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How do you understand/appreciate math on a more philosophical level?

Sensible Use of Quant Models and Modelers

Thank you very much for helping make sense of the mess.

Nothing innate about it. It's a political decision made by those in power that the math should serve as a fig leaf to disguise the nakedness of how prices are determined and to camouflage a casino-like activity (which MacKenzie discusses).

By innate, I meant that math and quant models now seem to be part-and-parcel of derivatives and structured products, many of which are really valued for risk management and hedging. Now, unless there is some way to turn the clock back and get rid of all the math- and quant modeling based products and services, we will need to learn to live with them and hopefully improve them by learning what doesn’t work.

If the models aren't working, why continue to use them -- except to deceive the lay public into how abstruse the whole area is? It's a case of the emperor without any clothes.

Folks such as Derman, Taleb, and, Wilmott have been critical of “misuse” and “ignorant” use of models and do not seem to have asked to reject math and models altogether despite their limitations. Their point is that models did not work because most individuals using them did not use them appropriately (for example, Wilmott had been recently organizing a bootcamp to train an army of modelers who will get it right). For whatever it is worth, it seems a plausible argument and perhaps cannot be summarily dismissed without stronger evidence and / or rationale. This observation doesn’t negate your point about the relative poverty of many models (and related methods) to capture the richness of real social phenomena such as finance. The above folks who still seem to have credibility as well as others such as Mandelbrot, all seemed to have acknoweldged this point. For example, if one reads some of Derman’s decade old articles, he talks about similar limitations of models that we are discussing here.

Use "Ockham's razor": search for the simplest possible explanations that make phenomena intelligible. In general, complex theories and explanations die a quick death while simple ideas -- or at least simple foundations -- endure. Be suspicious of complexity: it is usually there to hide intellectual poverty, to camouflage base and mercenary motives, to confuse and deceive people. Genius consists in finding simple ideas and explanations for seemingly complex phenomena while mediocrity consists in devising complex and confusing theories.

Agreed, some of the most profound systems are based on a few simple principles. It is yet to be determined if it may be feasible to simplify the complexity of financial innovations while improving their utility. Not sure if it is feasible, however, everyone should benefit from it given the ongoing backlash against complexity of such products. This seems to be a challenge that all modelers, old and new, should aspire to handle. That being said, if we acknowledge the complexity of finance, then I am not sure if we can really create simple systems to handle such complexity: it would seem to contradict the law of requisite variety.

If you want a job in the field, you have to demonstrate some mastery of these things to those interviewing you. If that's what you mean, I agree.

OK. At least you agree that being ‘legit’ requires knowledge [and probabaly accreditation] of the math and quant models probably as a ‘right of passage’. That puts this point to rest and hopefully those interested can take it for whatever it is worth. On a related note, the same observation may apply to many other fields and professions including engineering and trading as most 'real experience' is acquired in 'learning by really doing' ('strong empiricism' as Taleb would call it - also ties back to your point about empiricism).

If you mean you have to master complex models in order to demonstrate their inapplicability or falsehood, you are wasting your time. Life is too short for this kind of pointless demonstration. You don't have to master the Ptolemaic calculations in order to refute the Ptolemaic outlook on planetary motions

The issue is not about proving absolute truth or falsehood which is the domain of most purely academic pursuits, not suggesting that they are not important. However, mastering the models to recognize their applied and pragmatic limitations and then ‘tinkering’ (isn't that the name of the latest book that Taleb had been planning on writing?) them as needed based on learning-by-doing and rechecking to see if they deliver the expected outcomes is what seems prudent. The focus should probably be less on the neatness of the model and more on the neatness of the outcomes within an ever-adaptive dynamic context [something like Stefen Zota seemed to suggest earlier]. I think that folks such as Derman, Taleb, and Wilmott would probably agree with the method despite its madness.
 
Errm..was just talking about your extensive use of long-MBA-esque words. I am about to complete my Ph.D. and never had such discussion. Am I screwed. :-ss

Not yet, probably ;-). After getting admit to my second PhD at a top-10, dropped the idea recognizing that they probably can't teach me [especially] what I care to know. Probably you may also feel the same way a while after you are done with the first. Now you may also recognize why I may not recall or care much about GRE as compared with other stuff that fascinates my learning.
 
Not yet, probably ;-). After getting admit to my second PhD at a top-10, dropped the idea recognizing that they probably can't teach me [especially] what I care to know. Probably you may also feel the same way a while after you are done with the first. Now you may also recognize why I may not recall or care much about GRE as compared with other stuff that fascinates my learning.

Fair enough. We will see how it goes. but when you say "They can't teach me"...I find that odd. They are not supposed to teach you..you have to use the opportunity to learn, especially at this level. I got undergrad at 21 and will be done with a PhD before I turn 26, and I would say I enjoyed the experience a lot, and I am not THAT far behind my peers.
I have a better math background than most MFE people, and along with that quite a bit of experience working on big computational projects.
 
...but when you say "They can't teach me"...I find that odd. They are not supposed to teach you..you have to use the opportunity to learn

Great, you got the point ;-) No one can 'teach' anyone: it is everyone's own right, privilege, and, duty to 'learn' for oneself: some may argue that it is the only possible way to really learn. Greatest deans and professors at the greatest schools recognize so and have often explicitly said so. As you head out beyond PhD, here is something said by Taleb that may come in handy some day, I learned the same lesson in other words from a great professor in grad school, however Taleb's choice of words seems more colorful:

"Anytime I take a street smart kid with a strong Brooklyn accent and train him or her in quant methods, I develop a wonderful quant trader who knows how to squeeze the sitting ducks. When you take extremely quantitative trainees, particularly from the physical sciences, and try to make them arbitrage traders, they freak out and become pure gamblers. They can't see the edge and become the sitting ducks."
 
Great, you got the point ;-) No one can 'teach' anyone: it is everyone's own right, privilege, and, duty to 'learn' for oneself: some may argue that it is the only possible way to really learn. Greatest deans and professors at the greatest schools recognize so and have often explicitly said so. As you head out beyond PhD, here is something said by Taleb that may come in handy some day, I learned the same lesson in other words from a great professor in grad school, however Taleb's choice of words seems more colorful:

"Anytime I take a street smart kid with a strong Brooklyn accent and train him or her in quant methods, I develop a wonderful quant trader who knows how to squeeze the sitting ducks. When you take extremely quantitative trainees, particularly from the physical sciences, and try to make them arbitrage traders, they freak out and become pure gamblers. They can't see the edge and become the sitting ducks."


And how ironic is it that Taleb is a PhD and MBA from Wharton ?
 
He's not the usual kind of Ph.D. (i.e., a cowering, timid individual who just wants a steady job and secure salary). I think he earnt his doctorate to give his pronouncements more credibility.

And I want to earn my PhD. to give the models I design more credibility.
Whats up with PhD bashing ? All PhDs are cowering timid individuals ? And whats wrong with wanting a steady job ?
In my opinions, all MBAs are 24x7 BS machines...so what ?
 
Whats up with PhD bashing ? All PhDs are cowering timid individuals ? And what's wrong with wanting a steady job?

Sorry, bad experiences at the hands of academics, whom I've grown to despise. I like free spirits, revolutionaries, dissidents. Ph.D.s (and MBAs) are not made in such a mold. The American system of graduate education -- based on the Prussian model of the 18th and 19th centuries -- is designed to weed out mavericks and independent thinkers. Conformists are wanted, those who can kowtow to power.

The American university is intimately tied to the the American military and corporate complexes. The American academic is a functionary in this setup.

Going waaay off-topic now.
 
Getting Real About the World of Quant Finance

And what's wrong with wanting a steady job?

Any program in quant finance worth its price will tell you the first thing that anyone must know:

You can expect a lot to learn and lot that challenges you to grow and adapt.
However, don't expect a "steady job" in an area as volatile as quant finance especially in current economic era.

If they say anything different, 'caveat emptor' as our good friend BBW would say.

Andy who does a great job of caring and nurturing of QuantNet hints at the same 'lesson' in many prior posts.
 
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