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Jan 24, 2023 11 tweets 3 min read Read on X
7 books for automated trading you should read in 2023:
Algorithmic Trading with Python: Quantitative Methods and Strategy Development

Lessons:

• Modern quant trading methods in Python
• Focus on pandas, numpy, and scikit-learn
Algorithmic Trading with Interactive Brokers (Python and C++)

Lessons:

• Developing applications based on TWS
• Implement full-scale trading systems
Learn Algorithmic Trading: Build and deploy algorithmic trading systems and strategies using Python

Lessons:

• Fundamentals of algorithmic trading
• Apply algorithms to real market data
Python for Algorithmic Trading: From Idea to Cloud Deployment

Lessons:

• Ways to apply Python to algorithmic trading
• Interacting with online trading platforms.
Machine Learning for Algorithmic Trading

Lessons:

• Leverage ML to design automated trading strategies
• Use pandas, TA-Lib, scikit-learn, TensorFlow, and Backtrader
Hands-On Financial Trading with Python: A practical guide to using Zipline and other Python libraries for backtesting trading strategies

Lessons:

• Build and backtest your algorithmic trading strategies
• How to gain a true advantage in the market
Python for Finance and Algorithmic Trading: Machine Learning, Deep Learning, Time Series Analysis, Risk and Portfolio Management, Quantitative Trading

Lessons:

• Connect Python algorithms to MetaTrader 5
• Run the strategies with a demo or live trading account
Reading is foundational to growth and learning.

You can read all these books before July by reading 20 minutes a day.

Make it a priority.
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I post Python code and tools for quant finance at 8:15 am EST and 8:15 pm EST every day.
The FREE 7-day masterclass that will get you up and running with Python for quant finance.

Here's what you get:

• Working code to trade with Python
• Frameworks to get you started TODAY
• Trading strategy formation framework

7 days. Big results.

pythonforquantfinancemasterclass.com

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More from @pyquantnews

Feb 3
RenTec uses Hidden Markov Models in trading.

The technique generated 60% returns per year over 30 years.

One of the co-founders of RenTec's name is in the algorithm!

Here's how it works: Image
A Hidden Markov Model (HMM) is a statistical model used to represent systems that evolve over time with unobservable (hidden) states.

It is widely applied in areas such as natural language processing, speech recognition, and bioinformatics.

And in trading:
HMMs are particularly useful when dealing with sequential data, where the underlying process is governed by probabilities.
Read 9 tweets
Jan 23
Python and Excel:

A potent combination for working with data.

Here are the 17 Python libraries to help you unlock the power.
XlsxWriter

XlsxWriter is a Python module for writing files in the Excel 2007+ XLSX file format.

github.com/jmcnamara/Xlsx…
xlwings

xlwings is a BSD-licensed Python library that makes it easy to call Python from Excel and vice versa.

github.com/xlwings/xlwings
Read 19 tweets
Jan 20
Backtesting options strategies sucks.

• Millions of contracts
• Weekly expirations
• Assignment if ITM

Now, you can backtest options strategies in a few lines of code.

Here’s how (with a link to historical options data): Image
Optopsy is an analysis tool for options trading strategies.

• Generates strategies from raw historic data
• Uncover performance statistics for combos
• 12 strategies built in including strangles

We’ll use 5 years of historic options data on RUT for the analysis.

Let’s go!
First, import the libraries we need.

Optopsy is light with very few dependencies. Image
Read 12 tweets
Jan 10
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:
Algorithmic Trading Using Python (4.5 hours)

Learn how to perform algorithmic trading using Python in this complete course. Algorithmic trading means using computers to make investment decisions.

Quantitative Stock Price Analysis with Python (25 minutes)

We look at some quantitative analytical methods of stock price changes using Python and pandas.

Read 12 tweets
Dec 31, 2025
17 free Python GitHub repos for quant finance and algo trading:
OpenBB-finance: Investment Research for Everyone, Anywhere.

github.com/OpenBB-finance…
Read 19 tweets
Dec 22, 2025
Algorithmic trading is the domain of secretive hedge funds and banks.

Python unlocked these secrets for everyone (even Goldman Sachs has an open-source tool).

Use the same tools the professionals use.

Here are 17 Python libraries that open the black box: Image
OpenBB Terminal

Terminal for investment research for everyone.

github.com/OpenBB-finance…
PyQL

QuantLib's Python port.

github.com/enthought/pyql
Read 21 tweets

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