QuantNet has been compiling the annual list of best-selling quant books our members purchase every year since 2010 (see the best-selling book lists of 2010, 2011,2012, 2013. The following list is 20 best-selling quant books of 2014 (both hard-copy and ebooks), compiled from aggregate, anonymously collected data, provided by Amazon with QuantNet tags.
- A Primer For The Mathematics Of Financial Engineering, Second Edition - Dan Stefanica
- 150 Most Frequently Asked Questions on Quant Interviews - Dan Stefanica, Rados Radoicic, Tai-Ho Wang
- Fifty Challenging Problems in Probability with Solutions - Frederick Mosteller
- Solutions Manual - A Primer For The Mathematics Of Financial Engineering, Second Edition - Dan Stefanica
- The Complete Guide to Capital Markets for Quantitative Professionals - Alex Kuznetsov
- A Practical Guide To Quantitative Finance Interviews - Xinfeng Zhou
- Quant Job Interview Questions and Answers (Second edition) - Mark Joshi
- Liar's Poker: Rising Through the Wreckage on Wall Street - Michael Lewis
- When Genius Failed: The Rise and Fall of Long-Term Capital Management - Roger Lowenstein
- C++ Primer Plus (6th Edition) (Developer's Library) - Stephen Prata
- My Life as a Quant: Reflections on Physics and Finance - Emanuel Derman
- Heard on the Street: Quantitative Questions from Wall Street Job Interviews - Timothy Crack
- Frequently Asked Questions in Quantitative Finance - Paul Wilmott
- How I Became a Quant: Insights from 25 of Wall Street's Elite - Richard R. Lindsey, Barry Schachter
- Cracking the Coding Interview: 150 Programming Questions and Solutions - Gayle Laakmann McDowell
- Stochastic Calculus for Finance I: The Binomial Asset Pricing Model - Steven Shreve
- Stochastic Calculus for Finance II: Continuous-Time Models (Springer Finance) - Steven Shreve
- A Linear Algebra Primer for Financial Engineering: Covariance Matrices, Eigenvectors, OLS, and more - Dan Stefanica
- Financial Options: From Theory to Practice - Stephen Figlewski, William Silber
- Matlab, Third Edition: A Practical Introduction to Programming and Problem Solving - Stormy Attaway
C++ Programing for Financial Engineering Online Certificate. Approved for 15 CPE credit hours by GARP
With great pleasure, we'd like to announce that the Global Association of Risk Professionals (GARP) has approved our "C++ Programming for Financial Engineering" online certificate for 15 GARP CPE credit hours.
These 15 CPE credits will be only available to those who completed our C++ certificate in 2014 and later. If you are a Certified FRM®, ERP®, please record this activity in your Credit Tracker at www.garp.org/cpe. Contact CPE@garp.com with questions.
Since 2011, many of our members have taken the course as an important tool to achieve their career goal, be it to get in a top quant program or move to a more quantitative job. The feedback has been overwhelmingly positive. We will continue to work hard to provide the course at the highest level of quality.
An interesting article on NYTimes about the changing landscape of business schools where it's increasingly important to teach "skills like A/B testing, rapid prototyping and data-driven decision making, the bread and butter of Silicon Valley."
According to the article, the study body at MBA programs is changing as well. At Harvard Business School, "a third or more of the 900 students there have experience as programmers, and far more of them have undergraduate degrees in the so-called STEM disciplines — science, technology, engineering or mathematics".
How these changes at the top M.B.A programs will trickle down to science, business department across the country remain to be seen.
“But the major business issue, especially for entrepreneurs, is often that problems are not known, need to be discovered or defined in a new way,” Mr. Pass said. “You need a more integrated, broader view of things.”
The M.B.A. program, he said, is trying to nurture people with those wider horizons, technical know-how and quick business reflexes — “a new pivot on graduate education,” as he put it.
Now, this is the kind of training I may pay big bucks for.
From their press release
A group of students at Montana State University are in their first semester of a new financial engineering program that will feature professors from two colleges.
The new program, approved by the Montana Board of Regents last year, will allow MSU undergraduate students to major or minor in financial engineering with a curriculum of courses spanning the Department of Agricultural Economics and Economics in the College of Agriculture and the Department of Mechanical and Industrial Engineering in the College of Engineering.
If you’re someone with a mathematical bent, for whom ‘challenging’ maths questions are elementary and differential equations are fun, there is – allegedly – one place where you’ll feel especially fulfilled in banking: Goldman Sachs’ ‘strats’ Group. All banks have mathematical wizards, but the warlocks in Goldman’s strats team are reportedly higher paid, happier, and more empowered than those elsewhere.
“The strats team here is broader in scope than quant teams at other banks,” one strats vice president at Goldman in London tells us, speaking off the record as he is not authorised to talk to the press. “As well as quants, we have quant developers, technologists, structurers and salespeople.” Goldman’s strats team is at the forefront of the firm’s algorithmic and electronic trading business, he adds – making it key to the future of the firm.
Goldman itself describes its strats team as a, ‘a world leader in developing quantitative and technological techniques to solve complex business problems.’ Members of the team are divided into three groups: ‘desk strats’ who sit with traders and develop derivative pricing models and trading algorithms, ‘sales strats’ who support the sales team with quantitative research for client questions, and ‘core strats’ who work on the firm’s technology architecture using Goldman’s own proprietary coding language, ‘Slang.’ As we reported last week, Goldman’s already powerful strats group is said to be gaining influence internally now that the new CIO, Marty Chavez (a former strat himself) manages both strats and technology for the firm. The former CIO, Steve Scopellite, merely had technology in his purview.
Since writing for this blog in January about the HFT/algo job market, I’ve received many inquiries from students asking about the “requirements” for quant jobs on Wall Street. “Do I need a PhD?” is a frequent question. Each time I receive one of these inquiries, I struggle with the answer. My instinct is no. But when I look at who is working in these jobs, I do see a predominance of PhD’s in the top positions. PhD’s in mathematics, physics, operations research, EE, etc. are common in the quant community. So it’s tempting to tell students that a PhD is helpful, but it feels like the wrong answer. In my gut I know that the people getting these jobs are not getting offers because they have extra letters after their name. The people in these positions are there because they have proved over their academic and professional lives that they are:
At the end of last year I sent a State-of-the-Talent-Market email to colleagues. In that mail I wrote:
@Ken Abbott, a frequent contributor to QuantNet, replied to my mail:
Subsequently, he asked if I would elaborate on the job market in algo and HFT for this blog.
The simple answer is yes, there are jobs in Algo/HFT, and some of them are paying very well. However, that jaw dropping salary that you heard from a friend is only going to the very best individuals with rarified talent.
I have a large hedge fund client that is a pioneer in algo trading. I recently presented a candidate for a quant role at the firm, and the first thing the recruiter asked me about him was, “Does he have any medals?” “Medals?” I asked. “Yes, from math Olympiads.” As we talked further, it became clear that winning a medal at your country’s math Olympiad was okay, but really they’d prefer someone who had done well at the International Math Olympiad… Rarified indeed.
Teri Geske is a lecturer and Executive in Residence at the UCLA Anderson MFE Program. She share with QuantNet a few years ago about "Top 10 Things Practitioners Really Want from Financial Engineers". She recently wrote an article on GARP to reflect on what she has observed about the financial engineering programs the last few years. Here is her 5 recommendations for improving quantitative finance programs.
1. Agree on a Name.
Despite its growing acceptance in the financial community, there is still no consensus about what these degrees are called. Does it matter? I believe so. Some schools call the degree a "Master of Financial Engineering" and they call their graduates "Financial Engineers"; others offer a "Master of Computational Finance" or a "Master of Quantitative Finance," and use various acronyms to refer to their graduates. This inconsistent labeling should be fixed, as it would help to improve recognition of, and professional respect for, the degree-holders.
This article appears in QuantNet 2013-2014 International Guide to Programs in Financial Engineering.
The job market for quants has changed inexorably. The “particle finance” trend of the last 20 years is on the wane. While funds will still be able to trade on a prop basis, banks’ ability to do so has been severely restricted.
Some may see this as a pendulum, but most agree that the aggressive trading styles seen in regulated financial institutions will never be seen again.
Does that mean that there are no more jobs for quants? Certainly not. It does mean, however, that the nature of the job market will be different. The growing number of quant finance programs also suggests that there will be much more competition for these jobs.
The following suggestions may be helpful in the job hunt.
QuantNet is proud to announce the release of our second publication
QuantNet 2013-2014 International Guide to Financial Engineering
Our inaugural edition has been an extremely useful companion guide to the field of financial engineering for many students. It has been downloaded over 10,000 times since its debut. The 2013-2014 Guide has many new and updated contents, among them 2013-14 ranking of quantitative finance programs, career advice from top Wall Street executive, etc.
"Big Data" is an important topic these days, not only in finance but also other industries where quantitative skills are in high demand. We have it covered in this guide. You will learn what it means, how to prepare and reinvent yourself for this growing job market.
To share/download the Guide, use quantnet.com/guide
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