Financial Modeling and Optimization-Course Syllabus

RM 392- unique # 04305

TTh 2:00-3:30, GSB 3.106

Fall 2011

 

 

Instructor

 

Leon S. Lasdon

Office Phone:  471-9433

E-Mail:  lasdon@mail.utexas.edu

Office:  CBA North 5.244

Office hours:  TTh 3:30-5:00 or by appointment

Teaching Assistant:  TBA

TA e-mail: TBA

TA Office:  TBA

Course web page:  www.utexas.edu/courses/lasdon, and our web page on UT’s “Blackboard” system.

 

Course Topics

 

1.      The Process of Modeling

1.1       A six-stage framework

1.2       The craft of modeling

1.3       Visual modeling tools

1.4       Spreadsheet engineering

1.5       Analysis using spreadsheets

2.      Financial Statement Modeling

2.1       Basics: income statements, balance sheets, cash flow, etc

2.2       Applications: PPG Corporation

3.      Single Period Random Cash Flows

3.1       Mean-variance portfolio theory

3.2       Capital asset pricing model

3.3       Variants of mean-variance models: factor models, arbitrage pricing theory, model parameter estimation

3.4       Utility theory

4.      Multiperiod models

4.1       Optimal portfolio growth

4.2       General investment evaluation

5.       Derivative Securities

5.1       Forwards, futures, and swaps

5.2       Models of asset dynamics

5.3       Basic options theory

6.      Fixed income securities

 

Software Used

 

Learn to use state of the art optimization and simulation software including the following:

1.      Excel and the Excel Solver for optimization

2.      @RISK for Monte Carlo Simulation

3.      Precision Tree for Decision Tree analysis

4.      The GAMS algebraic modeling language.

This software, and the concepts underlying it, has applications in all areas of business.

 

This course is designed for MBA students, engineers, operations research students, computer scientists, and others who are interested in quantitative methods and their application to finance and investing. The level of mathematics used in the course is fairly basic-algebra, elementary calculus, and basic probability and statistics.  You also need the ability to think logically and systematically, but improving this ability is a course goal.

 

Instructional Methods

 

The basic approach is to learn by doing.  We will organize small learning groups, who work together to solve problems in class.  These problems are stated on the plan for each class.  Last year’s plans are on the course website, and are a reasonable guide to those used in the current year.  We then discuss the problem solutions.  This is interspersed with lecture segments when needed.  There will also be occasional outside speakers, who will explain how they use course topics in their work.

 

Course Materials

 

The text is “Financial Modeling” by Simon Benninga, MIT Press, 3rd edition, 2008.  It is available at the Co-op or online and should be purchased by each student or group of students.  The author is a professor in Finance at Wharton.

A second book, “Financial Models Using Simulation and Optimization III” by Wayne Winston, Palisade Corp (pub), 3rd edition, 2010, will provide many problems and cases, all framed as Excel spreadsheet models, provided on a CD-ROM which accompanies the book.   The CD-ROM also includes full trial versions of the PALISADES Excel add-in software @RISK (for Monte Carlo simulation), PRECISION TREE (for decision tree analysis), and EVOLVER, a genetic algorithm for optimization that can solve non-smooth and discrete problems. This book and its 68 excellent examples provide problem templates and solution software which many students will be able to apply in their future careers.  Although individual purchase is encouraged, one copy may be purchased and shared by each learning group.  It is available at online vendors.

 

 

 

Grading

 

There will be a midterm exam counting 30%, and a term project selected by the student and approved by the instructor counting 30%.  Cases and homework count 40%. 

 

Tentative Schedule of Topics

 

Class #

Topic

Text Chapters and pages

Other book Chapters and pages

Readings

Cases and Exams

1

Introduction, modeling framework

 

 

Art of modeling Ch 1

 

2

Craft of modeling

 

 

Art of modeling Ch 1, 2

Begin case 1

3

Excel and Spreadsheet Engineering

 

 

Art of modeling Ch 3-6

 

4

Racquetball case, Financial statement modeling

Ch 3

 

Art of modeling Ch 3-6

 

5

Case 1 presentations

 

 

 

Case 1 due

6

Financial statement modeling

Ch 3

 

 

 

7

Financial statement modeling

Ch 3

 

 

Begin case 2

8

Financial statement modeling

Ch 3

 

 

 

 

9

 Financial statement modeling

Ch 4

 

 

 

10

Financial statement modeling  

Ch 4, 5

 

 

 

 

11

Asset allocation

Ch 8

 

 

 

12

Asset allocation

Ch 8

 

 

Case 2 due,begin Case 3

13

Asset allocation

Ch 10

 

 

 

14

Asset allocation

Ch 12

Winston Ch 10

 

 

15

Scenario approach and other risk measures Asset allocation

 

Winston Ch 10

Quadratic programming, 3scen.xls

Mid-term exam

16

Case 3 presentations, asset allocation

 

 

 

 

17

Factor Models

Scenario approach and other risk measures

 

Winston, Ch 47, 49, 50

 

 

18

Factor models

Black-Litterman approach

Ch 13

 

 

Case 3 due

19

Black-Litterman approach, portfolios of  oil and gas E&P projects

 

 

Papers under readings/E&P project portfolios

Begin case 4

20

Modeling oil and gas E&P projects and selecting project portfolios

 

Winston Ch 19, 53

Papers under readings/E&P project portfolios

 

 

21

Scenario generators for oil and gas projects

 

Winston Ch 42

Papers under readings/E&P project portfolios

 

22

Risk measures other than variance,

Scenario generators for oil and gas projects

 

 

Papers under readings/E&P project portfolios

Case 4 due

23

Project portfolios: scenario generation and portfolio optimization

 

Winston Ch 43

Papers under readings/E&P project portfolios

 

24

Project portfolio optimization, lognormal stock price models,VAR

 Ch 18

Winston Ch 44-47

Papers under readings/E&P project portfolios

 

25

VAR, multiperiod portfolio models

 

 

Papers under readings\multiperiod portfolio models

 

26

Multiperiod models-scenario generation

 

 

Winston Ch 44-46

Papers under readings\multiperiod portfolio models

 

27

Multiperiod models-scenario generation

 

 

Winston Ch 44-46

Papers under readings\multiperiod portfolio models

 

28

Review, discussion of term projects

 

 

 

Term projects due during finals week

 

________________________________________________________________________

 

The University of Texas at Austin provides upon request appropriate academic accommodations for qualified students with disabilities. For more information, contact the Office of the Dean of Students at 471-6259.

 

By UT Austin policy, you must notify me of your pending absence at least fourteen days prior to the date of observance of a religious holy day.  If you must miss a class, an examination, a work assignment, or a project in order to observe a religious holy day, you will be given an opportunity to complete the missed work within a reasonable time after the absence.

 

Policy on Academic Integrity:
Students who violate University rules on academic dishonesty are subject to disciplinary penalties, including the possibility of failure in the course and/or dismissal from the University. Since such dishonesty harms the individual, all students, and the integrity of the University, policies on academic dishonesty will be strictly enforced. For further information please visit the Student Judicial Services Web site:
http://deanofstudents.utexas.edu/sjs