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• Computational Finance Seminars in MSCS at UIC

• Finance Workshop in CBA at UIC, every 2nd Thursday 2-3:30pm in 2250UH

• 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.

• 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, 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 Lipton-Lifschitz (alex.lipton@csfb.com), Department of Mathematics, Statistics, and Computer Science,
  and Global Modelling & Analytics Group, CREDIT SUISSE | FIRST BOSTON, New York, NY.
  • Financial Engineering
  • Fluid Dynamics
  • Mathematical Physics
    
    

• Professor Stanley R. Pliska, 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, 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

Fall 2002 Courses

MISI Computational Financial Mathematics Track:

• Fin 551 Financial Decision Making, Fall 2002, S. R. Pliska,
  
  • Time Table: 53890 LECD 1230-0145 M W 0337 BSB

  • 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. Additional information about the book and the course (which is being taught this spring) can be found on Professor Pliska's web page.

MISI Computational Financial Mathematics Track:

• Math 586 Computational Finance, Spring 2002, Prof. Charles Tier
  • TIMETABLE: 18165 LECT 0200-0250 M W F 0309 TH
  • COURSE DESCRIPTION: Finance is one of the fast growing areas in the corporate world. Along with this, the explosion in financial instruments has led ot the development of new mathematical models and methods for their analysis. The course begins with a review of financial derivatives and their applications. Models of financial derivatives will be presented such as Black-Scholes model. The approach will be baseed on partial differential equations using analytic and numerical methods.
  • PREREQUISITES: Background in differential equations and introductory probability or consent of the instructor.
  • TEXT(S): Wilmot, Howison, and Dewynne, The Mathematics of Financial Dervatives; A Student Introduction, Cambridge University Press.

MISI Computational Financial Mathematics Track:

• Fin 571 Empirical Issues in Finance, Fall 2001, Prof. Gilbert W. Bassett, Jr.
  • TIMETABLE: 49552 LECD 0300-0415 M W 0369 BSB
    (Time could change due to conflict with a PhD Economics Course)
  • COURSE DESCRIPTION: he methodology used in analyses of market efficiency, asset pricing and capital allocation.
  • PREREQUISITES: Fin 500 and consent of the instructor.

MISI Computational Financial Mathematics Track:

• Math 590 Advances Topics in Applied Mathematics: Computational Finance, Spring 2001, Prof. Charles Tier
  • TIMETABLE: 62915 LECD 0300-0415 M W 0208 TH
  • COURSE DESCRIPTION: Finance is one of the fast growing areas in the corporate world. Along with this, the explosion in financial instruments has led ot the development of new mathematical models and methods for their analysis. The course begins with a review of financial derivatives and their applications. Models of financial derivatives will be presented such as Black-Scholes model. The approach will be baseed on partial differential equations using analytic and numerical methods.
  • PREREQUISITES: Background in differential equations and introductory probability or consent of the instructor.
  • TEXT(S): Wilmot, Howison, and Dewynne, The Mathematics of Financial Dervatives; A Student Introduction, Cambridge University Press.
  • URL for MCS590 WEBPAGE: http://www.math.uic.edu/~tier/Finance/

• Math 590 Advanced Topics in Applied Mathematics: Principles of Financial Mathematics, Spring 2001, Prof. Stephen S. T. Yau,
  • TIMETABLE: 62907 LECD 1100-1150 M W F 0303 AH
  • PREREQUISITES: Approval of the Department. Graduate Standing Required.
  • TEXT(S): S. N. Neftci, An Introduction to the Mathematics of Financial Derivatives , Academic Press.
  • COURSE DESCRIPTION: Continuation of Spring 2000 course that started with 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. Black-Scholes Differential Equation, The Market Price of Risk.
  • Comment: Section is CLOSED

Fall 2000 Courses

MISI Computational Financial Mathematics Track:

• Fin 551 Financial Decision Making, Fall 2000, S. R. Pliska,
  
  • Time Table: T Th 4:15-5:30, Call Number: 59819

  • 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. Additional information about the book and the course (which is being taught this spring) can be found on Professor Pliska's web page.

• Fin 571 Empirical Issues in Finance. Gilbert W. Bassett, Jr.
  
  • Time Table: MW 3:00-4:15, Call Number: 59822

  • 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. There will be a required research paper. Students will be assumed to have taken econometrics and statistical courses at the level of Economics 534 and 535.

• Math 590 Advanced Topics in Applied Mathematics: Principles of Financial Mathematics, Fall 2000, Prof. Stephen S. T. Yau,
  • TIMETABLE: 75266 LECD 1200-1250 M W F 0316 BH
  • PREREQUISITES: Approval of the Department. Graduate Standing Required.
  • TEXT(S): S. N. Neftci, An Introduction to the Mathematics of Financial Derivatives , Academic Press.
  • COURSE DESCRIPTION: Continuation of Spring 2000 course that started with 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. Black-Scholes Differential Equation, The Market Price of Risk.
  • Comment: Section is CLOSED

Spring 2000 Courses

MISI Computational Financial Mathematics Track:

• Fin 551 Financial Decision Making I, Spring 2000, Prof. S. R. Pliska.
  • TIME: 21966 LECD 0415-0530 T R 0335 BSB
  • COURSE DESCRIPTION: First foundation course for the study of modern financial economics. Two-period individual consumption and portfolio decisions under uncertainty and their implications for the valuation of securities
  • PREREQUISITES: Consent of the instructor. This course is intended for both MBA students and grad students from the math department. Besides an interest in finance, students should be familiar with calculus, elementary probability theory, and linear algebra. Some introductory knowledge of stochastic processes and optimization theory, especially linear programming, would be helpful but is not mandatory. It would not hurt to have had a course or two in finance and/or economics.
  • TEXT: Introduction to Mathematical Finance: Discrete Time Models by Stanley R. Pliska, Blackwell Publishers. The class will cover most of this book. Information about my book, including the Table of Contents, can be found on my web page http://www.uic.edu/~srpliska/IntroMF.html.
  • COMMENTS: Overview: The aim is to learn some basic theory about financial markets, especially the financial economic theory associated with derivatives and portfolio management. Although this material will be presented in a mathematically rigorous fashion, by studying discrete time models of securities the level of math will be kept relatively elementary. Nevertheless, we will be studying principles are of fundamental importance, namely, principles that play important roles in the modern financial industry. This course is intended for students who like mathematical economics, quantitative subjects in finance like futures and options, and financial engineering. It is ideal for students who are intending to subsequently take more advanced courses in the area of mathematical finance.

• Math 590 Advances Topics in Applied Mathematics: Financial Mathematics on Options Pricing, Spring 2000, Prof. S. S. T. Yau
  • TIME: 61916 LECD 1200-1250 M W F 0212 TH
  • PREREQUISITES: Calculus
  • TEXT(S): S. N. Neftci, An Introduction to the Mathematics of Financial Derivatives , Academic Press.
  • COURSE 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. Black-Scholes Differential Equation, The Market Price of Risk.
  • COMMENTS: I shall keep the prerequisites as small as possible, i.e., the course will be more of less self-contained. However, it is good to have exposure in probability and differential equations.

Fall 1999 Courses

MISI Computational Financial Mathematics Track:

• Math 590 Advances Topics in Applied Mathematics: Financial Mathematics, Prof. C. Tier
  • Call/Time/Place: 65595 LECD 1200-1250 M W F 0307 AH
  • COURSE DESCRIPTION: Finance is one of the fast growing areas in the corporate world. Along with this, the explosion in financial instruments has led ot the development of new mathematical models and methods for their analysis. The course begins with a review of financial derivatives and their applications. Models of financial derivatives will be presented such as Black-Scholes model. The approach will be baseed on partial differential equations using analytic and numerical methods.
  • PREREQUISITES: Background in differential equations and introductory probability or consent of the instructor.
  • TEXT(S): Wilmot, Howison, and Dewynne, The Mathematics of Financial Dervatives; A Student Introduction, Cambridge University Press.
  • URL for MCS590 WEBPAGE: http://www.math.uic.edu/~tier/Finance/

• Fin 571 Empirical Issues in Finance, Prof. Gilbert W. Bassett, Jr.
  • TIME: 07156 LECD 0600-0830PM W 0335 BSB
  • COURSE DESCRIPTION: The methodology used in analyses of market efficiency, asset pricing and capital allocation.
  • PREREQUISITE: Fin 500 Introduction to Corporate Finance, Graduate Standing Required, and Consent of the Instructor.

• 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 Black-Scholes 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.

• 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, Gauss-Seidel, successive over-relaxation, conjugate gradient, Lax-Wendroff, 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 Strum-Liouville 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. Black-Scholes Differential Equation, The Market Price of Risk.

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Mathematical and Information Sciences for Industry (MISI) Courses

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