MS in Financial Engineering

Columbia University

New York, New York, USA
MS in Financial Engineering
Duration12 Months
LevelMasters Program
  • Financial Engineering is a multidisciplinary field involving financial theory, engineering methods, mathematical tools, and programming
  • It is designed for students who wish to work in industries such as securities, banking, and financial management and consulting, or general manufacturing and service firms
  • The first half of the program is devoted to tools of the trade and their use in modeling financial markets and instruments
  • The MSFE curriculum includes courses in stochastic processes, optimization, numerical techniques, Monte Carlo simulation, and data analysis
  • Students make use of these methods in portfolio theory, derivatives valuation, and financial risk analysis
  • The second half gives students an opportunity to take more advanced courses or study specialized topics, ranging from models of the term structure of interest rates to a study of the implied volatility smile, as well as a course on applications programming for financial engineering
  • The program offers seven concentrations, including:
    • Asset Management
    • Computation & Programming
    • Computational Finance/Trading Systems
    • Derivatives
    • Finance & Economics
    • Financial Technology
    • Machine Learning for Financial Engineering
Fees componentsAmount
Tuition & fees5790061 INR
Hostel & Meals1496733 INR
Insurance269230 INR
Transportation83713 INR
International Student Fee16113 INR
Document Fee7690 INR
Health Service Fee 89353 INR
Facilities Fee 77781 INR
SEAS Graduate Student Activity Fee29296 INR
Books & Supplies 153804 INR
Personal Expenses 395496 INR
Total2619209 INR

Entry Criteria

Class 12thNo specific cutoff mentioned
Bachelors3.0 GPA
  • The basic requirement for admission as a graduate student is the bachelor's degree received from an institution of acceptable standing
  • Background in engineering, mathematics, computer science, statistics, economics, finance, or other similar quantitative fields
  • Applicants should have a solid foundation in mathematics, including multivariate calculus, linear algebra, and probability and statistics
  • A 3.0 (out of 4) GPA is preferred. Most successful applicants have a GPA higher than 3.0
  • The applicant will have majored in the field in which graduate study is intended, but in certain programs preparation in a related field of engineering or science is acceptable
  • The applicant will be admitted only if the undergraduate record shows promise of productive and effective graduate work
  • Consideration for admission will be based not only on the completion of earlier courses of study but also upon the quality of the record presented and upon such evidence, as can be obtained concerning the candidate's personal fitness to pursue professional work
ExamsTOEFL: Accepted
  • There are no minimum test score requirements to apply for admission consideration.  However, it may be necessary to improve your English proficiency if the applicant scored: 99 or lower

IELTS: Accepted
  • There are no minimum test score requirements to apply for admission consideration. However, it may be necessary to improve English proficiency if applicants scored: 6.5 or lower

PTE: Accepted
  • There are no minimum test score requirements to apply for admission consideration. However, it may be necessary to improve English proficiency if applicants scored: 68 or lower

GRE: Accepted
  • There are no minimum test score requirements to apply for admission consideration
  • The average GRE quantitative scores for past entering classes, in recent years, rank around 91%. Therefore, it is recommended that the applicant's scores in this section be comparable

Additional info
  • Applicants may be asked to participate in an interview as part of the application process
  • Work experience: While not required, the university does recommend that prospective students have some professional experience, either in the form of a full-time position or an internship
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