This is a nice little book that summarizes questions and answers that many new quants may have about the quantitative finance field. The book answers questions at a relatively high level and too keep each question short only the most important points are stressed. Readers unfamiliar with this book can see what others have said here.

At the end of the book is a section on common quant interviewing questions. To make sure that I understood this material as well as possible I solved (and wrote up) as many of the questions as I had time for. For the problems that worked, I also developed working mathematical codes, that can be used to produce numerical solutions. You can find this material by following the various links on this page.

- matching_bdays.m (computes the probability that from n people at least two have the same birthday)

- position_in_line.m (computes the probability your birthday matches one of the n people ahead of you)

- balls_in_a_bag.m (evaluates the balls in a bag problem)

- ann_return.R (evaluates the annual returns problem)

- dice_game.m (performs the Monte Carlo simulation requested)

- closer_to_the_center.m (plots the region closer to the center)

- two_thirds_the_average.m (performs the iterations for this problem)

- einsteins_brainteaser.py (enumerates the possible combinations)

- miss_moneypenny.m (experiments in selecting the best secretary)

- eval_prob_best_selection_at_m.m (for given n and m evaluates the probability we select the best secretary)

- eval_prob_best_selection.m (for a given n evaluates what m gives the largest probability of selecting the best secretary)

John Weatherwax Last modified: Sun Jul 13 17:55:46 EDT 2008