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Quant interview questions you should always expect

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If you’re interviewing for a quant role in an investment bank, these are some the questions you should expect.

1) Can you tell me, briefly (and in words that a layman or non-quantitatively trained trader would understand) the contents of your thesis?
2) What are the limitations of Black-Scholes, implied volatility, and jump diffiusion models?
3) Are exchange rates mean reverting?
4) What test would you apply for mean reversion?
5) Why is there an n-1 term in standard deviation?
6) How do you manage risk and return using the Kelly criterion?
7) What is Itô's Lemma?
8) What assumptions must be made regarding the properties of derivatives for Itô's Lemma to be applied correctly?
9) Tell me a little about the big issues in your markets at the moment…

Especially for algo traders:
10) Can you explain the basic theory behind the Kalman Filter? (Expect this in algorithmic trading interviews)
11) How would you use the Kalman Filter to model stock price movements? (Expect this in algorithmic trading interviews too)

Especially for programmers:
12) How would you programme the Sieve of Eratosthenes?
13) How would you code up a smart pointer?
14) How would you code an exception safe copy constructor?
These questions have been assembled with the assistance of @DominiConnor at P&D Quant Recruitment and Trevor Symons at Selby Jennings.

An example of a longer quant question:
Here we have a supplementary quant question from Quora
15) ‘You want to evaluate an existing fixed for floating interest rate swap with 16 months remaining to maturity. Fixed side pays semi-annually, floating side pays quarterly and both sides pay at the maturity date. How many floating rate payments are left? How long until the next floating rate payment?’

Credit: http://news.efinancialcareers.co.uk/NEWS_ITEM/newsItemId-30976
 
Actually I helped write that article, but for some reason wasn't credited, words will be said on that.

The one about why there is an N-1 term in standard devitation seems to have got lost.

Mark Joshi has written a far more comprehensive list of questions together with their answers.
 
Just a question, why are the programming questions so comparatively easy? For example, programming the sieve of Eratosthenes was litteraly one of the projects for my middle school programming class. I feel as if you're asking about higher level math (i.e stochastic calculus) you should be asking about higher-level programming... no?
 
I've been playing around with Haskell recently and Wikipedia has an example of the concept of the sieve of Eratosthenes done in said language (known as Turner's sieve), for those interested:

Code:
primes = sieve [2..]
sieve (p : xs) = p : sieve [x | x <- xs, x `mod` p > 0]
It's rather simple and elegant.
 
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