I recommend you as well Abdul Bari's channel () for the explanations of how the algorithms work etc. and if you are more into books, you can read 'introduction to algorithms' which is a reference in the domain

Now looking at the difficulty of the problems, if you are a 'simple' Quant, you will mostly have medium problems but if you apply for Quant Dev position or SWE, then the odds are on the hard difficulty.

For SWE it's good for you to read as well 'cracking the coding interview'. And in a more general way, if you need a roadmap, you can take a look at neetcode ()

Now for the 'mini project assessment', for what I have seen, those mostly appears for hedge fund and are mostly oriented towards : - Data Analysis - Machine Learning - market making

I have not done some myself (only saw it when my friends applied) thus I can't say much about it.

Now you passed the test, it's time for the interview During those, there is 4 group of questions : - Brainteasers - Finance - Maths - Fit

For the brainteasers there are two kinds : the first one are brainteasers on probability and the second are 'tricks based' brainteaser. For the probability one, most of them use cards, dices, ...

for the others, they are more situation and modelling based. However most of the time you need a specific trick to solve them.

It's a bit a pain in the ass but there is not an infinity of tricks therefore if you do a lot of them and understand the patterns, you should be good on it.

For maths oriented questions, the 'subjects' kinda depends on who's interviewing you. If you are interviewed by a bank, as you mostly work on derivatives, your 'pure maths' questions will be oriented towards probability, stochastic calculus, algebra, analysis

BUT don't forget that this is in the GENERAL CASE, when talking with some friends, depending on the exact position / subject of your internship, the question asked vary a lot.

Therefore if you are interviewing in a bank and your subject is deep hedging, you will be asked some stuff about machine learning.

Concerning Stochastic Calculus, you need to know your stuff on how to determine the law of a Wiener integral, apply the Ito lemma, solve usual SDE (geometric brownian, Ornstein-Uhlenbeck, ...), Girsanov, Feynman-Kac.

Concerning machine learning, most questions I have seen are around the basics. What is the linear regression, lasso, ridge (pros and cons), PCA, bias-variance tradeoff etc...

Concerning numerical methods, we talked about Monte-Carlo and finite difference so be aware of the convergence order, the pros and cons of each methods, ...

But you can as well have stuff about optimization like the gradient descent or more 'finance' oriented stuff like the Longstaff-Schwartz algorithms and in which contexte it's usefull.

Concerning analysis/algebra, it's more around an undergrade level so linear algebra, matrix decomposition, ...

Now for finance you can have basic questions, difference between a forward and a future, payoff of a digital, of a straddle, how to reproduce a straddle with vanilla options. What are the greeks, their interpretations, the limits of the black-scholes model, ...

So for the books recommendation : if you don't know anything about finance you can start with the Hull (Options Futures and Other Derivatives). I'm not a big fan of this book as it doesn't go very deep but it can still give the big picture so more like a book for 'context'

To go deeper into finance and with a bit more mathematics, you can read the Bouzouba (Exotic Options and Hybrids). In this one you will see more stuff dealing with options, volatility surfaces, models, ...

For a focus on interview questions, there are special books : - Heard on the street - 150 Most Frequently asked questions on quant interviews - A practical guide to quantitative finance - Quant Job Interview Questions and Answers

Specifically for brainteaser, or at least to work on the thinking, you can take a look at brainstellar (). The discrete/probability puzzles are kinda interesting for this. Furthermore you can take a look at '50 problems in probability with solutions'.

I think that's all. There is a lot more ressources but tbh I have not read all of them so I'm not that much into recommending it. If I read them and like them, I will add it to this thread. Good luck for your interviews guys.