Future of Financial Mathematics?

An anonymous reader writes "Nassim Nicholas Taleb, a famous 'Quant,' has long been a strong critic of the use of mathematics and statistics in the financial markets. He has been very vocal in his books The Black Swan and Fooled by Randomness. In his article on edge.org, he says 'My outrage is aimed at the scientist-charlatan putting society at risk using statistical methods. This is similar to iatrogenics, the study of the doctor putting the patient at risk.' After the recent financial crisis, wired.com ran an article titled 'Recipe for Disaster: The Formula That Killed Wall Street' in which the quant David Li and his Gaussian Copula were crucified — we discussed it at the time. Now, I've recently been admitted to a graduate program of good repute in Computational & Applied Mathematics. There is a wide range of subjects in which you can pursue your PhD, one of them being Financial Mathematics. I had a passing interest in it for quite some time. In the current scenario, how advisable it is to pursue a PhD in this topic? What would my options be five years down the line? Will the so-called 'quants' still be wanted by the banks and other financial institutions, or will they turn to more 'non-math' approaches? Would I be better off specializing in less volatile areas of Applied Mathematics? In short, what is the future of Financial Mathematics in light of the current financial crisis?"

Comments

It will always be risky

[Tamran]

... given that people want to see subjective numbers. See:

http://www.amazon.ca/How-Lie-Statistics-Darrell-Huff/dp/0393310728

Advice from a PhD student

[chillax137]

Don't pick your research area based on profitability or popularity. There are always "hot" areas of research but these things are usually cyclic. Pick something interesting that excites you, and that you can spend the next 4 (or 5 or 6 or 7) years working on.

Re:Advice from a PhD student

[Narpak]

or the next twenty-forty-sixty years for that matter. Depending on how long you live or when Cthulhu raises from the sea.

Re:Advice from a PhD student

[averner]

Don't pick your research area based on profitability or popularity. There are always "hot" areas of research but these things are usually cyclic. Pick something interesting that excites you, and that you can spend the next 4 (or 5 or 6 or 7) years working on.

There's another reason for this: if you find something interesting to do, it also helps with motivation, and you'll end up doing better in it. Succeeding in a highly competitive field is almost always better than doing average in a field for which there is a lot of demand.

Re:Advice from a PhD student

[Ruie]

Don't pick your research area based on profitability or popularity. There are always "hot" areas of research but these things are usually cyclic. Pick something interesting that excites you, and that you can spend the next 4 (or 5 or 6 or 7) years working on.

I generally agree with this. I would like to add a few more points from personal experience:

• Financial mathematics booms when hedge funds or similar businesses proliferate. I remember financial mathematics being depressed after LTCP blew up, then went up again.
• One trend you should be concerned about is proliferation of computing power. What used to be done with approximate equations is more often than not is done with over-complicated Monte-Carlo simulations (whether they are warranted or not). These usually are hard to get statistically meaningful, so statistics is ignored as well. There will still be demand from people that think because you have a Ph.D. you just might come up with something useful (and are willing to spend $10-50k just in case), but if you do achieve anything it won't be because of Ph.D. level math.
• However, it does pay to be familiar with terminology and current trends. Find a few applied areas and get familiar with what they do and how they talk about it.

Re:Advice from a PhD student

[PopeRatzo]

Listen to chillax137, he's got it right.

My wife's a mathematician researcher. She's remarked to me several times lately that some of the big financial outfits have been picking people from the non-financial math areas, such as fluid dynamics, predictive analytics, combinatorics, etc.

They're looking for sharp, dynamic people more than a particular course of study or area of research. The secret is out that a lot of second-tier mathematicians went into financial math because they thought that would be their ticket to vast wealth and like a famous capitalist said, "First you get the money, and then you get the power, and then you get the woman."* In the current environment, people who strive to get a certain type of degree because they think it's going to make them rich are not so eagerly sought.

My first rule of preparation for career advancement: Don't learn how to do anything that you don't want to be doing. I figured that out long ago when I was trying to learn how to program SQL during a time when I was sick of my job. One night I realized that I would hate programming SQL all day, so I dropped it and put that energy into the stuff that I find fun.

Re:Advice from a PhD student

[Meneguzzi]

Besides that, one thing you will have to have in mind is that you are expected to create novel research in the area, so going into a "hot" area also means that there will be a lot of people doing research in the same area, putting you in a position where it is very likely that someone will scoop your research, or more precisely, creating the thing you thought was brilliant and original before you. So not only you may end up doing research on an area you hate, but the novel thing you thought you had might not be novel anymore by the time you have to defend your thesis.

Re:Advice from a PhD student

[urbanRealist]

I have a master's degree in financial math. I currently write software used to value structured financial transactions such as mortgage backed securities. I am over qualified for my job, but one of very few people in the world that is not under qualified for it.

So I second Ruie. Get the degree, people will realize you know something useful, but don't be surprised when you don't really utilize everything you learned in school during the course of your career.

A bit self-defeating

[russotto]

Reading up on the Wikipedia article on this guy...

"Taleb appeared to be vindicated against statisticians in 2008, as he reportedly made a multi-million dollar fortune during the Financial crisis of 2007-2008, a crisis which he attributed to the failure of statistical methods in finance "

But his thesis is that such events are fundamentally unpredictable. If he made a fortune, it means _he_ was able to predict it, well enough to profit for it. Which argues not that the events are unpredictable, but rather that his model is better.

Re:A bit self-defeating

[Jane Q. Public]

Distortions in the market, like over-leveraged corporations and too many risky investments hanging out, tends to make things predictable. After all, if you KNOW that the market for some commodity is over-priced, then you KNOW that sooner or later there will be a "market correction".

By and large, though, markets are unpredictable, and they need to stay that way. If markets were predictable, they would cease to exist... some one or a few would run off with all the money. To the extent that it has been "predictable" and made some corporations lots of money recently... as we have seen, that was largely due to manipulation and corruption, not the effects of free markets.

Re:A bit self-defeating

[maxume]

He believes that they are inevitable and uses strategies that work well during them and are mediocre the rest of the time. That doesn't mean he knows when they are going to happen, or what they are going to look like.

Re:A bit self-defeating

[the_other_chewey]

But his thesis is that such events are fundamentally unpredictable. If he made a fortune, it means _he_ was able to predict it, well enough to profit for it.

No. His "system" is indeed based on the assumption that such events are unpredictable. That's why he for years bet
simultaneously on a sharp increase and a sharp decrease in stock values - and ran slight daily losses, in the
anticipation and expectation that once such an event inevitably happens, the profits will more than make up for those
losses.

It worked.

He basically had no idea - and didn't care too much - when this (and what this "this" would be) would happen though.

Re:A bit self-defeating

[peragrin]

Actually markets are very predictable. every 10 years they go boom. Which part goes boom is varies but every ten years since Nixon they go boom.

The trick is that wall street likes unlimited growth. if you don't expand your business by 10% every year then you are a failure and your company should be punished. After 10 years at 10% growth you have over saturated the market by 100% and every company that got there with unstable books and balances collapses.

I forget exactly who and when but a walmart exec once stated. If we stop building new Walmarts we will go bankrupt. As they leveraged one walmart to build the next in a terrible endless pyramid scheme. Once the bottom bursts there is nothing holding up the top.

Indeed if you look closely to all the news reports on what happened to the banks that is exactly what happened. 5% failure of loans should be expected. However a handful of banks ended up holding that entire 5% as their portfolio. As they collapsed the rest of the banks were suddenly forced to cover them, and since they over extended themselves by laying off bad loans on a small group the rest of the banks couldn't take the weight.

the housing market the past 8 years was the same way. You can't have massive growth without massive contraction.

The dot com burst. was the same. unparalleled growth but questionable accounting.

Oh and I saw the housing market ready to burst 18 months ahead of time. Just look for massive growth over 5 years in any given market. a Seller's market for a long enough time leads to collapse. timing exactly when is the trick.

Re:A bit self-defeating

[BlackSabbath]

By and large, though, markets are unpredictable, and they need to stay that way. If markets were predictable, they would cease to exist... some one or a few would run off with all the money. To the extent that it has been "predictable" and made some corporations lots of money recently... as we have seen, that was largely due to manipulation and corruption, not the effects of free markets.

A few have run off with all the money. Who was on the other side of those massively leveraged positions that the banks lost on? It seems to me that the fact the losers are now being bailed out by the government means that effectively there has been a massive transfer of wealth from taxpayers to the "winners" of those bets.

Manipulated, corrupt and un-free markets indeed.

My suggestion to the submitter is to try a more honorable career, like record-company executive or drug-dealer.

Re:A bit self-defeating

[DriedClexler]

Unfortunately, you can only exploit your knowledge that X is overpriced, if you also know *when* the correction will occur (or you already own X, in which case you can sell). Otherwise, you'll end up bankrupting yourself by being stuck in a "short squeeze"[1] or buying worthless puts.

IMHO, the problem is not the risk; it's the coupling. That is, if everyone actually bore the full cost of their investment, and knew all of the ultimate counterparties, then it wouldn't be possible for one screwup to cascade to the entire system. If some investment lost, the direct investors would be out money that they themselves put up, and maybe those who lend them the money. It wouldn't be a complex web of leverage on top of unknown leverage on top of unknown leverage, all hidden in "safe" savings accounts.

[1] that's when your short-sell X -- borrow it and sell it -- and then it rises too much, forcing you to close out your position unfavorably.

Re:A bit self-defeating

[CompSciStud4U]

I would suggest reading The Black Swan. His basic thesis is that the gaussian methods used to calculate risk in financial markets underestimate the risk by several orders of magnitude. Crashes that happen every couple of decades are considered to be once in a million year occurrences by these methods. He made his money in the crash by betting against this. He assumes that he has no clue when a crash will happen, only that the risk is much greater than the vast majority of the market thinks. Everybody else thinks it will never happen, overextend themselves, and when the crash comes he takes their money. He did it in the 80's too.

Re:A bit self-defeating

[Bigjeff5]

It wasn't so much the 5% failure rate that was the problem. That and probably more was expected. It was the fact that when those loans failed, they could not be recovered because house values had actually slipped in a lot of places - that had never happened before on any kind of wide scale. But you're right that it could be predicted, and I'd expect your formula for predicting a market collapse of some kind is probably pretty acurrate in a general "rule of thumb" sense.

This housing market collapse was predicted over a decade ago. The recipe for disaster was there, the only question was exactly how long it would take.

Heavy-handed incetives to take risky loans that were first implemented 20 some-odd years ago, but greatly ramped up by the Clinton administration, created a climate where it was quite profitable to take on bad loans, and then shift, move, and otherwise hide that they were bad. The housing market itself was able to hide the risk of taking on so much bad debt, for as long as house values went up faster than interest rates, even extremely high risk loans (like fixed payment loans, and second and third mortgages) would almost always be covered when a house was sold. Homeowners who can't pay their bill just sell, banks get their money back, and nobody loses. Even when forclosure was necessary banks could reliably recoup most of their money, though forclosure is less than ideal.

However, as soon as housing prices stagnated the model became tenuous, and when it slipped, even a little, the model collapsed. You ended up with thousands of loans that could not be covered by the sale of the home, and forclosure was the only option.

This is BAD. Forclosures are expensive anyway, and only cover the balance left on the house for the initial bank, the secondary balance if there is one, or the homeowner if there isn't gets what's left. Forclosures that can't even get the primary loan balance back are a financial nightmare. What's more, the homeowners that tended to default were also more likely to get second and third mortgages to stave off forclosure. Houses went from being "guaranteed income" for banks to a massive liability. Companies like CountryWide - which embraced the Government's high-risk low income loans and who either Fannie May or Freddie Mac, I don't remember which, touted as the "model" for lending - was the first company to fail (no bailout for you! too bad so sad!). AIG, by the way, profited by shifting the risk of these loans via a special insurance type. Obviously that worked out well for them.

I personally think the healthiest thing to do would have been to let the market collapse and allow other companies to fill the voids. Definitely more painful in the short term, but in the long term I think it would be better. We'll be suffering for a long time with the current bailout plan. Though of course, I'm no economist, but they haven't done so hot anyway so...

Re:A bit self-defeating

[ChrisMaple]

Having recently read Black Swan, I can say with confidence that his main thesis is that the Gaussian distribution (bell curve) does not match much of reality, including the markets. Late in the book he says (without much clarity or any details) that his technique is to bet on changes being larger than most people think they will be, rather than betting that changes will be in any particular direction.
Taleb undercuts his arguments by disparaging those he disagrees with and using ten paragraphs when one would suffice.

Re:A bit self-defeating

[jstott]

No. His "system" is indeed based on the assumption that such events are unpredictable.

His system is basically arbitrage. We have an algorithm for pricing options (Black-Scholes) that makes an invalid assumption (it uses Gaussian statistics where it shouldn't). This fault was recognized almost as soon as it was published, but people continue to use it anyway, which means they're mis-pricing their options. Black Swan makes money in the long haul because they know big price swings occur more often than the options are priced for, and they buy based on this knowledge. Exploiting market mis-pricings like this one is the essence of arbitrage.

Like classic arbitrage, this only works because a) there is a mismatch between price and real cost [risk] and b) there aren't a lot of players making the same purchase. Change either A or B and Black Swan's strategy will become a money-loser, or at least a break-even.

-JS

Re:A bit self-defeating

[TheLink]

Any evidence that he isn't just like one of those lottery winners?

The losers don't get much press. Once in a while someone wins big and everyone wants to know how that person did it.

Even if there's a good reason why that person is "winning", often that person might not even be able to tell you how to replicate the success (he certainly can tell you lots of stuff, but that's not the same thing :) ). Apparently there's a finance guy who sells when his back hurts - and it works pretty well. His mind probably gathers various info from all sorts of sources processes it, when it's bad he gets more stressed and he gets back pain.

Warren Buffet does appear to have a consistent track record and his method does appear to make sense.

I know someone in the finance industry and he says what he really does is transfer money from the stupid to the smart (himself ), and it's not about "making more efficient markets", "providing liquidity" and all that bullshit. He says the difference with him is at least he's honest about it ( at least to some people :) ). He's pretty savvy, and can quickly work out if a casino has screwed up with a game/system. The trouble with casinos is they don't welcome players who make too much - if they find out that you're making too much, they'll never let you in again - even if you win legitimately. In contrast the financial markets welcome players who keep winning big.

Call me cynical but in my opinion all the "fancy math and investment strategies"[1] are the equivalent of smoke and mirrors magicians use to hide what they are really doing.

Think about it - what is actually happening if a bunch of people keep trading stuff amongst each other till things end up priced many times their original value, while they collect a commission per transaction (and a even bonus in some cases)? Where's the money really going?

If you really believe that sort of thing helps make the market more efficient, then there's someone out there who would like to sell you a "High Grade Structured Enhanced Leveraged Bridging Fund".

[1] Don't get me wrong - non-fancy math and strategies are OK. When it comes to investment, the fancier the math, the more likely it is to be BS.

I'm more interested in the governance than in math

[fuzzyfuzzyfungus]

As long as it is possible to get paid for the short term results of your crazy bets with other people's money, it barely matters whether the math actually works or not, you are fucked either way.

While I'm all for good mathematical modeling, the notion that our financial problems are caused by bad math is a distraction at best.

Quant != Finance Phd

[Sprogga]

There will always be a quant element in finance. I'd guess there will be fewer quants in five years than there were in (say) 2007, but there was definitely an over-supply then. Having said that, most quant jobs don't require you to have had specific training in finance or financial mathematics. For the best firms, its much more about your mathematical and programming abilities. So you definitely don't need to specialize now in finance to become a quant. You could make a case that focusing on AI would be a bigger draw with quant firms. The other advantage of not doing finance now is that it gives you five years to think about whether you want to be in a career where when you get down to it, you rent out your brain to rich people so that they can get richer. I do work as a quant and find it interesting and competitive etc, but ultimately its a money thaang.

Re:Quant != Finance Phd

[mithras the prophet]

Though arguably this is precisely the root of the problem. As the post above you mentions, many quants build their software around nonparametric statistics or statistical (machine) learning, without deeply understanding the domain. This can lead to an over-reliance on historical data, which in turn leads to a failure to predict rare but significant events, like, say, the current crisis. Now, I'm totally unqualified to pronounce that if only we'd had more quants who richly understood finance and economics we could have avoided the worst of current events. But I'm aware that there are those who make that claim...

What's more important money or ...

[blahplusplus]

... your passion? Are you the kind of person that gets bored even about things you are passionat about? You can study something if you believe it will bring you more money in the future.

What people don't understand is you can LEARN to love doing something by looking at it from another perspective - i.e. take joy in solving problems and strategizing in general and then it shouldn't matter what 'speciality' you go into specifically.

The real problem with algorithmic trading...

[thesandbender]

I have worked with companies that implement and use "algorithmic" trading. The real problem is that algorithmic trading doesn't try to beat the market... it tries to beat other algorithmic traders. The idea is to get the trades in before anyone else and there is only so much analysis you can do in a given period of time. Honestly, there's no real analysis to it... it's snap judgments based off a few dozen indicators. It's the equivalent of saying you should guess all C's on standardized tests. On average it works... but you should be shooting for better than average.

Re:If you enjoy it ...

[Anonymous Coward]

As a former Wall Street trader turned academic, I can agree that the demand will continue to grow for financial mathematicians. The "old school" trader is a former ivy-league athlete who is good at networking and teamwork, but can't do a lick of math. The D.E. Shaw's and hedge funds are crushing the "old school" traders as trading becomes more about speed (esp. algorithmic trading) and liquidity and less about connections. The large banks still have plenty that follow the old mindset, but they are slowly being replaced by the more successful "quant" traders. Granted, the current crisis was caused by over-reliance on models, but that happened because most traders and managers did not understand the models and their limitations. To rectify that, there will be an even greater need for those trained in financial mathematics.

A couple of things....

[gadders]

1) Taleb has a bit of the stopped clock quality about him. Anyone saying "bad things will happen" is bound to be right sooner or later. Plus, his writing is the most self-indulgent wankfest ever.

2) I don't know whether you will choose financial maths or not, but Banks will always need people that can do "fancy" maths. Although some maths is out of favour, high-frequency (algo) trading is currently still popular, and making money.

Mathematician Becomes Defense Secretary of the USA

[reporter]

If you love financial mathematics, then you should definitely study that subject. Do what you love. Life is short. Enjoy your time on earth.

Do not be concerned about "restricting" your future options. The applied mathematics in financial mathematics involves all areas of probability, random variables, and stochastic processes. These topics in applied mathematics have wide application in many diverse areas: digital image processing, gambling (e. g., card-counting techniques in the casinos of Las Vegas), computer simulations of warfare outcomes, etc. A degree in financial mathematics will enable you to work in many fields outside finance.

Mathematics, in general, does not restrict anyone's options -- if you are smart and hardworking. Just ask William Perry. He received graduate degrees in "only" mathematics and eventually became Secretary of Defense of the United States. His most recent accomplishment was authoring an essay published in "The Washington Post". In the essay, he advocates using military force to destroy North-Korean military facilities. Mr. Perry is a smart person with the right solution for dealing with North Korea.

use math to choose

[Zecheus]

If math can be used to tell us which stocks/companies will profit, can't math also tell you which outcome is best for you?

Population statistics should just be scrapped

[viking80]

In quantum mechanics, you use statistical models because that is the true nature of the underlying physics. In financial analysis, you do not need to use statistics. A borrower ability to pay monthly payments is not some unknown quantum state, but well known (at least to himself or his employer)

It is a fallacy to estimate risk in lending and then charge interest based on this risk. All borrowers that pay on time should get the best rate and those who don't just should be denied the loan.

The only reason not to do this, is lack of information or lack of computing power.

With fast computers and good data all population statistical analysis should be thrown out, and replaced with calculation for each individual and then integrated. This will replace the entire field of mathematics from insurance to lending and investing.

Re:Mathematician Becomes Defense Secretary of the

[PopeRatzo]

Do what you love. Life is short. Enjoy your time on earth.

And for god's sake, smoke weed.

Everything is better with a bag of weed.

Re:Mathematician Becomes Defense Secretary of the

[martin-boundary]

WTF? How did you get from studying mathematics to nuking North Korea? That was beautiful old-skool trolling, man :)

Please don't do it...

[mario_grgic]

Studying math with some concrete career in mind is like marrying for money.

If you are going to study math, study it for the love of it, and your own soul.

Your degree will prove useful to you in what ever career you choose for yourself later.

A perfect subject..

[meburke]

..for a Ph.D. thesis? How can Mathematics be applied to safely invest without damaging Society?

Well, first, NNT is "outraged" at the "inappropriate use" of Quantitative Analysis (according to his books and the articles I've read), not the "utility" of Quantitative Analysis. The reality is that investments' values fluctuate. The role of the Mathematician is to limit the losses, therefore the risks, involved in investing. This is a legitimate role. If you had been working for 45 years and were about to retire, wouldn't you want to know that your retirement funds were as safe as they could be?

Part of the problem comes from the fact that investment value is affected by information other than the worthiness of the investment. This value activity has created an analytical branch of its own, and subsequent buy and sell orders are based on the activity rather than the underlying fundamentals. NNT's argument in "The Black Swan" is based on the idea that since these random events are indeed "random", by definition they are unknowable, unpredictable and un-assessable. So, when these events occur, no contingency plan behaves correctly. Keep in mind, that this is only a problem if the event(s) affect the investment values, or the perception of investment values, in a negative way. Unfortunately, the use of these QA tools creates an aberration in perception, and may be creating it's own perception, and this "perception" may not conform to "reality", therefore leading to aberrant behavior based on an aberrant strategy. (Oooh, the stock market has become psychotic...) Skynet takes over the market and tries to wipe out the humans because its programming tells it that is what humans want.

Mathematics can tell us a lot about what reality "is", and there is a lot of room for a creative Mathematician to alleviate the downside and limits of financial decision-making. I say, if you like Math and this is an area that interests you, go for it. Try to be the best. Be creative and innovative instead of being a sheep.

Malcolm Gladwell's book, "Outliers" deals with somewhat the same problem in a different domain, and Ayers, "Super Crunchers" gives a good layman's view of how well Math can work for us in certain areas. Graham and Dodd, "Portfolio Analysis" may still be the best overall book touching on your field. Benjamin Graham's, "The Intelligent Investor" may still be the best basic investment book. If you want to get out there a little ways, try Prector's, "The Elliott Wave Theory." I had a friend working at Lockheed in Artificial Intelligence, who was responsible for the computer analysis of the market for Prector's newsletter. Every year they would run a 3-month test of the application, and it would consistently make money well in excess of the inflation rate (even in '89). It's been 15 years since I talked to him, and I have no idea how well it's done in the last few years, but the field seems fascinating.

I say go for it, and good luck!

Re:Monte Carlo, we should have known.

[hoytak]

Yeah, well, there's no reason to be troubled there. Monte Carlo is great, and great in this situation, because it expands the possible models that people can work with, and if done with any intelligence will give reliable answers and error bounds on those answers. Throw Monte Carlo out the window, and you're back to conjugate distributions and low dimensional models that have far more restrictive and unrealistic assumptions.

Run, don't walk, away

[rbrander]

There was an article in Maclean's (our Newsweek) about a pure-science institute having trouble recruiting in the 90's and 00's because "an entire generation of physicists, chemists and biologists went into Finance instead".

The "quant" maths haven't been proven wrong, exactly; whether heavy mathematical analysis and modelling can make markets more efficient and lower-friction is a separate question from the morals of those managing them.

The trouble is, baroque complexity of financial instruments and transactions was the primary concealment tool that allowed all the lying in the first place - lying to other institutions, to regulators, and certainly to the public that handed over all their dough at low interest because the institutions were so guaranteed-safe; and I suspect, they managed to lie to themselves. Models - especially complex ones with many parameters - have a way of reflecting all the prejudices of (and pressures on) the developers. A big part of the scientific method is about systematically counteracting that. There is way less pressure to counteract if you are not working for open publication after a rigorous peer-review. If your models will be strictest trade secrets, however, your only reviewer is your boss - who may personally become hugely wealthy if the model says X, and not much, if it says Y. Science (as in, "the search for truth") suffers.

If nobody, for a generation or two, will trust an institution with opaquely complex business methods, the market for quants is going to stay "plummeted" for a long time. (It has already plummeted because of the contraction in the whole finance industry - I presume you are even asking about this career only because you think there will again be some job openings in 4 years when you complete a degree.)

I think even 4 years from now, there will still be surplus quants littering the weak market; resumes in the hundreds will flood in for openings.

So, stay away from THAT career, job-wise. There's a crying need for physicists, chemists, and biologists.

I'd go further to say

[Sycraft-fu]

Don't go getting a masters or PhD if money is the objective. I see WAY too many people who are just hoop jumpers. They are going on to get a higher degree to get a better job. Some of these people get their PhD and then do post doc work not because there's still research they want to do but because they still can't get the job they want. Never occurs to them maybe education isn't the problem, it might be their complete lack of problem solving skills or the like.

A masters and more so PhD are NOT for everyone, they are not even for most people. They are supposed to be when you really want to specialize in an area and do new research on the topic. If that isn't what you are about, then don't go for it. Unless you are going in to a field that has a specific minimum, and most don't past a bachelors, then there's no reason to go for a higher degree just for its own sake.

Any time a friend or family member talks about wanting to get a masters my question for them is always: Why? Not as a petulant "Don't do it," thing but as a challenge. I want them to give me the reason they want to do it. If they can't, or the reason is "To make more money," then I'm going to tell them it is a bad idea. If the reason is "Because this interests and excites me," then I think it is a great idea, even if there isn't going to be a return on the money spent. Education for the sake of learning about what you want is wonderful. Just make sure that is really the reason you are doing it.

Re:I'd go further to say

[Lemmy Caution]

I don't completely agree with you. The BA or BS is the new high school diploma. To really optimize your earning potential, get an MA or MS. But yes, the PhD is actually good only if you love what you are working on more than you love the money it can earn you.

Re:the right way to get a PhD

[FredThompson]

No, this isn't flamebait, it's a direct insult.

Any fool who asks for a future historical perspective deserves disdain. Anyone who asks it in regard to predictive activities, doubly so.

Any fool who asks for the impossible (historical knowledge before the events occur) as a means to predict the relevance of fortunetelling...may as well invest in Bernie's fund.

Naive idealism run amok

[sjbe]

In financial analysis, you do not need to use statistics.

You aren't a financial analyst are you? Statistics is required precisely because financial decisions are almost always made with limited information. You can't model most financial activities including risk without statistics coming into play at some point.

A borrower ability to pay monthly payments is not some unknown quantum state, but well known (at least to himself or his employer)

Actually ability to pay in the future IS unknown even to the borrower. Furthermore ability to pay is not and never will be perfectly known to the lender. There is an inherent information asymmetry because the lender can never be sure the borrower isn't hiding something. Furthermore you are leaving out willingness to pay, as well as the fact that life sometimes isn't so kind and circumstances change. People lose their jobs, they invest with Bernard Madoff, their employer turns out to be Enron, etc. These things cannot always be predicted.

The only reason not to do this, is lack of information or lack of computing power.

So you are comfortable providing no insurance to people with a high likelihood of disease? How about losing most/all access to credit when you lose your job. Because that's what happens with perfect information. Be careful about the unintended consequences of perfect information. Even if a perfect model were possible (and it is not) there are many social reasons why we limit how much information is available and how it can be used.

With fast computers and good data all population statistical analysis should be thrown out, and replaced with calculation for each individual and then integrated.

Except that there NEVER is enough data and it is IMPOSSIBLE to perfectly model future events and actions. Even if I concede that you are right and ignore the unintended consequences, what you are proposing is quite literally impossible. The best you can do in many cases is to make a statistical model of likely behavior based on population models and then seek a portfolio to minimize risk for the desired return. Companies use population statistics because they are the best option available.

A false, or sorry, prediction

[sgt_doom]

I am in complete disagreement with gadget+junkie - if "financial math" is here to stay, we are all doomed - as it is based upon fraud, deception and super-leveraging - not to mention that criminal creation of old Naples, the tontine - a k a "last man standing" financial instrument - won't fly for any true progress - otherwise a continued state of regression will prevail - we will all become the failed neocon-generated economic states of Iceland and Russia.

True, the sum total invested in financial math WAS TRUE, but that has since been "magically" transformed into worthless derivatives - Geithner's fraudulent PPIP program to the contrary.

There should be mass mobs on their way to Basel to burn down the Bank for International Settlements, and to D.C. to burn down the Federal Reserve Bank; both detrimental to any true progress and human development.

Have math. Will pay

[Rsriram]

The financial markets run on sentiment. But no PHB will ever be caught admitting as much. Because it basically means they will lose their million dollar bonuses. They hire mathematicians to come up with a mathematical model to explain their decisionz. Taleb talked about it in his book "fooled by randomness". You can be assured that your job in the financial district is secure because the PHB don't understand math. But they want to be seen taking logical decisions. And what better field than math to "prove" that the decision is logical. Q.E.D