Hi y'all - this is a somewhat long post, but hope you'll help me out anyways!
I've been admitted to Pricenton's MFin program next year. I am going to do it in one year, so I need to work together a plan so I can get the most out of the program. If someone out there has done the program, please help me out, but I could certainly also use help from the rest of you.
I have to do either two or three electives besides the first year core courses (one in time series, one in asset pricing and maybe a third core course in financial investments, but I'm probably going to do an elective instead of that). I am going to do a course in computational finance - so far, so good.
But what about the one/two others? I am an econ grad from europe, meaning that I've done quite a lot of maths compared to fx an american econ. I've done linear algebra, ode's and optimization. I've also had two theoretical statistics courses, and three econometrics courses after that, taking me through most basic probability and statistics concepts. Next to my studies, I've done some courses at the department of mathematics. I started out doing a course in introductory real analysis (convergence concepts, intro. metric spaces and topology and epsilon-delta proofs). After that, I've done a course in ODE's, and two courses in measure theoretical based probability, although a tight schedule didn't allow me to do these courses as focused as I use to, resulting in grades above average instead of in the absolute top. I've also done some introductory stochastic calculus.
I want to do some more probability. The MFin offers two courses with descriptions below:
ORF 526
Stochastic Modeling
Fundamental models of random phenomena in financial engineering and operations research: Poisson processes, Markov chains, Brownian motion, and diffusion processes.
Sample Reading List:
E. Cinlar , Introduction to Stochastic Processes
S. Ross , Introduction to Probability Models
S. Karlin & H. Taylor , A First Course in Stochastic Processes
Grimmett and Stirzaker , Probability and Random Processes
H. M. Taylor and S. Karlin , An Introduction to Stochastic Modeling (3rd Edition)
</B>and:
ORF 551/APC 551
Probability Theory
Graduate introduction to probability theory: measure spaces, expectation, sigma-algebras, conditioning; convergence concepts and laws of large numbers; stochastic processes, filtrations, and stopping times; Poisson random measures, Brownian motion, and martingales.
Sample Reading List:
Cinlar , Lecture Notes on Probability
Neveu , Foundations of Calculus of Probabilities
Chung , A Course in Probability Theory
Breiman , Probability
my question is now which one you think I should follow? I'm thinking about doing the second one, which is the harder one - actually, most student take 526, and then follow up with 527 (a course in introductory stoch. calc. for finance) before doing 551. Do you think I will be able to follow that with my background?
If anyone has some good advise for me regarding other issues while doing my course (from own experience or so), please write it
Thanks!
I've been admitted to Pricenton's MFin program next year. I am going to do it in one year, so I need to work together a plan so I can get the most out of the program. If someone out there has done the program, please help me out, but I could certainly also use help from the rest of you.
I have to do either two or three electives besides the first year core courses (one in time series, one in asset pricing and maybe a third core course in financial investments, but I'm probably going to do an elective instead of that). I am going to do a course in computational finance - so far, so good.
But what about the one/two others? I am an econ grad from europe, meaning that I've done quite a lot of maths compared to fx an american econ. I've done linear algebra, ode's and optimization. I've also had two theoretical statistics courses, and three econometrics courses after that, taking me through most basic probability and statistics concepts. Next to my studies, I've done some courses at the department of mathematics. I started out doing a course in introductory real analysis (convergence concepts, intro. metric spaces and topology and epsilon-delta proofs). After that, I've done a course in ODE's, and two courses in measure theoretical based probability, although a tight schedule didn't allow me to do these courses as focused as I use to, resulting in grades above average instead of in the absolute top. I've also done some introductory stochastic calculus.
I want to do some more probability. The MFin offers two courses with descriptions below:
ORF 526
Stochastic Modeling
Fundamental models of random phenomena in financial engineering and operations research: Poisson processes, Markov chains, Brownian motion, and diffusion processes.
Sample Reading List:
E. Cinlar , Introduction to Stochastic Processes
S. Ross , Introduction to Probability Models
S. Karlin & H. Taylor , A First Course in Stochastic Processes
Grimmett and Stirzaker , Probability and Random Processes
H. M. Taylor and S. Karlin , An Introduction to Stochastic Modeling (3rd Edition)
</B>and:
ORF 551/APC 551
Probability Theory
Graduate introduction to probability theory: measure spaces, expectation, sigma-algebras, conditioning; convergence concepts and laws of large numbers; stochastic processes, filtrations, and stopping times; Poisson random measures, Brownian motion, and martingales.
Sample Reading List:
Cinlar , Lecture Notes on Probability
Neveu , Foundations of Calculus of Probabilities
Chung , A Course in Probability Theory
Breiman , Probability
my question is now which one you think I should follow? I'm thinking about doing the second one, which is the harder one - actually, most student take 526, and then follow up with 527 (a course in introductory stoch. calc. for finance) before doing 551. Do you think I will be able to follow that with my background?
If anyone has some good advise for me regarding other issues while doing my course (from own experience or so), please write it
Thanks!
