Advice requested: getting into computational finance
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I'm an experienced software engineer with a B.S. in physics, a Ph.D. in computer science, and a love of mathematics. I feel like my brain is going to atrophy if I don't find some way to use my math skills, and I ran across a description of computational finance in Wikipedia that sounds like it could be just what the doctor ordered. The Wikipedia article states that "knowledge of the C++ programming language, as well as of the mathematical subfields of: stochastic calculus, multivariate calculus, linear algebra, differential equations, probability theory and statistical inference are often entry level requisites". I'm a bit rusty on my differential equations and I lack the background in stochastic calculus, but I'm pretty strong on everything else.
So how would you all recommend I go about getting into this field? One constraint I face is that I can't drop everything and go back to school for two years; I need to keep on making an income. But I'm pretty good at studying things on my own. -- Kevin S. Van Horn |
Re: Advice requested: getting into computational finance
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On Fri, Apr 10, 2009 at 6:22 AM, ksvanhorn <[hidden email]> wrote:
> So how would you all recommend I go about getting into this field? One > constraint I face is that I can't drop everything and go back to school for > two years; I need to keep on making an income. But I'm pretty good at > studying things on my own. start studying "The Concepts and Practice of Mathematical Finance" by Mark S. Joshi, which is the best introduction to the field in my opinion. It would help to also have "Options, Futures, and Other Derivatives" by John C. Hull, which is kind of weaker but has a broader coverage and a gentler introduction to markets, asset classes, practitioner practices, etc Add QuantLib for C++ and Wilmott forums (http://www.wilmott.com/index.cfm?NoCookies=Yes&forumid=1) for discussions and you're ready for a rewarding self study trip ciao -- Nando ------------------------------------------------------------------------------ This SF.net email is sponsored by: High Quality Requirements in a Collaborative Environment. Download a free trial of Rational Requirements Composer Now! http://p.sf.net/sfu/www-ibm-com _______________________________________________ QuantLib-users mailing list [hidden email] https://lists.sourceforge.net/lists/listinfo/quantlib-users |
Re: Advice requested: getting into computational finance
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In reply to this post by ksvanhorn
we have a range of distance learning courses that just might address your needs.
regards
Daniel J. Duffy From: ksvanhorn [mailto:[hidden email]] Sent: Fri 10-04-2009 06:22 To: [hidden email] Subject: [Quantlib-users] Advice requested: getting into computational finance I'm an experienced software engineer with a B.S. in physics, a Ph.D. in ------------------------------------------------------------------------------ This SF.net email is sponsored by: High Quality Requirements in a Collaborative Environment. Download a free trial of Rational Requirements Composer Now! http://p.sf.net/sfu/www-ibm-com _______________________________________________ QuantLib-users mailing list [hidden email] https://lists.sourceforge.net/lists/listinfo/quantlib-users |
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In reply to this post by ksvanhorn
Not to discourage you, but given the recent financial services industry meltdown there are a lot of experienced people out of work in this field right now and it will be extremely difficult for someone without experience to get into this field. Plus, there are probably a lot of other things the world needs a lot more than new financial engineers. The president of the united states basically said so himself :) . If you want to use your math skills more, why not consider scientific or graphics related software development? - Matt |
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In reply to this post by cuchulainn
First I would question if all this mathematical
stuff is really needed (I have a PhD in Statistics). There is a huge gap between
the academic-financial and the real-world. Most models are mathematics pour
la mathematics. There are a lot of would-be Einsteins in the field and they want
to show how good they are in Ito-Calculus et al.
I can not judge the quality of the
distance-learning material. I have only read Daniel J.Duffy: Finite Difference
Methods in financial engineering. I would give this book 2-Amazon
stars. The author has put his dusted PhD-Thesis from the shelve. The
thesis is obviously about hyperbolic DEs, the option-problems are
parabolic. So he speaks most of the time of another problem.
The presented code is terrible. Some parts are
commented by the author with
//
This part of code is not really optimal but it works
Unfortunatly even this is not always
true.
D.Duffy has written also an article in Wilmotts
magazine "A Critique of the Crank-Nicolson Scheme". The scheme has - as pointed
out by the author - some numeric problems. But its practically a non-problem.
The options-models are all junk. The numerical problems of Crank-Nicoloson
are negible in comparison to the model-errors. We are not dealing with
dynamic fluid problems.
Furthermore one can solve the instability of
Crank-Nicolson in a trivial way. Crank-Nicolson is a 1:1 combination of the
Explicit and Implicit-Solution method. By changing the weight from 0.5 to e.g.
0.6 (in direction of the implicit method) the instability problems disappear.
Theoretically only Crank-Nicolson has 2nd order convergence, the implicit method
(and also a factor of 0.6) has 1st order. But the exact formulation is: One can
only proove 1st order, in most problems the convergence is almost identical.
Besides this, numerical accuracy is not a real topic in junk-models.
Chrilly Donninger
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well, well, well.. there are some strong comments here.
however the advice is probably a good one ie to think a few times before jumping in. There are many people who study quant finance but only a small proportion get jobs as a quant. This was true even before the financial crisis and is more true in present conditions. Regarding dr. duffy's book, its a good starting point and worth the effort to go through the book. The comments by chrilly are true but can be worked around with the help of forums etc. I would ask this question "IF dr. duffy's book is not good, what are the other options". It is an art to put together code from different source to get something working. Sure there is some hardwork involved in it but thats the way it is with c++. Just my thoughts On Fri, Apr 10, 2009 at 11:38 AM, chrilly <[hidden email]> wrote:
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>>There
are many people who study quant finance but only a small proportion get jobs as
a quant. This was true even before >>the financial crisis and
is more true in present conditions.
The times are generally not the best for starting a new job/project. But the quant business is probably even worse than most other fields. I know of an university which thinks about a "rescue-plan" for students which have done e.g. for 3 years their finance-studies. To ease the change to other more promising directions. Or at least to change the name of the course. Its not only that the demand for finance has evaporated. The field has also got a very bad reputation (at least in some European countries). Its almost like having a PhD for drug-trafficing. >>Regarding dr. duffy's book, its a good starting point and worth
the effort to go through the book.
As a first introduction to the field in general its
reasonable. "Europe in 14-days". A tour de force through the field, but
each time it gets interesting one reads "for further details see..." As already
mentioned it does not really address the methods in option-pricing.
>>The
comments by chrilly are true but can be worked around with the help of forums
etc. I would ask this question "IF dr. >>duffy's book is not good, what
are the other options".
The negative answer, which books are even worse, is
easier:
Justin London, Modeling Derivatives in C++. One of
the worst books I have ever seen.
D.Tavella, C.Randall: Pricing Financial
Instruments: The Finite Difference Methods. The are some interesting glimps, but
overall the book reads like the authors haven written it on one
weekend.
Somewhat better is: L.Clewlow, C.Strickland:
Implementing Derivatives Models.
Wilmott has in Vol-III some explanations and code.
But the quality is also low. Generally there are zillions of Financial books but
the overall quality is rather low. Its was like the market. A lot of hot
overpriced air.
Its better to read general classical
introductions/books to the field. Although this books are for my taste also too
mathematical and too less practical. E.g.
J.W.Thomas: Numerical Partial Differential
Equations.
K.W.Morton, D.F.Mayers: Numerical Solution of
Partial Differential Equations.
Quantlib has also some
classes (E.g. Crank-Nicolson).
>>It is
an art to put together code from different source to get something
working. Sure there is some hardwork involved in >> but thats the
way it is with c++.
Yes. Chrilly
------------------------------------------------------------------------------ This SF.net email is sponsored by: High Quality Requirements in a Collaborative Environment. Download a free trial of Rational Requirements Composer Now! http://p.sf.net/sfu/www-ibm-com _______________________________________________ QuantLib-users mailing list [hidden email] https://lists.sourceforge.net/lists/listinfo/quantlib-users |
Re: Advice requested: getting into computationalfinance
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>>Regarding dr. duffy's book, its a good starting point and worth the effort to go through the book.
As a first introduction to the field in general its reasonable. "Europe in 14-days". A tour de force through the field, but each time it gets interesting one reads "for further details see..." As already mentioned it does not really address the methods in option-pricing. I think you are referrring(?) to the "Introduction to C++ for financial engineers", which is a basic introduction. I have 2 others books as well, one on more advanced topics in C++ and PDE and a book on PDE/FDM.
//
On the Crank Nicolson, here is a thread showing how it not works for the Greeks
And for the Heston model CN needs to be replaced by Richardson (see Shephard's thesis, it's on my site).
regards
Daniel Duffy From: chrilly [mailto:[hidden email]] Sent: Fri 10-04-2009 21:47 To: Satish Vangipuram Cc: Daniel J. Duffy; ksvanhorn; [hidden email] Subject: Re: [Quantlib-users] Advice requested: getting into computationalfinance >>There are many people who study quant finance but only a small proportion get jobs as a quant. This was true even before >>the financial crisis and is more true in present conditions.
The times are generally not the best for starting a new job/project. But the quant business is probably even worse than most other fields. I know of an university which thinks about a "rescue-plan" for students which have done e.g. for 3 years their finance-studies. To ease the change to other more promising directions. Or at least to change the name of the course. Its not only that the demand for finance has evaporated. The field has also got a very bad reputation (at least in some European countries). Its almost like having a PhD for drug-trafficing. >>Regarding dr. duffy's book, its a good starting point and worth the effort to go through the book.
As a first introduction to the field in general its reasonable. "Europe in 14-days". A tour de force through the field, but each time it gets interesting one reads "for further details see..." As already mentioned it does not really address the methods in option-pricing.
>>The comments by chrilly are true but can be worked around with the help of forums etc. I would ask this question "IF dr. >>duffy's book is not good, what are the other options".
The negative answer, which books are even worse, is easier:
Justin London, Modeling Derivatives in C++. One of the worst books I have ever seen.
D.Tavella, C.Randall: Pricing Financial Instruments: The Finite Difference Methods. The are some interesting glimps, but overall the book reads like the authors haven written it on one weekend.
Somewhat better is: L.Clewlow, C.Strickland: Implementing Derivatives Models.
Wilmott has in Vol-III some explanations and code. But the quality is also low. Generally there are zillions of Financial books but the overall quality is rather low. Its was like the market. A lot of hot overpriced air.
Its better to read general classical introductions/books to the field. Although this books are for my taste also too mathematical and too less practical. E.g.
J.W.Thomas: Numerical Partial Differential Equations.
K.W.Morton, D.F.Mayers: Numerical Solution of Partial Differential Equations.
Quantlib has also some classes (E.g. Crank-Nicolson).
>>It is an art to put together code from different source to get something working. Sure there is some hardwork involved in >> but thats the way it is with c++.
Yes. Chrilly
------------------------------------------------------------------------------ This SF.net email is sponsored by: High Quality Requirements in a Collaborative Environment. Download a free trial of Rational Requirements Composer Now! http://p.sf.net/sfu/www-ibm-com _______________________________________________ QuantLib-users mailing list [hidden email] https://lists.sourceforge.net/lists/listinfo/quantlib-users |
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In reply to this post by ksvanhorn
My thanks to everyone who has responded; I appreciate your help. I'm not entirely sure where I'm going with this -- just exploring possibilities, mainly. Yes, everyone is laying off and hiring is down everywhere these days; dice.com job listings are down 45% from a year ago. I did find one company, though, that seems to be aggressively hiring software developers with a background in functional programming to work closely with their quants.
I have two final questions, if you don't mind. First, is there a good quick survey of the field, something that maps out the important ideas, topics, and problems? Second, is QF only useful for large enterprises, or could some of this stuff be of use to individual investors and decision makers for small/medium businesses? Two issues lead me to ask this: 1) transaction costs, which I assume are going to be a lot more significant for a smaller player, and 2) in my initial reading I've encountered an assumption that interest rates for borrowing and lending are (nearly) the same, which only holds for large enterprises. |
Re: Advice requested: getting into computationalfinance
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In reply to this post by chrilly
"The author has put his dusted PhD-Thesis from the shelve. The thesis is obviously about hyperbolic DEs, the option-problems are parabolic. So he speaks most of the time of another problem."
Actually, my PHD was on convection-diffusion (hyperbolic + parabolic). I think you focus on chapters 5 and 9.
The splitting methods are the most robust. Here is a thesis based on Heston (chapter 22) using these methods.
And again, see the section on CN in that thesis, it just is wrong (in this case).
Daniel Duffy From: chrilly [mailto:[hidden email]] Sent: Fri 10-04-2009 17:38 To: Daniel J. Duffy; ksvanhorn; [hidden email] Subject: Re: [Quantlib-users] Advice requested: getting into computationalfinance First I would question if all this mathematical stuff is really needed (I have a PhD in Statistics). There is a huge gap between the academic-financial and the real-world. Most models are mathematics pour la mathematics. There are a lot of would-be Einsteins in the field and they want to show how good they are in Ito-Calculus et al.
I can not judge the quality of the distance-learning material. I have only read Daniel J.Duffy: Finite Difference Methods in financial engineering. I would give this book 2-Amazon stars. The author has put his dusted PhD-Thesis from the shelve. The thesis is obviously about hyperbolic DEs, the option-problems are parabolic. So he speaks most of the time of another problem.
The presented code is terrible. Some parts are commented by the author with
// This part of code is not really optimal but it works
Unfortunatly even this is not always true.
D.Duffy has written also an article in Wilmotts magazine "A Critique of the Crank-Nicolson Scheme". The scheme has - as pointed out by the author - some numeric problems. But its practically a non-problem. The options-models are all junk. The numerical problems of Crank-Nicoloson are negible in comparison to the model-errors. We are not dealing with dynamic fluid problems.
Furthermore one can solve the instability of Crank-Nicolson in a trivial way. Crank-Nicolson is a 1:1 combination of the Explicit and Implicit-Solution method. By changing the weight from 0.5 to e.g. 0.6 (in direction of the implicit method) the instability problems disappear. Theoretically only Crank-Nicolson has 2nd order convergence, the implicit method (and also a factor of 0.6) has 1st order. But the exact formulation is: One can only proove 1st order, in most problems the convergence is almost identical. Besides this, numerical accuracy is not a real topic in junk-models.
Chrilly Donninger
------------------------------------------------------------------------------ This SF.net email is sponsored by: High Quality Requirements in a Collaborative Environment. Download a free trial of Rational Requirements Composer Now! http://p.sf.net/sfu/www-ibm-com _______________________________________________ QuantLib-users mailing list [hidden email] https://lists.sourceforge.net/lists/listinfo/quantlib-users |
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In reply to this post by ksvanhorn
despite all negativity that one can read/hear these days in the media about quants, there is one thing for sure: quants are here to stay. because it is not quants who failed, correct? it was risk management / compliance / regulation or simple ethics and stupidity. in the aftermath of dot.com internet became an almost forbidden word. same is happening now to quants. nevertheless quants can and will provide a valid value-adding service to the world of financial intermediation, aka banks and co.
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Re: Advice requested: getting into computational finance
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Financial products were too complex and the quants and scholars (especially on exotic derivatives) claim they can provide good foundation (so called) for pricing and risk management. But theory and practice may significantly different.
> Date: Fri, 10 Apr 2009 14:40:53 -0700 > From: [hidden email] > To: [hidden email] > Subject: Re: [Quantlib-users] Advice requested: getting into computational finance > > > despite all negativity that one can read/hear these days in the media about > quants, there is one thing for sure: quants are here to stay. because it is > not quants who failed, correct? it was risk management / compliance / > regulation or simple ethics and stupidity. in the aftermath of dot.com > internet became an almost forbidden word. same is happening now to quants. > nevertheless quants can and will provide a valid value-adding service to the > world of financial intermediation, aka banks and co. > > > > ksvanhorn wrote: > > > > My thanks to everyone who has responded; I appreciate your help. I'm not > > entirely sure where I'm going with this -- just exploring possibilities, > > mainly. Yes, everyone is laying off and hiring is down everywhere these > > days; dice.com job listings are down 45% from a year ago. I did find one > > company, though, that seems to be aggressively hiring software developers > > with a background in functional programming to work closely with their > > quants. > > > > I have two final questions, if you don't mind. First, is there a good > > quick survey of the field, something that maps out the important ideas, > > topics, and problems? > > > > Second, is QF only useful for large enterprises, or could some of this > > stuff be of use to individual investors and decision makers for > > small/medium businesses? Two issues lead me to ask this: 1) transaction > > costs, which I assume are going to be a lot more significant for a smaller > > player, and 2) in my initial reading I've encountered an assumption that > > interest rates for borrowing and lending are (nearly) the same, which only > > holds for large enterprises. > > > > > > -- > View this message in context: http://www.nabble.com/Advice-requested%3A-getting-into-computational-finance-tp22982909p22995108.html > Sent from the quantlib-users mailing list archive at Nabble.com. > > > ------------------------------------------------------------------------------ > This SF.net email is sponsored by: > High Quality Requirements in a Collaborative Environment. > Download a free trial of Rational Requirements Composer Now! > http://p.sf.net/sfu/www-ibm-com > _______________________________________________ > QuantLib-users mailing list > [hidden email] > https://lists.sourceforge.net/lists/listinfo/quantlib-users Rediscover Hotmail®: Now available on your iPhone or BlackBerry Check it out. ------------------------------------------------------------------------------ Stay on top of everything new and different, both inside and around Java (TM) technology - register by April 22, and save $200 on the JavaOne (SM) conference, June 2-5, 2009, San Francisco. 300 plus technical and hands-on sessions. Register today. Use priority code J9JMT32. http://p.sf.net/sfu/p _______________________________________________ QuantLib-users mailing list [hidden email] https://lists.sourceforge.net/lists/listinfo/quantlib-users |
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economics as a science is reasonably old compared to our lives-times and has very little formulars in it so that most people can read it and draw conclusions. However, we still live in the current crisis and nobody (i.e. no government) has any real clue about how to get out of where we are. And no need mention that theory of economics failed to warn us before we got here. I can still remember very clearly how Greenspan was treated when he resigned.
So I believe it is a clear sign of how well mainstream theories align with realities. Thus no need to blame quants and their field more than anybody else. Important disclosure: I am no a quant (as per definition of my position)
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In reply to this post by snovik
"quants are here to stay. because it is
not quants who failed, correct? it was risk management / compliance / regulation or simple ethics and stupidity. " ===========
Just wonder how many quants are actually working in or for risk management! In my view, they are part of risk management team. On Fri, Apr 10, 2009 at 4:40 PM, snovik <[hidden email]> wrote:
------------------------------------------------------------------------------ Stay on top of everything new and different, both inside and around Java (TM) technology - register by April 22, and save $200 on the JavaOne (SM) conference, June 2-5, 2009, San Francisco. 300 plus technical and hands-on sessions. Register today. Use priority code J9JMT32. http://p.sf.net/sfu/p _______________________________________________ QuantLib-users mailing list [hidden email] https://lists.sourceforge.net/lists/listinfo/quantlib-users |
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