Quantitative researcher Interview Questions | Glassdoor

# Quantitative researcher Interview Questions

636

quantitative researcher interview questions shared by candidates

## Top Interview Questions

Sort: RelevancePopular Date

### Quantitative Analyst at Morgan Stanley was asked...

Jan 21, 2014
 What's the best unbiased estimator for a series random variables?5 AnswersI guess it is just a Gaussian distribution (Normal dist.). Since it has the smallest uncertainty (from quantum point of view) or variance.I guess it is just a Gaussian distribution (Normal dist.), since it has the smallest uncertainty (from quantum point of view) or variance.It is the OLS estimator (with Gauss-Markov approximations and normality), by Fisher's theorem on Maximum Likelihood Estimators.Show More ResponsesIt didn't mention linear. if it's linear, then ols. if not, CEF, conditional expectation function.It didn't mention linear. if it's linear, then ols. if not, CEF, conditional expectation function.

May 14, 2011

Apr 17, 2011

### Software Engineering and Quantitative Research at D. E. Shaw & Co. - Investment Firm was asked...

Jan 9, 2014

Nov 18, 2015
 Given log X ~ N(0,1). Compute the expectation of X.12 AnswersThis is a basic probability question.Exp[1/4]exp(mu + (sigma^2)/2) = exp(0+1/2) = exp(1/2)Show More ResponsesLet Y = log(X), then X = exp(Y) = r(Y), if we call the pdf of X f(X), then E[X] = integral(Xf(X)dX). By variable transformation, f(x) = g(r^-1(X))r^-1(X))', plug this into E[X] = integral(Xf(X)dX), we get integral( f(y)dy ), which equals to 1Suppose the density function of Y is P(y) and the one for X is F(x), it obeys that P(y)*dy = F(x)*dx; then the expectation of X is E(x) = Integral( x*F(x)*dx ) = Integral( Exp(y) * P(y) * dy ); if you plug the gaussian function and standard deviation in, you will find E(x) = Integral( Exp(1/2) * P(y-1/2)*d(y-1/2) ) = Exp(1/2) So, mojo's ans is correct.I m not that sure, as I got E(x) = 4 I substituted log X = y e^y = X ;and e^2y = t and plz do not forget to change the integration limitsDo they care if you explain the theory or not? I just looked at it, it's standard normal, therefore x=50%P(logX P(XSorry misread the problem. ignore.X has a log-normal distribution, so yes the mean is exp(mu+sigma^2/2)=exp(1/2)Expanding on the correct answers above: E[X] = E[exp(logX)], and logX is normally distributed. So: E[X} is the moment-generating-function (mgf) of a standard normal distribution, evaluated at 1. The mgf of a normal distribution with mean mu, SD sigma is exp(mu*t + (1/2) * sigma^2 * t^2), now set mu = 0, sigma = 1, t = 1 to get exp(1/2).Complete the square in the integral

Dec 9, 2016

Jul 31, 2009

Nov 11, 2015