UWashington MS Computational Finance class 2013-2014

ElephantParks

ElephantParks

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Hi guys, not sure if admission is already over, but would like to start getting in touch with future classmates here:) I'm an international student and will be joining the program this Fall.

Graduates and current students are more than welcomed to impart your wisdom and suggestions here too;) e.g. things to do to better prepare for the program, internship/job placement stats in great Seattle area etc etc
 
I got accepted and am tentative on the yes (reserved a spot). Ultimate decision will wind up being a financial one, no pun intended.
 
Hi IlyaKEightSix, thanks for the input, have you tried applying for scholarship of any sort at UW? (if that's the kind of financial predicament you're talking about though)
 
I am in the UW program and should be completing my degree in December (2013). I work full time and have been taking one class per quarter (for the last two years).

As to preparation: if you don't already have a solid statistics background (and perhaps even if you do) brush up on your statistics. In my view, you can't have too deep a background in statistics.

Almost all of the courses have some amount of R programming. There is an in depth course taught by Guy Yollen in R. There was/is also a mini-course in SQL.

For your professional future, the deeper your software background the better. If you are in Seattle and can take some computer science courses, I'd do so. I had classmates that took numerical analysis and other applied math courses to fill in the credits (they needed to take 10-units a quarter). I don't want to knock numerical analysis, since it is important, but there's only so much time. I think my classmates would have been better off taking courses in the CS department (UW has an excellent CS department). The better you are at C++ and Java the better your job prospects will be (you should get pretty good at R by the time you graduate).
 
Hi Ian, do you have any recommrndation on books that are effective in brushing up statistics? Thanks in advance.
 
I have gotten a lot of mileage out of a book I have on statistics for engineers. There's lots of choices in this area so I'd look on Amazon and by a used book.

Another book I'd recommend, since you are going to need it on your bookshelf anyway, is David Ruppert's book "Statistics and Data Analysis for Financial Engineering". When I first used Ruppert I didn't like him much. Some of his explanations can be sparse and his notation can be confusing. However, he has grown on me, perhaps as my background has improved.

When you are registered as a UW student you have access to the on-line library resources. This includes Springer-Link. You should be able to order a paperback version of Ruppert via Springer-Link for $25.

Another classic, which you should be able to get used is MASS: Modern Applied Statistics with S+. R is based on S+ and most of the S+ functions exist in R so this is still a great reference. David Ripley, the co-author of the book, is active on the R forums. A lot of us wish that he would write a new book that directly references R.

I like Julian Faraway's book "Linear Models with R".

And, since you will be using R, I recommend Norman Matloff's book "The Art of R Programming" and "R in a Nutshell". I've also gotten a lot of use form "R Graphics" by Paul Murrell. This is a basic book on R graphics that explains things like the plot margins and various ways to control plot labels.
 
That's a really specific answer, thanks Ian for the meticulous wisdom pouring! Just recently I've started reading Fabozzi's "Probability and Statistics for Finance" as I've come to like his way of presentation after a few other of his books, and also the fact that I'm a little rusty on the subject so I'd feel more comfortable doing a comprehensive brush-up with both fundamentals and relevant financial applications. I'll get a copy of Ruppert's later too. I think for now my objective is more on getting the clarity than delving into a lot details.
 
If you're reading about statistics, R is a great thing to use along the way. Many of the R packages include data so you can experiment with it. The problem with statistics is that its a huge field and there's always something I wish I knew more about (right not that would be logistic regression). I deal with this by buying a lot of used books on Amazon.

You're definitely going to be using Ruppert in more than one course. The book is a great reference.

Best,
Ian
 

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