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IMA Short Course
Tools for Modeling and Data Analysis in Finance/Asset Pricing
March 29-April 2, 2004


Probability and Statistics in Complex Systems: Genomics, Networks, and Financial Engineering, September 1, 2003 - June 30, 2004

IMA Public Lecture
Stephen Ross, Behavioral Finance - The Closed End Fund Puzzle,
March 30, 2004
Talks(A/V)    Talks(Audio)
Slides:   html    pdf    ps    ppt

Topics covered: This tutorial recounts the state of the art in asset pricing theory and modeling. In many cases, models can be crucial for decision-making and the allocation of financial resources. Investment banks, often the most efficient users of capital, manage their trading portfolios using simulation models calibrated to hundreds of traded instruments. These models are used to price illiquid instruments as well as to manage the exposure of the firms to market and credit risk. The result is a more efficient use of economic capital and, hopefully, a more transparent relation between financial institutions and regulators. Leading theoreticians and practitioners will lecture on the models used in the main asset classes.

Speakers:

Blaise G. Morton
EBF Funds
blaise.morton@ebf.com

Glenn J. Satty
Telluride Asset Management
gsatty@tridecap.com

Srdjan D. Stojanovic
Department of Mathematical Sciences
University of Cincinnati
http://math.uc.edu/~srdjan/

Carlos Fabian Tolmasky
University of Minnesota
tolmasky@math.umn.edu

Syllabus:

Options Pricing, Portfolio Hedging, and Data Analysis
Lecturer: Srdjan D. Stojanovic

1. Classical methods in options pricing and hedging. European options. Traditional derivation of the Black-Scholes PDE. Monte-Carlo verification of the derivation. Black-Scholes formula and extensions for time dependent data. Effect of continuous and instantaneous dividends. Numerical extensions for price dependent data. American options, optimal stopping, and (obstacle) free boundary problems. Numerical solutions.

2. Options data analysis. Options data. Elementary implied volatility. Derivation of the Dupire PDE and integral-differential equations. Non- elementary methods for implied volatility, and other parameter estimation problems in complete markets: optimal control of Dupire PDEs, integral- differential equations, and obstacle problems.

3. Optimal portfolio hedging. Merton's classical optimal portfolio theory for (linear) Log-Normal markets. Portfolio hedging formula under appreciation rate uncertainty for linear non-Markovian markets. Portfolio hedging for multi-factor non-linear Markovian markets. Hamilton-Jacobi-Bellman and Monge-Ampère PDEs in optimal portfolio hedging. Portfolio hedging for multi- factor non-linear Markovian markets under general affine constraints on the portfolio.

4. State of the art in options pricing and hedging. Stochastic volatility models. Market price of volatility risk. The general problem of option pricing in incomplete Markovian markets. Complete solution of the general option pricing problem in incomplete Markovian markets via optimal portfolio theory, and Monge-Ampère PDEs. Unique fair prices. Non-unique fair prices: price-spread. Black-Scholes and optimal options hedging in general incomplete markets.

Preprints:
StojanovicPreprintPortfolioFormula.pdf
StojanovicPreprintStochasticVolatility.pdf
StojanovicPreprintHypoellipticBlackScholes.pdf


Practical Aspects of Risk, Utility, and Derivative Valuation
Lecturer: Glenn J. Satty

1. Utility and Behavior: practical examples of why rational people behave differently whether or not they have the same information, and how utility and behavior impact financial markets and pricing of financial instruments.

2. Fundamental Intuition behind Derivative Pricing: reducing the Black-Scholes equation and its solution to a "trading intuitive" form, in order to understand how traders and risk controllers use the equations and formulae in their daily work.

3. Relationship between Γ and Θ: how a market maker risk manages a position in real time. In this section we discuss ways a market maker makes money on both short and long term positions. If time permits we will also discuss classical portfolio insurance and its effect on the market.

4. Topics on Demand: according to the group we can discuss other issues, including different dynamics in different markets, actual vs theoretical distributions, exotic options, or other topics of interest. If time permits we may have a mock trading session.


Derivatives in Commodity Markets
Lecturer: Carlos Fabian Tolmasky

1. Generalities. Consumption and non-consumption commodities. Storage. Arbitrage relationships. Convenience yield. Contango, backwardation. Seasonality. Futures and Swaps. Mechanics: exchange traded contracts, over-the-counter contracts. Basis risk. Hedging. Example: Metallgesellschaft.

2. Description of some market structures and participants: metals, grains, energy (petroleum, natural gas, electricity), weather.

3. More on Swaps. Vanilla Options on futures. Spread options: craks, crush and timespread options. Asian options and options on swaps.

4. Term structure models. One factor models. Stochastic convenience yield. Gibson and Schwartz model. Statistics of various futures and volatility curves. Multicurve markets, intra and inter curve correlations.

5. Petroleum market revisited: the market as a description of a refinery and its economics.

Slides:   Commod.pdf


Quantitative Methods for Pricing Fixed-Income Securities
Lecturer: Blaise G. Morton
(based on notes by Blaise Morton and Thomas Spiegel)

1. Introduction to Bonds and the Fixed-Income Markets. What is the market structure and who are the players. Basic models of Treasury Yield curves. Practical and philosophical issues with continuous yield curves. Back to reality with treasury, swap and agency dealer screens, quoting conventions. Treasury curve modeling techniques and basic analyses such as duration, convexity and the convexity bias. Understanding the shape of the treasury curve (following Ilmanen). A formula for expected bond return

2. Interest-Rate Swaps and the LIBOR Curve. Basic models. Building the LIBOR (rate) curve. Money market, interest-rate swaps and Eurodollar futures. The convexity bias in Eurodollar Futures (following Burghardt). The repo market -- Basic trades and determining fair value. Definitions of spread trading and fixed-income arbitrage.

3. Stochastic Models and Derivatives Pricing. Black's model applied to pricing interest-rate caps, floors. Binomial trees for pricing callable bonds using the option-adjusted spread (OAS). PDE pricing models based on stochastic differential equations, example: the first convertible bond model of Brennan and Schwartz. Market Models, example: swaption pricing.


SHORT COURSE SCHEDULE
Monday Tuesday
MONDAY, MARCH 29
All talks are in Lecture Hall EE/CS 3-180 unless otherwise noted.
8:30 Coffee and Registration

Reception Room EE/CS 3-176

9:15 Douglas N. Arnold and Scot Adams Welcome and Introduction
9:30-10:15 Part 1
10:15-10:30 Break Reception Room EE/CS 3-176
10:30-11:15 Part 2
11:15-1:30 Lunch break
1:30-2:15 Part 3
2:15-2:30 Break Reception Room EE/CS 3-176
2:30-3:15 Part 4
TUESDAY, MARCH 30
All talks are in Lecture Hall EE/CS 3-180 unless otherwise noted.
9:00 Coffee Reception Room EE/CS 3-176
Glenn J. Satty (Telluride Asset Management)
Practical Aspects of Risk, Utility, and Derivative Valuation
9:30-10:15 Part 1
10:15-10:30 Break Reception Room EE/CS 3-176
10:30-11:15 Part 2
11:15-1:30 Lunch break
1:30-2:15 Part 3
2:15-2:30 Break Reception Room EE/CS 3-176
2:30-3:15 Part 4
IMA Public Lecture
March 30, 2004 , Room 100 Smith Hall
5:00-6:30 pm Reception Lind Hall 400
7:00 pm
Room 100 Smith Hall
Stephen A. Ross
Massachusetts Institute of Technology

Behavioral Finance - The Closed End Fund Puzzle

Talks(A/V)    Talks (Audio)
Photo Gallery

Slides:   html    pdf    ps    ppt

WEDNESDAY, MARCH 31
All talks are in Lecture Hall EE/CS 3-180 unless otherwise noted.
9:00 Coffee Reception Room EE/CS 3-176

Carlos Fabian Tolmasky (University of Minnesota)
Derivatives in Commodity Markets

Slides:   Commod.pdf

9:30-10:15 Part 1
10:15-10:30 Break Reception Room EE/CS 3-176
10:30-11:15 Part 2
11:15-1:30 Lunch break
1:30-2:15 Part 3
2:15-2:30 Break Reception Room EE/CS 3-176
2:30-3:15 Part 4
THURSDAY, APRIL 1
All talks are in Lecture Hall EE/CS 3-180 unless otherwise noted.
9:00 Coffee Reception Room EE/CS 3-176
9:30-10:15 Part 1
10:15-10:30 Break Reception Room EE/CS 3-176
10:30-11:15 Part 2
11:15-1:30 Lunch break
1:30-2:15 Part 3
2:15-2:30 Break Reception Room EE/CS 3-176
2:30-3:15 Part 4
FRIDAY, APRIL 2
All talks are in Lecture Hall EE/CS 3-180 unless otherwise noted.
9:00 Coffee Reception Room EE/CS 3-176
9:30-10:15 Part 5
10:15-10:30 Break Reception Room EE/CS 3-176
10:30-11:15 Part 6
IMA/MCIM Industrial Problems Seminar
April 2, 2004 , EE/CS 3-180
1:25-2:15
Richard Derrig
(President, OPAL Consulting LLC, Visiting Scholar, Wharton School, University of Pennsylvania)

Mathematical Models for Insurance Fraud Detection

Paper: Fraud Classification Using Principal Component Analysis of RIDITs (pdf)

LIST OF CONFIRMED PARTICIPANTS

NAMEDEPARTMENTAFFILIATION
Vilen AbramovDepartment of Mathematics Kent State University
Scot AdamsInstitute for Mathematics and its Applications University of Minnesota, Twin Cities
Inkyung AhnDepartment of Mathematics Korea University
Hengjie Ai University of Minnesota, Twin Cities
Greg AndersonSchool of Mathematics University of Minnesota, Twin Cities
Valentin AndreevDepartment of Mathematics Lamar University
Douglas ArnoldInstitute for Mathematics and its Applications University of Minnesota, Twin Cities
Donald AronsonInstitute for Mathematics and its Applications University of Minnesota, Twin Cities
Sezai AtaSchool of Mathematics University of Minnesota, Twin Cities
Gerard AwanouInstitute for Mathematics and its Applications University of Minnesota, Twin Cities
Hee-Jeong BaekDepartment of Mathematics Seoul National University
Karen BallInstitute for Mathematics and its Applications University of Minnesota, Twin Cities
Antar BandyopadhyayInstitute for Mathematics and its Applications University of Minnesota, Twin Cities
Peter BankDepartment of Mathematics Humboldt-Universität
Camelia BejanDepartment of Economics University of Minnesota, Twin Cities
Slava Belyaev ITEP
Florin BidianDepartment of Economics University of Minnesota, Twin Cities
Hunt BlatzQuantitative Group Advantus Capital Management
Maury BramsonSchool of Mathematics University of Minnesota, Twin Cities
Olga BrezhnevaInstitute for Mathematics and its Applications University of Minnesota, Twin Cities
James Carson RisQuant Energy
Jamylle Carter University of Minnesota, Twin Cities
Zhiwei ChenDepartment of Mathematics University of Maryland
Dong Chung Sogang University
Pin ChungInvestment and Risk Management Chung ALM
Palahela (Daya) DayanandaDepartment of Mathematics University of St. Thomas
Richard Derrig Opal Intelligent Solutions
Gregory Duane University of Minnesota, Twin Cities
Yang Fan University of Minnesota, Twin Cities
Narryn FisherDepartment of Mathematics University of Maryland
Louis FortiDepartment of Energy Risk Trading CHS, Inc.
Liliane Forzani University of Minnesota, Twin Cities
Shmuel FriedlandDepartment of Mathematics, Statistics, and Computer Science University of Illinois, Chicago
Tim GaroniInstitute for Mathematics and its Applications University of Minnesota, Twin Cities
Urmi Ghosh-DastidarDepartment of Mathematics City University of New York
Victor GoodmanDepartment of Mathematics Indiana University
Elliot GootmanDepartment of Mathematics University of Georgia
Lawrence GraySchool of Mathematics University of Minnesota, Twin Cities
Matthew Gray Allianz Life Insurance Company Of North America
Marshall HamptonDepartment of Mathematics & Statistics University of Minnesota, Twin Cities
Chuan-Hsiang HanInstitute for Mathematics and its Applications University of Minnesota, Twin Cities
Silvia IorgovaInternational Capital Markets Department International Monetary Fund
Naresh JainSchool of Mathematics University of Minnesota, Twin Cities
Abu JalalDepartment of Finance University of Minnesota, Twin Cities
Dhandapani KannanDepartment of Mathematics University of Georgia
John KemperDepartment of Mathematics University of St. Thomas
Mohammad KhanDepartment of Mathematics Kent State University
Andy KimDepartment of Applied Economics University of Minnesota, Twin Cities
Bong KoDepartment of Mathematics Education Cheju National University
Thomas KurtzDepartment of Mathematics University of Wisconsin, Madison
Chang LeeSchool of Mathematics University of Minnesota, Twin Cities
Jeong LeeDepartment of Mathematics Seoul National University
Rodrigo LievanoDepartment of FMIS University of Minnesota
Mingyan LinSchool of Mathematics University of Minnesota, Twin Cities
Xiaoji LinDepartment of Finance University of Minnesota, Twin Cities
Dennis LuiWells Capital Management Wells Fargo
Huaqiang MaDepartment of Mathematics University of Maryland
Andy MackQuantitative Finance Department Telluride Asset Management
Hantao MaiDepartment of Mathematics University of Maryland
Richard McGeheeSchool of Mathematics University of Minnesota, Twin Cities
Andreas Michlmayr Patpatia & Associates
Oana MocioalcaDepartment of Mathematics Purdue University
Hamid MohtadiDepartment of Applied Economics University of Minnesota, Twin Cities
Blaise Morton EBF & Associates
Gary Nan TieInvestment Department The St. Paul Companies
J. Michael NealDepartment of Statistics University of Minnesota, Twin Cities
Amir NiknejadDepartment of Mathematics University of Illinois, Chicago
Glenn PedersonDepartment of Applied Economics University of Minnesota, Twin Cities
Thomas PetersDepartment of Computer Science University of Connecticut
Lea PopovicInstitute for Mathematics and its Applications University of Minnesota, Twin Cities
H. PradhanDepartment of Finance and Economics XLRI Jamshedpur
Huiyan QiuDepartment of Finance University of Minnesota, Twin Cities
Grzegorz RempalaDepartment of Mathematics University of Louisville
Stephen RossSloan School of Management Massachusetts Institute of Technology
Fadil SantosaInstitute for Mathematics and its Applications University of Minnesota, Twin Cities
Glenn Satty Telluride Asset Management
Arnd ScheelSchool of Mathematics University of Minnesota, Twin Cities
Jamie SeguinoCorporate Economics Ford Motor Company
A. SilvaDepartment of Physics University of Maryland
Mihai SirbuDepartment of Mathematical Sciences Carnegie Mellon University
Srdjan StojanovicDepartment of Mathematical Sciences University of Cincinnati
Marcelo TakamiDepartment of Research Central Bank of Brazil
Peter Tankov École Polytechnique
Carlos TolmaskyDepartment of Mathematics Cargill, Inc.
Pradyumna UpadrashtaDepartment of Scientific Computation University of Minnesota, Twin Cities
Hong WangDepartment of Civil Engineering University of Minnesota, Twin Cities
Jing WangInstitute for Mathematics and its Applications University of Minnesota, Twin Cities
Xiaodi WangDepartment of Mathematics Western Connecticut State University
Yuhong YangDepartment of Statistics Iowa State University
Ofer ZeitouniSchool of Mathematics University of Minnesota, Twin Cities
Bing ZhangDepartment of Mathematics University of Maryland
Tao ZhangDepartment of Mathematics Purdue University
Yuming ZhangDepartment of Mathematics University of Maryland
Jun ZhaoInstitute of Mathematics and its Application University of Minnesota, Twin Cities
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