The questions were very generic. Was asked a simple probability brain teaser.
Quantitative Research Interview Questions
815 quantitative research interview questions shared by candidates
Given that I only did a basic phone screen, nothing was unexpected.
They asked about experience with large data sets
Assumptions of the Black-Scholes option pricing formula. And asked me to write the formula.
Probability, normal distribution properties, Brownian motion...
ED 1.Option payoff: (Max(s1,s2),0)+, find the p1,2 that could maximize the payoff(p1,2 = -1) 2.Option payoff: 1(s>k), use which model to price it VP 3.go through your resume 4.internship experience, discussed a strategy I developed before, asked a lot details 5.assumptions of OLS 6.why no multicolinearity; how to check multicolinearity (VIF), definition of VIF statistic, other methods without checking VIF? (large r squared, but none of the parameters is significant) 7.stepwise 8.arma, acf and pacf plots, very detailed 9.probability problem, conditional probability 10. expected time to clean up 100 dirty apples in a bag, pick one each time ED 11.go through your resume 12.my exchange experience 13.internship experience 14.probability, classic 3 doors problem, should I switch 15.conditional probability 16.BS equation, why no u? (no arbitrage) 17.difination of brownie motion
What is inheritance?
1)X,Y are standard random variables, the correlation is 0.5. Given X, what's the conditional distribution of Y? 2)A,B,C are r.v.s. correlation between A and B is 0.9, between B and C is 0.9. is it possible that A is unrelated to C? 3)Given two assets, their average return, variance of return and correlation. Find a portfolio such that the sharpe ratio is optimal. 4)toss coins consecutively, get 1 pt if head is up and 2 pts if tail is up. So we can get a sequence of total points. Question: what is the probability that we have 100 pts in this sequence?
tell me about yourself; some basics of prob. and linear algebra; data frame questions in python and r
Solving SDE
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