wolf87

4 & 5 are my favorites, along with "WLOG, take ... . All other cases are trivial/analogous." You also have to love the technique, especially common in Rudin, of citing 10+ numbered theorems in a sentence or two, writing one or two expressions, and stating that the desired consequence follows easily.

You might also want to check "Econometrics in R", page 18 ( http://cran.r-project.org/doc/contrib/Farnsworth-EconometricsInR.pdf )

Shouldn't there be an adjustment to make it a fair bet? Like, say $25 per school you get into, $100 per reject?

I think that the GRE score may be a slight issue at places like Berkeley, Columbia, and NYU, but her engineering background and work experience may help to make up for it. I would shoot for the three programs I mentioned, plus Cornell and maybe a few others (I've heard that Purdue is fairly good and gives funding in some cases). Also, the discussion boards at Wilmott (Wilmott Forums - Careers Forum) tend to be a bit better for this kind of question. Good luck.

Thanks doubtful & CalmLogic. Does anyone have an idea what the typical math subject GRE score range is for the top 10?

Hey everyone. Hope that the wait for decisions is proceeding (relatively) stress-free. I'm considering a transition from a background in math & econ to a PhD in statistics, and I would appreciate some input. I am interested in theoretical statistics (primarily time series & spatial) and technical/scientific applications. I have been advised that integrated math/stats departments may be my best bet, but I do not know of very many of these. So, first question is: does anyone know what the best such departments are? Second question: I would appreciate any feedback you can give me on my profile. I'm looking at top-10 stats departments (Berkeley, Stanford, Harvard, etc.). Degrees: Completing BA in econ & math, MA in econ this May GPA: 3.97 overall, 4.00 in math & stats GRE (general): Q 800, V 720, A 4.5 GRE (math subject): have not yet taken; looking to sit-in on abstract algebra this semester to fill in missing piece of background Math coursework: Multivariate calculus, differential equations, linear algebra, stochastic processes (masters-level), mathematical finance (masters-level), 2 semesters of real analysis, first year PhD statistics & econometrics in economics department Research: Derivation & implementation of algorithm for estimation of controlled state-space systems Other: US citizen, native English speakerI realize that it's pretty late to be trying to sort this stuff out, but I figure better late than never. If I end up going this direction, I'll probably apply for Fall 2009, which leaves the coming year to sort out; any ideas on that would be also be welcome :) . Thanks

Hi everyone. I'm getting my stuff together to apply to grad schools, but my efforts are being hindered by a point of confusion. I'm trying to sort out what the applied vs. theoretical labels mean for econometrics. I had previously thought that applied meant that you work on practically-inspired problems, developing methods and maybe doing a bit of empirical work with them, whereas theoretical meant that you just worked on far more abstract problems. Lately I've heard that applied --> mainly empirical work & theoretical --> mainly method development. Can anyone help me sort out the various branches of econometrics? Even brief list of definitions would be incredibly helpful. My interests are basically as follows: I'm interested in developing methods and approaches inspired by real-world problems and doing a bit of empirical work with these. I would also very much like to work across multiple application areas. Would this fall under theoretical or applied econometrics? Thanks in advance.

The quant and verbal are on ridiculously different scales. As of August, an 800 on the quant is 94%, whereas a 720 on verbal is 98%. So, just to be in the top 6% on quant, you need the 800. For verbal, you have a lot more leeway. If you want to see something really interesting/weird about this stuff, open up the GRE powerprep software and look at the reports for econ PhD quant, econ PhD verbal, and english PhD verbal. Note how insanely skewed the distribution is the the first, how much closer to normal the second is, and how low the median for the third is.

I'm a prospective PhD, but I spend this past summer doing research on a trading floor. The advice from everyone there with a PhD: "Never compute the NPV of a PhD. It's depressing." Unfortunately, they told me 6 month after I computed it. The short answer is that, in pecuniary terms, a PhD will not be worth it. The main payoff from a PhD is the potential to do work in a field you love, the job security of academia and some other positions (govt, etc.), and, in some sense, a nice 'retirement package'. In many fields, once you're over a certain age it's either up or out, so there's a very slim chance that you can spend your entire career doing research. With a PhD, you have the option of going into academia for a bit, going to govt, coming back, etc. If you have experience and the degree, you can teach later on in life. Anyways, those are just my thoughts. Good luck on your decision(s); these are the tough ones.

Hello everyone. Brief question on age ranges: I am looking to apply to PhD programs in economics and finance for 2008 (interests are econometrics, finance, and macro, in that order), and I have a few concerns about age. I will be 20 when I complete my BA & MA at my current program, and I will turn 21 next August. In either kind of program, I will be young. My question is, are students in finance PhD programs typically older than those in econ programs? I have had a tough time finding good data on this subject. Thanks, and good luck to everyone who is finishing up finals.

UChicago GSB has a dedicated program in econometrics. A few business schools also have statistics PhD programs. A lot of schools have dedicated Statistics PhD programs (Harvard and Stanford come to mind as two of the best), but their research tends to be somewhat different than what you see in econometrics. According to my econ advisors, if you decide to go for an econ PhD -> econometrics, the best US programs are Yale, Harvard, MIT, Chicago, Stanford, Princeton, and Berkeley. Best of luck.

I am currently in BU's masters program (BA/MA student). Masters students do get a fair amount of faculty attention, especially if you are planning on continuing onto a PhD. Wherever you end up, what matters most for both faculty attention and future success is how well you do.

Hello everyone. I am currently pursuing a BA in econ & math and a MA in econ at a top-30 US university, graduating in May 2008, and I hope to go on to a PhD in finance. My research interests include financial econometrics & asset pricing. I am currently getting ready to conduct research this summer, and I have encountered a tricky question: Will grad schools care about empirical research? I have a few topics in mind, and each could be approached either theoretically or empirically. Even though I don't intend to become a pure theorist, do you think it would be more beneficial to do theoretical research at this point? Thanks for your input.

Princeton has a good program in this discipline, as do NYU and Columbia. I am not sure about the relative importance of GRE Verbal and TOEFL scores for any of them, though. There are a couple of other forums that are fairly active for these programs: http://www.wilmott.com http://www.global-derivatives.com

Hello everyone. I am planning on pursuing a PhD in mathematical finance, and I could use some advice. I've researched most departments in this field, but I'm not sure which kind of program would be a better fit. It seems that I have three basic options: Finance PhD (business school) Financial Engineering / OR PhD (engineering school) Financial Math PhD (math dept)My background is econ & math undergrad, econ masters, and my research interests involve mathematical methods & commodity markets. My math background is fairly strong (calc through multivar, ODE, linear algebra, stochastic processes, real analysis x 2, and prob theory), but it has some notable weaknesses (no topology or abstract algebra, so the math subject GRE looks ... challenging). My GPA is above 3.9, I'm a US citizen, and my target GRE scores are 800 quant, 700 verbal. Business schools don't appear to be strong in my areas of interest, as a rule. Currently, I'm leaning towards the engineering programs because they appear to be offer good research prospects, and I think I would have a decent shot at getting in. Some math departments (such as Carnegie Mellon & NYU) appear to be quite strong in these areas as well, but I'm not sure if I would have any chance at getting in. What do you think? What kind of program would be good for both research & admissions prospects? Thanks.

Hello all. I've been away for awhile, but I wanted to pose a question to the TM community: Consider the spectrum of research, from pure theory to applied theory to purely empirical studies. I have been considering finance, but this applies to all econ fields. Where do you think the most interesting research is being done? The most valid? The highest impact? Where do you think the best prospects lie? Not really looking for a definitive answer, just thoughts from a bunch of great people. Thnx.

Hey everyone. I'm currently investigating PhD Finance and Financial Engineering (typically within IEOR) programs in the US (business & engineering schools), and I would like to get some perspectives from current students & recent grads. Consider this any open invitation to vent/gush/comment on various departments & schools. Seriously, if all you have to say is 'Nice place, but the guy I wanted to work with was insane', I want to hear about it.

Can't comment on CMU, but I can give you a bit about Caltech. I looked into their 'department' and talked to a few people there. First, it's not a traditional econ department. They take poli sci instead of macro, and there is a lot of interdisciplinary research (econ, poli sci, and some neuroscience). Second, they are great within some areas and have nothing for others. Game theory, social networks, and empirical micro (for some specialities) are quite good. Macro is nonexistent, and financial econ appears similar. Their placement record is good, and they have rather good funding prospects. If you know what area you want to go into, and they are strong in it, Caltech may be a good bet. Otherwise, you should probably look for a department with broader research prospect.

I'm not sure of the relative strengths for the other fields, but, from what I have heard, the market in sociology is quite weak.

Thought I would wrap-up this thread. First, thnx to everyone for their advice. Second, here's what has happened: I talked to the profs, and they agree that I need real analysis (2 semesters would be good). I was told that optimization methods would not be worthwhile, and more analysis would be better than math stats. I was able to get a substitution for my degree requirement, so I will be taking 2 semesters of real analysis. My math courses will be: -calc through multivar, diff eq, linear algebra, stochastic processes, probability theory, & 2 semesters of real analysis So, happy ending (yay!).

mosfro - A couple of things. First, Harvard, and quite a few other top b-schools, do not have undergrad programs or courses. Thus, all of their students are either MBA or PhD/DBA. MBA students are typically not looking to continue their studies (see starting salary comparisons for business PhD and fresh MBA), so the pool is pretty small. As they are only teaching grad students, the demand for faculty is also relatively low. For finance, IMHO, a lot of the competition is because you need to be good in a quite a few areas to excel in a finance PhD: especially math, but also econ (understanding if not formal training), programming, and business. Just my 2c on that point.

I think that one reason there is so little action on the business boards is that the programs are tiny; for example, at HBS, it's 2006 entering class across all disciplines was only 21 people. Finance is especially competitive. On rankings, I haven't seen any. I work as a RA in a business school, and from what I have heard, the programs are rather heterogeneous. This makes consistent, meaningful rankings rather difficult.

camello - thnx. I'm graduating w/both degrees in 2008 after 4 yrs (currently a junior/some kind of master’s student), so the course lists are a combination of completed & upcoming. I had never thought about math stats that way (very good to know), and nice to hear about the degrees.

My bad. Questions are: (1) Of these courses, which would you say is the least important/best to drop for real analysis: stochastic processes, probability theory, mathematical stats (2)Would taking courses as a nondegree student after I graduate w/MA be a good way to get reqs done, or do adcoms prefer to see MSc?

I should be able to talk to the head of my school's fin math program within the next week or two; calls also sound good. Here's my binding constraint: If I add any more courses to my plan of study (including summer), I will lose a semester of financial aid (credit limits). Also, I can't reduce the number of econ classes (degree requirements). So, to take more math, my choices are (1) substitute math classes or (2) take courses as non-degree or MS student after I finish the BA/MA. For (1), optimization methods would be a primary candidate, if it weren't a degree requirement. Anything else that you think would be good to swap out? For (2), would non-degree be a good idea?