Hi,
I wanted to write this meet for quite a long time. I am posting below some useful accounts to follow in different social media/websites with regards to quant finance. I have learned so much by following these and I hope you will enjoy their posts as much as I do. Without further ado:
- Finance:
FinTwit is full of noise, but sometimes you can find some rare pearls (a signal-to-ratio true to the field you might say)
- https://twitter.com/Ksidiii : former exotics trader, still young but provides very detailed thread on equity vol.
- https://twitter.com/bennpeifert : vol oriented systematic trader. Used to teach in the Berkely MFE program.
- https://twitter.com/VolQuant : Also vol trader, very interesting threads (more macro oriented).
- https://twitter.com/nope_its_lily : tons of useful stuff in her feed, but a lot of shitposting as well. Follow at your expense.
- https://twitter.com/SinclairEuan : checkout his books more.
- https://www.linkedin.com/in/frido-r-22a1094: Please follow this guy in SSRN and LinkedIn, his knowledge of the derivatives space and models is quite amazing.
- https://www.reddit.com/r/options/comments/8qfs14/options_book_list_review_of_all_books_that_helped/ : an amazing book list review about options books.
There are a lot of useful podcasts to listen to as well. I have to go through some of them and curate before posting here.
- Mathematics:
- https://twitter.com/daniela_witten : One of the co-authors of ISLR, she writes every now and then, interesting threads about statistics.
- https://twitter.com/gabrielpeyre : interesting stuff, provides a nice applied maths general culture.
- https://twitter.com/WomenInStat : weekly rotating account. Every week you got a new poster and they post quality content about their domain of expertise.
Mathematicians are not the greatest marketers obviously, but there is always something new to learn from books. A lot has been written about counterexamples for example, and so on.
- Computer Science:
Could not found persons per say to follow (except mcmar) but put a few useful links for continuous learning
- https://leetcode.com/discuss/career/216554/from-0-to-clearing-uberappleamazonlinkedingoogle
- https://leetcode.com/mcmar/
- https://github.com/CME211/notes : C++ and Python from Stanford.
- https://missing.csail.mit.edu/2020/course-shell : bash and shell from MIT.
- https://github.com/ossu/computer-science : whole CS program, please have a look, wonderful stuff.