IUBio

New Computational Finance Program

Computational Finance compfin at cse.ogi.edu
Mon Jun 17 12:58:57 EST 1996


Computational Finance at the Oregon  Graduate  Institute  of
Science & Technology (OGI)

A Concentration in the MS Programs of
         Computer Science & Engineering (CSE)
         Electrical Engineering & Applied Physics (EEAP)

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20000 NW Walker Road, PO Box 91000, Portland, OR  97291-1000
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Program Overview

Today's technology has increased the level of technical pro-
ficiency required in the financial markets. At one time, for
example, spreadsheet skills  and  a  good  understanding  of
financial  instruments  were  all  that were needed to build
practical derivative  pricing  tools.  Today,  leading  edge
financial  institutions  routinely  use  advanced techniques
from engineering and computer science computers  to  create,
price, and manage risk for new instruments.

Computers of today are powerful enough to analyze  and  make
decisions  based  on real-time data (tick-by-tick). Further-
more, modern data analysis tools can consider many variables
simultaneously  and  capture complicated and often nonlinear
inter-dependencies between variables. This has opened up new
modeling possibilities for hedging, derivatives instruments,
and decision making.

At OGI, the demand within the financial industry for techni-
cally  competent graduates that are well versed in state-of-
the-art analysis techniques is addressed by an intensive  12
month  Computational Finance program. The program is offered
as a concentration in both the Computer Science &  Egnineer-
ing  (CSE),  and  Electrical  Engineering  & Applied Physics
(EEAP) departments. The program leads to a Master of Science
degree  in  Computer Science and Engineering (CSE track), or
in  Electrical  Engineering  (EEAP   track).   Computational
Finance  courses  are also cross-listed in the Management of
Science & Technology (MST) program.

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The Computational Finance Program is:
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   * An intensive 12 month track directed at training  scen-
     tists, engineers, and financial professionals in the theory
     and  practice of advanced quantitative financial analysis.
   * An attractive alternative to a standard 2 year MBA, for
     highly motivated and technically  sophisticated  students
     who are considering a career in quantitative financial
     analysis.
   * A way of gaining a solid foundation in finance,  cover-
     ing material equivalent to 3 semesters  of  MBA  level
     finance  and beyond, in only 3 quarters. Finance courses
     are taken  in  parallel  with demanding engineering and
     computer science courses, and the  program is not
     recommended for students  without  mathematical  skills
     corresponding to an undergraduate degree in a  scientific
     or technical field.
   * Based on a solid foundation in relevant data analysis and
     signal processing techniques from Computer Science,
     Electrical Engineering, and Statistics. These techniques
     are utilized for modeling financial markets and developing
     investment analysis, trading, and risk management systems.
   * Geared towards adaptive and nonlinear signal processing
     tools, like artificial neural networks.
   * Strongly project oriented, using state-of-the-art  com-
     puting facilities and live/historical financial market data
     provided by Dow Jones Telerate. Students are exposed to tools
     and trading environments that reflect the modern facilities
     at a typical Wall Street trading firm.  Students are also
     trained in using high  level  numerical, and analytical
     packages, such as MatLab, Mathematica, SPlus, and Expo, for
     analyzing and modeling financial time series.

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Admission Requirements
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Admission requirements are the same as the general  require-
ments  of  the  institution. GRE scores are required for the
12-month concentration in  Computational  Finance,  although
they can be waived under certain circumstances.

A candidate must hold a bachelor's degree in  computer  sci-
ence,  engineering, mathematics, statistics, one of the bio-
logical or physical sciences, finance, or one of the quanti-
tative social sciences.

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Contact Information
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For more information, contact

 Program Information                  Admission Information
  E-mail: CompFin at cse.ogi.edu            Betty Shannon, Academic
  WWW:                                           Coordinator
  http://www.cse.ogi.edu/CompFin/        Computer Science and
                                         Engineering Department
                                         Oregon Graduate Institute
                                         of Science and Technology
                                         P.O.Box 91000
                                         Portland, OR 97291-1000

                                         E-mail:
                                         academic at cse.ogi.edu
                                         Phone: (503) 690-1255

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