*We are the CDO makers,*

*and we are the dreamers of dreams.*

*Betting on lone loss triggers,*

*and trading in eclectic teams.*

*Spread losers and yield forsakers,*

*for whom the pale bonus gleams.*

*Yet we are the sole underwriters,*

*of the deals, forever it seems!*

All over the world, it has become fashionable for Universities and Colleges to offer Masters degree programs in quantitative finance or financial engineering (FE), a code word meaning the solution of the Black-Scholes option pricing differential equation in as many ways as possible. To do so, students are taught to use basic techniques in numerical analysis whenever the equation is either non-linear or does not lend itself to the standard analytical solution. As a precursor to this main task, the program usually includes a course in stochastic calculus during which Ito’s celebrated lemma is discussed, proved and used.

In general, the cost and length of such programs are remarkably similar despite the variability in the quality of the teachers and the brand name of the institution. In many cases the FE program is one of the biggest money makers at the University, if not the biggest, enabling schools to charge somewhere between $25,000 and $35,000 for eighteen months of night classes taught by top professionals in the field. Many such people are in fact refugees from bulge-bracket Wall Street firms looking for something to do before heading out to pasture in Florida and Arizona. In addition to being crassly commercial in their approach to knowledge transfer, often resorting to advertising their own former firm in the classroom, they are willing to accept much less in compensation than full-time professors and never become management headaches to the institution. Even Ivy League schools like Princeton University, who swore up and down they would never play this game, are now happily teaching finance and deriving significant incremental income from a fully depreciated curriculum.

The techniques taught in quantitative finance are completely standard in other fields. In most cases, the only exciting thing about the curriculum is that one day these methods might be applied on Wall Street to the calculation of cash flows. If they were instead applied to the making of widgets or the collection of tomatoes, it is a fair bet that nobody would be interested in them, and certainly no university would be able to charge $35K to learn them. In many other cases, schools with no MBA program have succeeded in manifesting an MBA curriculum out of thin air under the FE banner. At this point, financial engineering does not appear to have any specific meaning, or perhaps it means whatever it takes to get people through the door.

It is a plain fact that the field of quantitative finance has not made a single fundamental step forward over the past twenty years, not to mention that Black himself, by his own admission, had nothing to do with the equation that now bears his illustrious name. The BS equation was first formulated and solved by Casey Sprenkle some ten years before Black’s famous 1973 paper in the Journal of Political Economy. Regrettably, it is still politically incorrect to give due credit to someone who made a real contribution to finance. Unlike those of some of his associates, Black’s reputation hardly hangs on one paper.

Statistics and numerical analysis have nothing to do with finance per se but are merely tools of financial analysis, just like accounting statements and legal opinions. Finance is quantitative by definition; there is thus no need to add an adolescent adjective to the word. This is like saying aerial flight or wet swimming. Although people employed as aerospace engineers use computers on a daily basis, none would describe him- or herself as a computer programmer.

But if this were about mere semantics, it would not be worth mentioning. Unfortunately, FE programs are also drifting farther and farther away from their purported subject matter. In effect, quantitative finance has entered the scholastic stage whereby numerical techniques are taught completely out of context as if a deal were somehow a differential equation that could be solved for the right solution. In fact, there is no solution to a deal as there is to a differential equation. At this point, analysts are talking about investing angels dancing on financial pins. Even worse, professional societies devoted to financial engineering are in reality pressure groups acting on behalf of various financial constituencies, like hedge fund managers seeking to get the regulators off their proverbial backs. Although every American citizen has the right to lobby whomever he pleases, this cannot exactly be described as furthering the field of financial engineering or building esprit de corps among its members.

Students thinking themselves financial experts simply because they can solve the BS equation in a few minutes (there is apparently no other one around) are being misled by their own mentors and teachers into the naïve belief that this amounts to finance. Seminars with magical titles like How I Became a Quant or A Quant Roundtable only serve to perpetuate a myth, the myth that finance is about differential equations or positive definite matrices. Anyone even remotely acquainted with the practice of finance knows full well how far removed such mathematical topics truly are from the real subject matter and the day-to-day bubbling within the cauldron of finance.

A deal only happens when various constituencies (lawyers, investors, bankers, rating agencies sometimes, regulators, accountants, etc.) are able to come together under a unified framework. This is not the time to deliberate or lecture on cross-correlation and conditional VAR. On the contrary, any such talk is completely counter-productive and propagates the negative stereotype commonly attached to those that engage in it to impress or intimidate their neighbors. Rather than repel them, a savvy financial engineer ought to find a way to bring all the parties together, thereby placing him- or herself at the center of the deal instead of its margins. However, this pre-supposes the emergence of a new language better suited to deal making, i.e. not the current one extracted lock, stock and barrel from theoretical physics. To be on a fantastic journey is great only as long as everybody else is on board with you.

Too often, students who would otherwise have something valuable to contribute are being led down the primrose path at the instigation of people for whom this is, at best, a hobby. The promise of high-flying jobs in New York is all that has propped enrollment at its current levels, since once on the job, graduates of financial engineering programs quickly become aware that it is MBA graduates, and not themselves, who are destined to breathe the rarefied air of boardroom deal-making. In fact, the label quant has now become quasi-pejorative, the practical equivalent of geek or inconsequential number-cruncher. Deal-makers do not want such people in front of their clients, if only for fear of hearing naïve prognostications of hetero-scedasticity and Gaussian copula bandied about before befuddled investors (and even before lunch).

Not surprisingly, business school professors often warn their students about not being labeled a quant if they ever want a career in the community of finance. Given the current state of affairs, we could not agree more. Every financial professional worth his salt should be numerate at least to the extent necessary to do his or her own deals, and ideally more. If solving a differential equation is what it takes, then so be it. Unfortunately, it rarely if ever does. Professor Joel Hasbrouck of the Stern School of Business at New York University has posted a rather blunt Power Point presentation entitled Quantitative Finance on the Internet. Despite the obviously self-serving and competitive nature of his remarks, he is largely and sadly correct.

Many students pursuing financial engineering degrees already have technical degrees in other fields and are merely looking to acquire a brand name enabling them to join the party on Wall Street and earn much more than they would in their own field, assuming they would even find a job there. For them, most of the course work in the program is useless or repetitive at best, since they already know what they need to know to perform. Others are liberal arts majors with essentially no background in numerical analysis. They find the program hard and commonly team up with students from the first category to make sure they can do all the assignments. To such students, names like Crank-Nicholson and McCormack easily acquire mythical status, being by definition the way to solve the BS equation numerically. They have no way to gauge whether these are just two methods among many or the pure, unadulterated truth.

In some cases, students are blindly taught to use techniques that only work because the BS equation is parabolic. The course assignments we have looked at are remarkably commercial in intent and mainly serve to stifle basic creativity by intimating, for instance, that what Risk Metrics (a commercial vendor of analytical services) does is the right way to model credit or market risk. This is thoroughly and sleazily transparent, anti-intellectual and only fosters cynicism in the student body when it is perfectly clear that there is no such thing as a right answer in finance, unless by that term one trivially means that no logical mistakes have been made.

What is obvious and regrettable is that no effort is ever made to teach numerical analysis as a proper and rigorous discipline. Instead, students literally learn numerical recipes and are no more equipped to handle reality than someone equipped with a driver’s license when their breaks down. One also gets the disturbing feeling that the majority of teachers involved in quantitative finance have limited knowledge of either finance or of the elements of numerical analysis. Unfortunately, too many professors in that field are there for the same reason that the school can charge enormous tuition fees, i.e. they can earn much more for teaching the same material in finance than they would in the original field. It’s hard to turn down $150,000 for teaching either statistics or the numerical solution of partial differential equations on a full-time basis when your equally competent buddies from graduate school are doing the same thing elsewhere for $50,000.

Although we freely admit that we have not performed the monumental task of a complete inventory and comparative analysis of financial engineering curricula, a cursory review of the most popular ones reveals what seems to be their central dilemma, which is how to fill 18 months of teaching with a single topic: stochastic calculus and its applications. The general answer appears to be to fill the remaining 14 months or so with subsidiary material peripheral to finance but available for much less elsewhere. Here, the main target is numerical analysis. In the latter domain, although students are taught a few useful techniques, the elements of numerical analysis are not addressed, perhaps because this would take up too much time and force the school to hire teachers who would demand higher pay and thus decrease yields.

The upshot is that the curriculum is always sitting between chairs but never on any one of them. One meanders across finance discussing swaps, default swaps and various options (instruments that hardly require Herculean intellectual prowess to grasp), engages in endless and meaningless debates on the eigenvalues of correlation matrices, and then dabbles in numerical analysis by learning basic methods applied to the BS equation taken as the last word in finance for the remainder of mankind’s existence. At no time, as far as we can tell, are students taught how to construct a numerical method from scratch or how to tell if it will work or fail.

Throughout our Internet search, the following topics were absent from the syllabi of the numerical analysis courses within the financial engineering curricula of the academic institutions we reviewed:

1. Z-transforms and Laplace transforms 2. Banach and Sobolev spaces 3. Fourier series and transforms (one exception) 4. Lax equivalence theorem (same exception) 5. Von Neumann stability analysis 6. Courant-Friedrichs-Loewy (CFL) condition 7. The Nyquist sampling theorem (useful in Fourier analysis) 8. Convergence analysis 9. Error propagation analysis 10. The Weierstrass approximation theorem 11. The interplay between truncation and discretization error

It is simply not possible to claim expertise in numerical analysis if one does not have at least a passing acquaintance with the above foundational elements. However, learning these things takes time. On the other hand, if the goal is not to become knowledgeable in numerical analysis but simply to learn a sundry assortment of basic methods, there are much cheaper ways to do this, for instance in the mathematics or computer science department of the same school. Numerical analysis is a well-formed discipline that does not need finance to give it credibility.

The consequence of all this is that today, and through no fault of their own, students with degrees in financial engineering are ill-equipped to face the rapidly changing face of finance. Once ensconced in their jobs, they are quickly marginalized and relegated to the role of glorified programmer until being eliminated in the next headcount reduction because (with unfortunate justification) they are not considered producers.

It would be a different matter if financial engineering were just a code word for numerical analysis with finance used as a marketing mechanism to attract people to the field. It would be equally acceptable if financial engineering were devoted to the actual practice of finance instead of being largely an obsession with one equation, no matter how interesting it might be. Someone who has never done an actual deal can hardly be expected to know how deals are done, let alone teach how to do them. Likewise, a manager who used to supervise twenty-five Ph.D.s in some research department on Wall Street has as much knowledge about deal making as an usher at Yankee Stadium has about baseball. On the contrary, it has become painfully obvious that these managers, if the term can be used at all to describe this level of incompetence, are precisely the people who truly need supervision instead of underlings who, at bottom, never make a single decision that could take their firm down.

Financial engineering never grew up within finance; it was taken over by physics. This is not surprising given that the same thing happened to economics 100 years ago. Unless the field re-invents itself pronto and starts becoming relevant to what people actually do out there, graduates with newly minted financial engineering degrees hoping to see a decent return on their own or their parents’ sizable investment will continue to be sorely disappointed by their actual career prospects, and will keep wondering where in God’s name they went wrong.Regrettably, the answer is: nowhere.

Originally published at The Spectrum and reproduced here with the author’s permission.

Great article

Where is this powerpoint “Damn Quantitative Finance” ? Google can’t find it.

I can’t find it either!

A version of the presentation hosted by our website is available for download here.All of our multimedia material can be accessed on the blog section of R&R’s website.

Very interesting article, Sylvain. I do think that you gave FE more lashes than it deserved, but you did touch on some of the major issues.I just finished a degree with the intention on going into FE but during the course of my studies changed my plan to one in Economics instead, mainly for two reasons. Like you alluded to, I found that there was way too much math and programming involved in the FE program, after-all it’s supposed to be Finance, albeit engineering. [But your raising the fact that it does focus on a sole aspect of math and touches little on the other areas seems to show one of the short comings of the program.] And secondly, I just had a greater appreciation and interest in Economics instead. The narrow career path, again, albeit one that’s more specialized, is also very limiting with this program.

Financial engineering seems to be a little like counterfeiting, a painstaking task born of greed and an attempt to fool the public, only it was embraced by our financial system and became much more rewarding. It might of worked better with the help of a moral compass.

Spot on..but the author has a tone of snobbish resentment in the piece, which he holds against the academic institutions.True, the practice of finance is not the same as “Science”, though it draws so many from Science(/and engineering). For one thing the practice of quant. finance is RIDDLED WITH SECRECY AND OBFUSCATION! Once a fancy product comes into the hands of an Investment Bank, where are the PEER REVIEWS, the DISSEMINATION OF METHODS / RESULTS and DEBATE? NOPE…it becomes more like a fancy suit worn to cover up a very shallow and venal GREED, presided over by boardroom types who could care less other than for ROI.Absolutely True, that there is no such thing as a right answer in finance and YET, here we are at the start of a depression because quants can PREDICT the likelihood and depth of default of a firm (CDS). If that aint angels dancing on pins then WHAT IS? and how much were those people paid??? all sheer RUBBISH! Let’s BURY FE, and have the FE’s designing hearing aids or sattelite communication systems, cause those things ARE REAL SCIENCE…the results are repeatable, and methods TRANSPARENT.

Wow! I agree with the article, wholeheartedly. As a former quant, and now a trader, I can attest to the fact that the quants back stage have no clue about what happens on a trading desk. They play an important role though, and it is hard for me to understand why those FE programs don’t try to do a better job of teaching the two sides of the coin. One way for such education is through a good old MBA with quantitative electives.

Agreed also with the comments. It is nice to see these remarks beeing expressed at last. The maths are only the tool, first understand your problem, feel the rationale behind it, make sure you did grasp its economics and the psychological aspect then worry about the tools to solve your problem. And anyway there will be a lot of approximations to your specific issue for which you will plainly measure risks vs rewards….BTW: could someone post back the presentation DAMN QUANTITATIVE FINANCE

It is regrettable that a generation of sharp minds was lured into Quant only to be followed by the masses looking for easy quick books. Another malinvestment on a scale heretofore not seen.Folks now know the capital markets were a casino with probably about the same odds as the craps table.Academia is a business and is anti-competitive. Try transferring credits. The last thing it is about is education at a majority of institutions, public or private.FE programs taught by adjuncts is a high margin business just as law schools are.Deflation will come to academia, too. The debt that has been taken out for dubious credentials is mind boggling.So a great piece!

This is a work of art. Fully agree with what you wrote, from a to z.

Since Mr. Raynes teaches Structured Finance in a MFE I wonder if his analysis of other financial engineering curricula is simply a plug for the school at which he teaches.

Please read Dr. Raynes’ follow-up post, “The Answer is the Question, the Question is the Deal” on The Spectrum, the official blog for R&R Consulting and the original source of this article.

What the hell, we have gamers on this site now too?It appears to me that the Wall Street didnt want the Financial Engineers to inderstand things like the need for a downside put in the equation in order to adequately addresss the mortgage securities and their derivitive’s risk.Wall street supplied the jobs, academia (sp?) supplied the workers exactly the way Wall Street wanted them. Bean crunchers being what they are only crunch the numbers that the power brokers want to be seen. These jobs will dry up just like all the rest vapourizing into nothingness just like so much of the wealth that many thought they had but instead turned out to be elusive.As another blogger wrote:We might as well commit hari-kari sooner than later. The alternative is to go on living in this Alice-in-Wonderland chaos having to think like Keynes, then Marx, then Dali…

Seems to happen in many fields. There are people who are good at math & figure out a way to prove some theorems vaguely mapped to an oversimplified abstraction of a problem in the field. Since one can publish a lot of papers based on mathematical perturbations of the same idea, you see the field descending into …complete and utter math-turbation

Good article. I agree with the author in many points, especially the the huge gap between math tool box and financial reality at work. As a product of FE program myself, I think what is lack in FE program (at least the one I came out of) is lack of training on financial common sense. We are so blurred by all the fancy math and equations and forget that the very most fundamental thing in finance is making money at given degree of perceived risk. The problem is that risks are not distributed correctly (moral hazard problems) and not symmetrically ‘perceived'(psychology). With these problems, even well-calculated numbers from well-defined models do not work, because the market behaves differently than the underlying assumptions.

The author used to be a quant, was never a deal maker, and is really bitter! The top FE programs have senior people with far more successful careers than Mr. Raynes on their steering boards. There is some truth in the article, but there is a lot more BS. The numerical stuff he mentions is irrelevant in most areas. The author also seem to have no clue of how things work in other places (eg London), where many traders, sales, and people working in global markets have technical degrees.Gee, what a loser…

I am actually a professor teaching FE at a top school. I happen to have degrees in physics, math, and finance.The article clearly shows that the author has never been “Within” an FE program, as he/she has very little idea of how FE programs are run and what various constraints are (for one, often FE courses are jointly offered to MBA students with absolutely no math background).1. Z-transforms and Laplace transforms 2. Banach and Sobolev spaces 3. Fourier series and transforms (one exception) 4. Lax equivalence theorem (same exception) 5. Von Neumann stability analysis 6. Courant-Friedrichs-Loewy (CFL) condition 7. The Nyquist sampling theorem (useful in Fourier analysis) 8. Convergence analysis 9. Error propagation analysis 10. The Weierstrass approximation theorem 11. The interplay between truncation and discretization errorRegarding the above, I think we have to be realistic that FE programs are mostly a master degree program. How many PH.D. students in numerical analysis can comfortably say that they can pass a qualification on the above topics on the next day?

Here is what I have to say –Firstly he is trying to point out the disconnect between whats taught in schools/graduate programs and what happens in the real world. That’s not only true for FE program but for any other graduate study program. What do MBAs do in real life in companies you think? Do they go and start developing company strategy from day one? No..any education degree allows you to just get started in the right direction, it’s a pre-requisite, it tells people that you are interested in pursuing that field. Then its upto each individual to find his or her way in the organization. You need to develop management skills to go up the ladder. The same way, its up to any FE graduate to understand the connections between his or her day to day work with the rest of the company or the deal making that this professor is talking about..Always make sure that you know the bigger picture, what is the final outcome of the small task that you are working on..And also keep learning new skills..Secondly, he is able to talk about it so openly now because of the environment, the credit crisis. Read his reply to some of the comments – he states he wrote the article 4 years earlier but published it now..Everyone wants to criticize when things are going bad..thats just human nature…2 years down the line you will see different comments about the usefulness of FE course.I don’t want you to feel discouraged by this article. It’s a very interesting thought and something to keep in mind as you study now and later work..but always remember you have control over your career. You can decide which direction to move in. The FE course is just to get your foot in the door, hopefully in one of the better doors out there but finally its up to you how far you want to go..

Here is what I have to say –Firstly he is trying to point out the disconnect between whats taught in schools/graduate programs and what happens in the real world. That’s not only true for FE program but for any other graduate study program. What do MBAs do in real life in companies you think? Do they go and start developing company strategy from day one? No..any education degree allows you to just get started in the right direction, it’s a pre-requisite, it tells people that you are interested in pursuing that field. Then its upto each individual to find his or her way in the organization. You need to develop management skills to go up the ladder. The same way, its up to any FE graduate to understand the connections between his or her day to day work with the rest of the company or the deal making that this professor is talking about..Always make sure that you know the bigger picture, what is the final outcome of the small task that you are working on..And also keep learning new skills..Secondly, he is able to talk about it so openly now because of the environment, the credit crisis. Read his reply to some of the comments – he states he wrote the article 4 years earlier but published it now..Everyone wants to criticize when things are going bad..thats just human nature…2 years down the line you will see different comments about the usefulness of FE course.I don’t want you to feel discouraged by this article. It’s a very interesting thought and something to keep in mind as you study now and later work..but always remember you have control over your career. You can decide which direction to move in. The FE course is just to get your foot in the door, hopefully in one of the better doors out there but finally its up to you how far you want to go..