Resources for Quant Dev (important announcements) Python for Quants''1
Before we go into the resources, for 1 week (until Valentines) we are doing discounted access for our quant library for trading and learning:
quantpylib: (50% off, $182)
https://hangukquant.thinkific.com/courses/quantpylib
and Funding Arbitrage lectures: ($300 off, $850)
https://hangukquant.thinkific.com/courses/qt410
Additionally, for each sale of the above items during this period, we will be allocating 50-USD to the bounty program to reward contributors to quantpylib:
In the last post, we released 100+ pages of notes on efficient python programming:
We will evolve this work with new updates, examples and case studies of writing Python for quants. Although we intend these notes to be self contained, we would first like to give a useful reading list for those who would like to go in-depth on their own.
I have included C/C++ material as understanding the behavior of low(er) level language implementations is crucial to appreciate the abstractions that the Python language abstracts away from the developer.
Only then would there be a good appreciation of what can be done to bring back performance optimizations into a high level language.
C/C++ Programming
Cython
Cython: A Guide for Python Programmers
Python
Python Concurrency with asyncio
The rest of the reading material is on my reading list, but I have not completed them yet - so I cannot give assured recommendation:
Numerical Python, Scientific Computing and Data Science Applications
See you in the next post.