U. Washington Computational Finance program

Hi, this program looks great, however, it would be very helpful if ex / current students could shed some light on the placements (which companies / banks, what is the package / salary, jobs for algo trading (opportunities), whats the location of the jobs are.. surely must be away from NY). Also, would top banks consider this degree (from UW) good enough.. or one is required to go to CMU, Columbia (which are strategic in terms of location and network, however, comes at a heavy cost)?

Would be really helpful and much appreciated. Thank you
 
Hi Guys,

I am working on application for UW CF&RM online. I have a Bachelor's Engineering degree in Information Science from Indian University.

Has anyone with similar background tried out the GPA conversion matrix ? Attaching the matrix documents.
 

Attachments

March 19, 2014: We are pleased to announce a new faculty member on our team. The UW Applied Mathematics Department has hired Matthew Lorig as an Assistant Professor in support of the MS-Computational Finance & Risk Management program, and he will join us this coming July. Matt is finishing the third year of a Post-Doctoral Research appointment in the Princeton University Operations Research and Financial Engineering Department, and has a substantial research record in mathematical finance.
 
If this program is less quantitative in nature, how does that translate in terms of job opportunity and salaries?
 
I would be keen to hear from some recently qualified UW CF&RM grads.
I plan to start this course in September as I have just been accepted :)
 
I've looked at the curriculum and am curious how helpful this program would be for a research analyst? Or is it predominantly optimization of portfolios, derivatives pricing, etc?

Also how much of this can just be self taught for a dedicated, and passionate (about the subjects) student.

Thanks in advance to anyone who can answer. Interesting looking program.
 
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I've just completed the Trading Systems module (CFRM 551) and it was excellent.
The quality of teaching was superb.
551 is a very hands-on module - we did 6 programming assignments and 2 exams. R is used.
The module is fairly unique as I am not aware of any other university that teaches trading systems development.

Other students who have completed other modules say the course over-all is very rigorous.
 
Thanks Nick, I understand it is rigorous program but I am curious who the program applies to...an equity analyst? Or what the desired outcome/position for students job wise?

Trading systems, classic portfolio optimization, derivatives, etc. seem like pricing esoteric securities, trading strategies, and quant funds that 'optimize' their portfolios allocations off classical algorithms.

Am I misinterpreting this? If so anyone please put their two sense in and again can one self learn this material with a decent math/finance background?
 
It seems like you're asking two questions: 1) would the UW program be useful for an equity analyst and 2) can you learn the material in the program on your own.

The UW program leans more toward mathematical finance. They do not cover asset pricing and corporate factors (cash flow, book value, debut, taxes, etc). Nor do they cover how to estimate future corporate profits (e.g, company Foo is projected to earn $0.1/share). This material is covered more in an MBA program. As I understand it, the equity analysis that specialize in becoming experts on a corporate sector generally have MBA backgrounds.

Can you learn this material on your own? I don't think that I could have. In fact, there are some topics that we covered in the program that I had tried to learn on my own and didn't understand until I took the classes. Also, you would need to be a very dedicated person. Courses motivate you because you want to do well in the course. I worked full time during my degree, so I was working 80 hours a week. I don't think that I would have had this level of motivation if I were not worried about doing well in my courses.
 
Ian Kaplan said:
It seems like you're asking two questions: 1) would the UW program be useful for an equity analyst and 2) can you learn the material in the program on your own.

The UW program leans more toward mathematical finance. They do not cover asset pricing and corporate factors (cash flow, book value, debut, taxes, etc). Nor do they cover how to estimate future corporate profits (e.g, company Foo is projected to earn $0.1/share). This material is covered more in an MBA program. As I understand it, the equity analysis that specialize in becoming experts on a corporate sector generally have MBA backgrounds.

Can you learn this material on your own? I don't think that I could have. In fact, there are some topics that we covered in the program that I had tried to learn on my own and didn't understand until I took the classes. Also, you would need to be a very dedicated person. Courses motivate you because you want to do well in the course. I worked full time during my degree, so I was working 80 hours a week. I don't think that I would have had this level of motivation if I were not worried about doing well in my courses.
Click to expand...

Thanks Ian that was helpful.

One follow up that may be dumb, what is the goal(s) of the program? i.e. pricing derivatives, optimizing portfolio allocations, etc??

And how is this goal reached...if it is derivatives pricing, is it taught via classical formulas; same for optimizing portfolio positioning? It seems from what I read that maybe UW does it a little different as they try to mix theoretical with application....but basically what does one get out of the program and how is it applied in real life? I would love to see/hear lots of examples if anyone has time. One example I'd like to know is in one of the courses I noticed they discussed kelly wagers, are different theories discussed? or is it predominantly classical optimization of portfolio positions and these ideas are briefly mentioned?

Thank you to all of you that have expounded on the program, it seems real interesting.
 
I think that the "goal" of he UW program is to provide a solid foundation in computation finance and risk analysis. What the program taught me is how little I know and how much I want to learn. Practitioners spend their lives mastering topics like options and portfolio analysis and construction. No graduate program is going to replace this.

There are a variety of constraints on a graduate program. One of these is time. Most student are not able or willing to spend more than a couple of years or so getting a masters. The UW program, from its inception, has had working students in mind. For most people this means that you take about one course a quarter (I had a few really brilliant fellow students who worked full time and took two courses a quarter, but I could not have done this). If the Masters degree were sixty units, for example, many working students couldn't do this.

The time constraint in a Masters program means that although the courses are very demanding and intensive, they are only an introduction to the actual practice of quantitative finance.

As to how the program "applies to real life": again, it provides a foundation for what you need to know. Quantitative portfolio construction in the Masters program is only the first step in being able to structure a portfolio that has more attractive features than the benchmark. In my view, academic programs would be better if they spent more time on the estimation of future return. However, the problem is, people write articles about this less than they write about portfolio risk and optimization.

A brief digression on the Kelly formula: I have been fascinated by Ed Thorp's career and the "Kelly formula" is probably famous because of Thorp. But it is just another way to view risk and it has its problems. Thorp is a genius and a creative mathematician. He derived the Black-Scholes formula before Black-Scholes-Merton. However, Thorp kept quiet and made hundreds of millions of dollars. However, the Kelly formula was just another tool in his tool box (which he constantly sought to expand).
 
Thanks for the insightful reply. I guess I struggle with the definition of this "computation finance and risk analysis" since so much risk analysis uses beta.

Thorp is fascinating. Besides his book have you found much info on him? From what I have read he used that tool for his whole portfolios and was a key reason why he outperformed. Is they incorrect?

How would you relate learning about things like kelly, etc to the program? And those are excellent points on the time constraints.

Predicting future returns seems more interesting for indices etc that individual securities as it is quite difficult to determine the true factors that made an individual security to up or down in price.

What type of options/derivatives trading/pricing is taught?

Thanks so much Ian this is very helpful.
 
Actually, I don't think that it's true that "much of risk analysis is beta". More like distributions, copulas and so on.

The book "Fortune's Formula" has a profile of Thorp. He also has a set of articles he wrote for Wilmot on his web site. Then there are his academic articles.

I think that the fascination with derivatives is misplaced. I took the excellent UW derivatives and modeling courses and I remain fascinated by derivatives in investment portfolios. But most people are not going to do derivatives pricing or even use derivatives. Fixed income pricing is more likely and portfolio investment more likely still. Think about it: there are trillions of dollars invested in portfolios.

I did my Masters project on portfolio factors (http://www.bearcave.com/finance/thesis_project/index.html) and I have been working on portfolio models for my own investment. I did not learn in my courses how to construct a portfolio that will beat an index (e.g., an IR > 0). But my course work gave me the building blocks I needed. Without these building blocks, I would not have understood quantitative portfolio construction.

Finance has become very sophisticated. Without the foundation provided by graduate level courses, you don't have a clue. But a foundation does not make a building. All the rest you have to build on your own and there is a lot.
 
Ian Kaplan said:
Actually, I don't think that it's true that "much of risk analysis is beta". More like distributions, copulas and so on.

The book "Fortune's Formula" has a profile of Thorp. He also has a set of articles he wrote for Wilmot on his web site. Then there are his academic articles.

I think that the fascination with derivatives is misplaced. I took the excellent UW derivatives and modeling courses and I remain fascinated by derivatives in investment portfolios. But most people are not going to do derivatives pricing or even use derivatives. Fixed income pricing is more likely and portfolio investment more likely still. Think about it: there are trillions of dollars invested in portfolios.

I did my Masters project on portfolio factors (http://www.bearcave.com/finance/thesis_project/index.html) and I have been working on portfolio models for my own investment. I did not learn in my courses how to construct a portfolio that will beat an index (e.g., an IR > 0). But my course work gave me the building blocks I needed. Without these building blocks, I would not have understood quantitative portfolio construction.

Finance has become very sophisticated. Without the foundation provided by graduate level courses, you don't have a clue. But a foundation does not make a building. All the rest you have to build on your own and there is a lot.
Click to expand...

Thanks for the Thorp rec's. Have you read his book?

When I referenced beta I was thinking that all the models you produce to estimate risk the input is historical prices and therefore incorporates beta or just in general that the theory of taking historical prices (unless it is indices) would be difficult to adjust for factors.

Thanks for the paper link, looking forward to reading it! Thanks again for all the replies.
 

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