Computational Finance Graduate Courses
and Other Information at UIC
{For Admission and related information, please contact:
Ms. Kari A. Dueball, Assistant Director of Graduate Studies,
kdueball@uic.edu,
Phone: 13124132175, Department of Mathematics, Statistics, &
Computer Science (M/C 249), 851 S. Morgan, Chicago, IL 606077045}
{Caveat Usor Disclaimer: Please check the University
TimeTable for the Course Official Time Schedule}
Quick Takes:

Courses

Seminars

ComputationalFinanceTrackOptions

Faculty


MISI

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UIC Finance Seminars
UIC Computational Finance Options

UIC MSCS Computational Finance Options:
Webpage version of Department MSCS hand out describing
the Computational Finance Track Options for Master's Degree in MISI,
Master's Degree in Mathematics with the Applied Math Option, and the
Ph.D. Degree in Mathematics with the Applied Math Option, as well as
other information on faculty and track or collateral courses.

Graduate Admission Application Procedures and Deadlines:
Webpage for Admission Applications, but see main
Graduate Studies page links for more information.
Computational Finance Track Faculty

Professor Gilbert W. Bassett, Jr., Department of Finance
(also Professor of Economics),
 Econometrics
 Statistics, Financial Markets
 Energy and the Environment
 Decision, Risk, and Voting
 Statistics and Sports

Professor Jerry L. Bona,
Department of Mathematics, Statistics, and Computer Science
 Mathematical Economics
 Fluid Mechanics
 Partial Differential Equations
 Numerical Analysis
 Oceanography.

Professor Floyd B. Hanson (RETIRED),
Department of Mathematics, Statistics, and Computer Science
 Portfolio Optimization Subject to Jump Events
 Computational Finance and Financial Engineering
 Computational Stochastic Control
 Stochastic Modeling Applications
 Mathematical Bioeconomics

Professor Charles Knessl,
Department of Mathematics, Statistics, and Computer Science
 American Options and Free Boundary Problems
 Stochastic Modeling
 Asymptotic methods
 Singular perturbation
 Queueing Theory

Adjunct Professor Alexander LiptonLifschitz (RETIRED),
Department of Mathematics, Statistics, and Computer Science,
and US Manager of Equity Derivatives, Convertible Unit and Global FX,
in Global Modelling & Analytics Group, of Credit Suisse First Boston LLP,
New York, NY.
 Financial Engineering
 Fluid Dynamics
 Mathematical Physics

Professor Stanley R. Pliska (RETIRED),
Department of Finance
 Risk Sensitive Portfolio Management
 Dynamic Asset Allocation with Imperfect Information
 Portfolio Management with Taxes and Transaction Costs
 Interest Rate Derivatives and Term Structure Models

Professor Charles Tier (RETIRED),
Department of Mathematics, Statistics, and Computer Science
 Analysis of Stochastic Models
 Queuing Theory
 Financial Mathematics
 Numerical Analysis

Professor Stephen S. T. Yau,
Department of Mathematics, Statistics, and Computer Science
 Control
 Information Theory
 Financial Mathematics
Spring 2005 Courses
Fall 2004 Courses
Spring 2004 Courses
Fall 2003 Courses
Spring 2003 Courses
Computational Finance Core Courses
 Fin 551 Financial Decision Making, Stanley R. Pliska
Description: This course will cover much of Professor
Pliska's book Introduction to Mathematical Finance, which as the name
suggests is a theoretical yet introductory study of security markets
including stocks, bonds, futures, and options. Considerable attention
will be. given to topics in financial economics such as arbitrage, risk
neutral valuation of derivative securities, and optimal
consumption/investment problems where the objective is to maximize
expected utility. Although the course will involve mathematics
presented in a rigorous fashion, the only mathematical prerequisites
are knowledge about probability, calculus, linear algebra, and
optimization, so economics students who have completed the first year
of graduate study should be well qualified. No particular courses in
finance are prerequisites, but students should come with an interest in
financial markets.
 Math 586 Computational Finance, Charles Tier
Description: The course begins with a review of financial
derivatives and their applications. Models of financial derivatives
will be presented such as BlackScholes model. Models of exotic options
as well as interest rate products will be studied in depth. The
approach will be based on partial differential equations using analytic
and numerical methods.
Computational Finance Track Collateral or Elective Courses
 Fin 571 Empirical Issues in Finance, Gilbert W. Bassett, Jr.
Description: The course will cover empirical applications
focusing on financial equity data. The course will introduce robust
statistical methods, compare them to standard methods, and present
their application to problems in Finance. Problems to be considered
include the predictability of asset returns, analysis of market
microstructure, multifactor models for predicting returns, risk neutral
distributions implicit in options prices, and forecasting portfolio
tracking error.
 Math 574 Applied Optimal Control. Floyd B. Hanson.
Description:
Introduction to optimal control theory; calculus of variations, maximum
principle, dynamic programming, feedback control, linear systems with
quadratic criteria, singular control, optimal filtering, stochastic
control.
 Math 584 Applied Stochastic Models. Charles Knessl.
Description:
Applications of stochastic models in chemistry, physics, biology,
queueing, filtering, and stochastic control, diffusion approximations ,
Brownian motion, stochastic calculus, stochastically perturbed
dynamical systems, first passage times.
 MCS 571 Numerical Methods for Partial Differential Equations. Floyd
B. Hanson.
Description:
Finite difference methods for parabolic, elliptic, and hyperbolic
differential equations: explicit, Crank Nicolson implicit, alternating
directions implicit, Jacobi, GaussSeidel, successive overrelaxation,
conjugate gradient, LaxWendroff, Fourier stability.
 Math 480 Applied Partial Differential Equations. Various
Instructors.
Description:
Initial value and boundary value problems for second order linear
equations, Eigenfunction expansions and StrumLiouville theory, Green's
functions, Fourier transform,. Characteristics,. Laplace transform.
 Math 590 Principles of Financial Mathematics, Stephen S. T. Yau
Description: 1. Probability Theory, 2. Financial
Instruments, 3. Basic Principles of Asset Evaluations, 4. One Period
Asset Valuation, One Period Pricing Model, 5. Discrete Time Model,
Arbitrage and Martingales, Complete Markets, 6. American Options,
Supermartingales and Snell Envelope, Stopping Time, Decomposition of
Supermartingales, 7. Continuous Time Model for Stock Prices, Brownian
Motion, Continuous Martingale Stochastic Calculus, 8. BlackScholes
Differential Equation, The Market Price of Risk.