What are the best-selling books that Quantnet members purchased in 2010?
The following 25 best-selling books is compiled from a list of almost 600 titles purchased as provided by Amazon where Quantnet.com is shown as a referrer. The complete list is attached here.
#Title1 A Primer for the Mathematics of Financial Engineering – Dan Stefanica 2 Solutions Manual – A Primer For The Mathematics Of Financial Engineering – Dan Stefanica 3 50 Challenging Problems in Probability with Solutions – Frederick Mosteller 4 Quant Job Interview Questions And Answers – Mark Joshi 5 A Practical Guide To Quantitative Finance Interviews – Xinfeng Zhou 6 My Life as a Quant: Reflections on Physics and Finance – Emanuel Derman 7 How I Became a Quant: Insights from 25 of Wall Street’s Elite – Richard R. Lindsey 8 Heard on The Street: Quantitative Questions from Wall Street Job Interviews – Timothy Crack 9 Starting Your Career as a Wall Street Quant – Brett Jiu 10 Frequently Asked Questions in Quantitative Finance – Paul Wilmott 11 The Complete Guide to Capital Markets for Quantitative Professionals 12 C++ Design Patterns and Derivatives Pricing – Mark Joshi 13 Principles of Financial Engineering, 2nd Edition – Salih Neftci 14 Stochastic Calculus for Finance I: The Binomial Asset Pricing Model – Steve Shreve 15 Problem Solving with C++, 7th Edition – Walter Savitch 16 Liar’s Poker – Michael Lewis 17 Financial Instrument Pricing Using C++ – Daniel Duffy 18 Stochastic Calculus for Finance II: Continuous-Time Models – Steve Shreve 19 The Concepts and Practice of Mathematical Finance – Mark Joshi 20 Nerds on Wall Street: maths, Machines and Wired Markets – David Leinweber 21 Liar’s Poker: Rising Through the Wreckage on Wall Street (Hardcover) – Michael Lewis 22 Introduction to C++ for Financial Engineers: An Object-Oriented Approach – Daniel Duffy 23 Working the Street: What You Need to Know About Life on Wall Street – Erik Banks 24 An Introduction to the Mathematics of Financial Derivatives, Second Edition – Salih Neftci 25 Monte Carlo Methods in Financial Engineering – Paul GlassermanThis post originally appeared at Quant Network.
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