University of Washington - Master of Science in Computational Finance and Risk Management

MS Overview

Key takeaways

only 1 year program, fall semester provided
tuition fee $45,000
many interesting electives

Program

Fall

Deadline: February

Fees

$45,570

Prerequisites/requirements

Minimum admissions requirements

Calculus through partial differentiation, matrix algebra, and one-dimensional optimization
Probability and statistics at the level of an upper level undergraduate course or entry level graduate course
A programming language such as Java, C++, Python, or in a math or a statistics programming language such as MATLAB, R/S-PLUS

GRE/GMAT

optional

For reporting GRE scores, use 4854 (University of Washington) under Score Report Recipients. The Department code is not necessary. For reporting GMAT scores, use GMAT code 459-75-53.

Items for application

Academic transcripts from undergraduate or previous graduate education.
Statement of purpose, a current resume, and recommendation letters (two for online applicants; three for campus applicants).
Completed application forms and payment of $85 non-refundable application fee
Other items as identified by your application (e.g. proof of English proficiency)

Curriculum

Optional undergraduate-level preparatory courses

Mathematical methods for quantitative finance
Probability and statistics for computational finance
Introduction to financial markets
Introduction to computational finance and financial econometrics
R programming for quantitative finance

Mandatory MS-CFRM courses

Investment science
Financial data science
Asset allocation and portfolio management
Options and other derivatives
Monte Carlo methods in finance
Ethics in the finance profession

Required course option

Financial data access & analysis with SQL, VBA, Excel
Optimization methods in finance

Elective MS-CFRM courses

Special studies in computational finance
Financial software development and integration with C++
Machine learning for finance
Introduction to trading systems
Advanced trading systems
Advanced C++ for finance
FinTech, blockchain, and cryptocurrencies
Fixed income analytics
Portfolio performance analysis & benchmarking
Endowment and institutional investment management
Risk in financial institutions
Quantitative risk management
Credit risk management
Stochastic calculus for quantitative finance
Energy markets analytics and derivatives
Financial time series forecasting methods

Special CFRM electives

Independent research or study

Internship or CPT

Master’s thesis

Elective AMATH courses

AMATH 582 and 583 are acceptable elective courses in the CFRM MS program