"Led by two top-notch quants, Richard R. Lindsey and Barry Schachter, How I Became a Quant details the quirky world of quantitative analysis through stories told by some of today's most successful quants. For anyone who might have thought otherwise, there are engaging personalities behind all that number crunching!" --Ira Kawaller, Kawaller & Co. and the Kawaller Fund
"A fun and fascinating read. This book tells the story of how academics, physicists, mathematicians, and other scientists became professional investors managing billions." --David A. Krell, President and CEO, International Securities Exchange
"How I Became a Quant should be must reading for all students with a quantitative aptitude. It provides fascinating examples of the dynamic career opportunities potentially open to anyone with the skills and passion for quantitative analysis." --Roy D. Henriksson, Chief Investment Officer, Advanced Portfolio Management
"Quants"--those who design and implement mathematical models for the pricing of derivatives, assessment of risk, or prediction of market movements--are the backbone of today's investment industry. As the greater volatility of current financial markets has driven investors to seek shelter from increasing uncertainty, the quant revolution has given people the opportunity to avoid unwanted financial risk by literally trading it away, or more specifically, paying someone else to take on the unwanted risk.
How I Became a Quant reveals the faces behind the quant revolution, offering you?the?chance to learn firsthand what it's like to be a?quant today. In this fascinating collection of Wall Street war stories, more than two dozen quants detail their roots, roles, and contributions, explaining what they do and how they do it, as well as outlining the sometimes unexpected paths they have followed from the halls of academia to the front lines of an investment revolution.
This collection of essays by quants lets you inside their heads and into the somewhat secretive world of quantitative investing. As in any collection, the quality is uneven, but the best chapters are golden (I highly recommend the essays by Andrew Weisman, David Leinweber, and Neil Chriss—neither of them is a prolific writer which makes this book a rare source of insight into their minds). The level of discussion rises above the usual uninformed drivel emanating from organs such as Wall Street Journal, Business Week, or the Economist, but remains accessible to non-mathematical reader. For those interested, there are plenty of references to technical papers with all the math one could want (and more).
The only downside of the book is the (understandable) fact that the discoveries and strategies it discusses are fairly old, mostly dating to 1980s and 1990s. It would be unrealistic to expect cutting-edge money-making ideas in a $17 paperback.
How I became a Quant is the insightful study in the world of mathematical modelling of financial securities. With first person accounts of 25 well known quant specialists, the reader gets a detailed account of how the trend started. The book is filled with interesting anecdotes and challenges faced by people coming into this skill. If you are interested in the world of Quants, this book is a good starting point to gain perspective into the practical working of various Quant roles. Given most of the accounts are from 90s, the world has moved a lot ahead but the basic principles mentioned by people in the book still holds true.
Everyone knows that, due to the fatter than lognormal tails in most asset returns, far- from-the-money options should generally be priced significantly above the Black-Scholes formula price.
An interesting assortment of short essays written by the practitioners of financial engineering. Not a lot of depth, nice and easy leisure read though!
As the title would suggests, the book is a sneak peek into the life of 25 Professionals succeeded in the world of Finance who were good at Mathematics and Data analysis and to an extent technology.
The book consists of 25 stories, one devoted to a quant. I found all the stories really informative and inspiring. Although some stories could have been better written. One doesn't need much mathematical background to follow the chapters.
Financial Engineering is now an established career but some of these people started out when the field was in its infancy. It is great to see how they tackled the challenges they faced.
Recommended for people who want an inside view of the world of quantitative finance or just about anyone who is good with numbers and has an inclination towards towards Finance.
As the title suggests, this book throws light on the process of how to become a quant. Quant is a person who specializes in application of mathematical techniques to financial domain, making models to predict returns or manage risks etc. The stories shared are highly inspiring and guides one to becoming a quant. Though personally I think, times have changed a lot from when PhDs in math or physics was requisite in the beginning period of quantitative finance. Today, a lot of master courses help graduates get into this field. Nevertheless, I found this book interesting, to know how these 25 Wall Street elites started, the challenges they faced, how this shaped their life, and how they molded the industry.
This is a very insightful book for anyone wanting to know about the field of quantitative finance. In reading it, I found that there is a marked distinction between quantitative analysts (quants) who come from physics and mathematics and those who come from the more traditional frields of finance, economics, and business. I find the physicists and mathematicians have far more lucid stories of how they became quants as well as the field itself. Perhaps it's due to the culture within science but they truly outshine the econo-finance types in the book--both in how they became quants and how they are on the leading edge of the field.
This book is awesome for 1) people who are already quant-types and want an easy read, or 2) high schoolers or college kids who have no idea what they want to do but are good with math and computers. Everyone else will probably not enjoy this. Also, the editor was asleep at the wheel on this one, as there are tons of typos.