150 Most Frequently Asked Questions on Quant Interviews (Pocket Book Guides for Quant Interviews)

Topics:

• Mathematics, calculus, differential equations

• Covariance and correlation matrices. Linear algebra

• Financial instruments: options, bonds, swaps, forwards, futures

• C++, algorithms, data structures

• Monte Carlo simulations. Numerical methods

• Probability. Stochastic calculus

• Brainteasers

The use of quantitative methods and programming skills in all areas of finance, from trading to risk management, has grown tremendously in recent years, and accelerated through the financial crisis and with the advent of the big data era. A core body of knowledge is required for successfully interviewing for a quant type position. The challenge lies in the fact that this knowledge encompasses finance, programming (in particular C++ programming), and several areas of mathematics (probability and stochastic calculus, numerical methods, linear algebra, and advanced calculus). Moreover, brainteasers are often asked to probe the ingenuity of candidates.

This book contains over 150 questions covering this core body of knowledge. These questions are frequently and currently asked on interviews for quantitative positions, and cover a vast spectrum, from C++ and data structures, to finance, brainteasers, and stochastic calculus.

The answers to all of these questions are included in the book. These answers are written in the same very practical vein that was used to select the questions: they are complete, but straight to the point, as they would be given in an interview.

The authors are professors in the elite Masters Program in Financial Engineering at Baruch College, City University of New York, and have vast experience educating students who interview very successfully for quantitative positions (95% employment rate for 2007-2013 Baruch MFE graduates).

Dan Stefanica has been the Director of the Baruch MFE Program since its inception in 2002, and is the author of the best-selling A Primer For The Mathematics Of Financial Engineering and A Linear Algebra Primer for Financial Engineering. He teaches graduate courses on numerical methods for financial engineering, as well as pre-program courses on advanced calculus and numerical linear algebra with financial applications. His research spans numerical analysis, graph theory, and geophysical fluid dynamics. He has a PhD in mathematics from New York University and taught previously at the Massachusetts Institute of Technology.

Rados Radoicic has been on the faculty of the Baruch MFE Program since 2006, teaching graduate courses on financial instruments, econometrics, and statistics, as well as pre-program courses on advanced calculus with financial applications. He has done extensive research in discrete and computational geometry, extremal combinatorics, and graph theory. He has a BS and a PhD in mathematics from the Massachusetts Institute of Technology.

Tai-Ho Wang has been on the faculty of the Baruch MFE Program since 2008, teaching graduate courses on stochastic processes and optimization methods, as well as pre-program courses in probability. His research spans fields as varied as quantitative finance, statistics, and Riemannian geometry. He has a PhD in applied mathematics from National Chiao Tung University.