…
willowtree

Robust and flexible Python implementation of the willow tree lattice for derivatives pricing.

github.com/federicomariam…
financial-engineering

Applications of Monte Carlo methods to financial engineering projects, in Python.

github.com/federicomariam…
optlib

A library for financial options pricing written in Python.

github.com/dbrojas/optlib
tf-quant-finance

High-performance TensorFlow library for quantitative finance.

github.com/google/tf-quan…
Q-Fin

A Python library for mathematical finance.

github.com/RomanMichaelPa…
Quantsbin

Tools for pricing and plotting of vanilla option prices, greeks, and various other analysis around them.

github.com/quantsbin/Quan…
finoptions

Complete python implementation of R package fOptions with partial implementation of fExoticOptions for pricing various options.

github.com/bbcho/finoptio…
For more on options:

Get the 46-Page Guide to Pricing Options and Implied Volatility.

Here's why:

• Compute Black-Scholes, the greeks, and implied volatility
• Includes a Jupyter Notebook with the code
• How to use Python to analyze the results

pyquantnews.gumroad.com/l/46-page-ulti…
Boom!

17 libraries that will teach you more than a master's.

• ffn
• optlib
• Q-Fin
• PyQL
• vollib
• pysabr
• OpenBB
• QuantPy
• pynance
• gs-quant
• FinancePy
• Quantsbin
• finoptions
• willowtree
• Finance-Python
• tf-quant-finance
• financial-engineering
There's a lot here!

Hop back up to the top tweet (click the link here) and retweet it to keep it handy for later and show your followers you know your Python.

Then, if you like tweets like this, follow @pyquantnews for more!
If you like Tweets about trading, you might enjoy my weekly newsletter: The PyQuant Newsletter.

Real Python code for quant finance you can use now.

Join 7,800+ subscribers who are taking action with Python.

pyquantnews.com/the-pyquant-ne…

• • •

Missing some Tweet in this thread? You can try to force a refresh
　

Keep Current with PyQuant News 🐍

PyQuant News 🐍 Profile picture

Stay in touch and get notified when new unrolls are available from this author!

Read all threads

This Thread may be Removed Anytime!

PDF

Twitter may remove this content at anytime! Save it as PDF for later use!

Try unrolling a thread yourself!

how to unroll video
  1. Follow @ThreadReaderApp to mention us!

  2. From a Twitter thread mention us with a keyword "unroll"
@threadreaderapp unroll

Practice here first or read more on our help page!

More from @pyquantnews

PyQuant News 🐍 Profile picture
Nov 24
99% of beginners get backtesting wrong:

Build backtest, get poor results. Tweak backtest, get positive results.

Then they wonder why they lose money.

Here's the dead-simple framework the pros use to get backtesting right:
If you replicate this framework, you’ll:

• Setup a backtest with bt
• Run a backtest and analyze results
• Assess how random your results are

Plus, you’ll dramatically reduce the risk of your strategy performing poorly in the market after a great backtest.

But first…
In case you’re new to backtesting.

It's used to:

• Simulate how a strategy might perform live
• Test trading ideas against historic market data
• Optimize for performance parameters like Sharpe

It's easy to setup but hard to get right.

Here’s how to do it with Python.
Read 21 tweets
PyQuant News 🐍 Profile picture
Nov 23
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 next cohort starts 15 January with limited spots.

Here's everything you get:
🎥 10 live sessions where you'll install and configure Python, create a quant lab in Jupyter Notebook, install packages, understand the quant finance landscape, and build real quant code.
🥇 10-module curriculum you can review at your own pace (with lifetime access to these recordings).
Read 17 tweets
PyQuant News 🐍 Profile picture
Nov 20
My rocket scientist professor told me to learn Octave during my master's degree ("it's free MATLAB").

So I watched 197 YouTube videos to learn Python instead.

94.4% of them were a complete waste of time.

But these 11 taught me more than all my PhD professors combined:
Basic Statistical Arbitrage: Understanding the Math Behind Pairs Trading

The statistics that ground the trading logic when conducting and finding pairs trades.

Developing Trading Strategies

How quant trading strategies are developed and tested with author and fund manager Ernie Chan.

Read 14 tweets
PyQuant News 🐍 Profile picture
Nov 17
Professional investors know returns are not normally distributed.

So they use the Omega ratio to capture the full distribution.

You don’t need to be a professional to do it too.

Here’s how in Python:
By reading this thread, you will know:

1. Why investors use the Omega ratio
2. How to get stock data in Python
3. How to compute Omega ratio
4. Analyze return distributions

Are you ready?
In case you’re unfamiliar with the Omega ratio:

• Considers a return threshold
• Weighted probability of gains divided by losses
• Uses the positive and negative integral to capture skew and kurtosis

Sound abstract?

In Python, it's easy.
Read 12 tweets
PyQuant News 🐍 Profile picture
Nov 16
Myth:

You need a PhD to get started with Python for quant finance.

Reality:

You need Jupyter Notebooks pre-built with quant code.

Get 20 with Getting Started With Python for Quant Finance.

Here's a breakdown of all 20:
And here's what else you get:

• $1,000 at IB
• 6 deep dives
• 10 live sessions
• Private community
• 10-module curriculum
• Deep Dive into OpenBB
• Lifetime access to recordings
• A free copy of 2 options ebooks

Now, on to the Notebooks!

…gstartedwithpythonforquantfinance.com
Assess a real trading strategy

Algorithmic trading is hard for retail traders. Don't spend 6 months building a backtest for one that doesn't work.

This Notebook shows you how to assess a working trading strategy quickly.
Read 24 tweets
PyQuant News 🐍 Profile picture
Nov 14
Yesterday, 217 people started Getting Started With Python for Quant Finance.

In 30 days they will:

• Escape from Tutorial Hell
• Beat imposter syndrome
• Destroy overwhelm

And FINALLY get started with Python for quant finance.

Here's what else they get:
🎥 10 live sessions where you'll install and configure Python, create a quant lab in Jupyter Notebook, install packages, understand the quant finance landscape, learn algorithmic trading, and build real quant code.
🥇 10-module curriculum you can review at your own pace (with lifetime access to these recordings).
Read 15 tweets

Did Thread Reader help you today?

Support us! We are indie developers!

This site is made by just two indie developers on a laptop doing marketing, support and development! Read more about the story.

Become a Premium Member ($3/month or $30/year) and get exclusive features!

Become Premium

Don't want to be a Premium member but still want to support us?

Make a small donation by buying us coffee ($5) or help with server cost ($10)

Donate via Paypal

Or Donate anonymously using crypto!

Ethereum

0xfe58350B80634f60Fa6Dc149a72b4DFbc17D341E copy

Bitcoin

3ATGMxNzCUFzxpMCHL5sWSt4DVtS8UqXpi copy

Thank you for your support!

Follow Us on Twitter!

Send Email!

:(