Topics:

€ Mathematics, calculus, differential equations

€ Covariance and correlation matrices. Linear algebra

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

Buy Now From Amazon

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.



Similar Products

A Practical Guide To Quantitative Finance InterviewsHeard on the Street: Quantitative Questions from Wall Street Job InterviewsQuant Job Interview Questions and Answers (Second Edition)Fifty Challenging Problems in Probability with Solutions (Dover Books on Mathematics)A Primer For The Mathematics Of Financial Engineering, Second Edition (Financial Engineering Advanced Background Series)Advances in Financial Machine LearningFrequently Asked Questions in Quantitative FinanceA Linear Algebra Primer for Financial Engineering: Covariance Matrices, Eigenvectors, OLS, and more (Financial Engineering Advanced Background Series)