Ted Ralphs

Miscellaneous Handouts and Course Information

• Course Syllabus
• Course Calendar (Google)

Lecture Slides

• Preliminaries
• Lecture 1: Introduction
• Lecture 2: Course Overview
• Lecture 3: Introduction to AMPL
• Lecture 4: Linear Programming, Dedication, and Cash Flow Matching
• Lecture 5: Duality and Asset Pricing
• Lecture 6: Option Pricing and Arbitrage Detection
• Lecture 7: Introduction to Portfolio Optimization
• Lecture 8: Markowitz Portfolio Models
• Lecture 9: Efficient Portfolios and the Market Price of Risk
• Lecture 10: Nonlinear Programming, Optimality Conditions, and Duality
• Lecture 11: Interior Point Methods for Convex Quadratic Programs
• Lecture 12: Parameter Estimation in Portfolio Optimization
• Midterm Review Slides
• Lecture 13: Modeling with Integer Variables
• Lecture 14: Solution Methods for Integer Programs
• Lecture 15: Constructing an Index Fund
• Lecture 16: Dynamic Programming
• Lecture 17: Option Pricing Revisited
• Lecture 18: Structuring Collateralized Mortgage Obligations
• Lecture 19: Stochastic Optimization
• Lecture 20: Multi-stage Stochastic Programming with Recourse
• Lecture 21: More Stochastic Programming
• Lecture 22: The L-Shaped Method
• Lecture 23: Sample Average Approximation
• Lecture 24: Conditional Value at Risk

Models from Lecture

• Bond Selection
• Python
• bonds_simple_PuLP.py
• bonds_PuLP.py
• bonds_data.py
• bonds_data_extended.py
• AMPL
• simple.mod
• bonds_simple.mod
• bonds_simple.run
• bonds.mod
• bonds.dat
• bonds.run
• bonds_alt.dat
• bonds_extended.dat
• bonds_features.mod
• Short Term Financing
• Python
• short_term_financing_PuLP.py
• short_term_financing_data.py
• AMPL
• short_term_financing.mod
• short_term_financing.dat
• short_term_financing.run
• Dedication
• Python
• dedication_PuLP.py
• dedication_PyomoConcrete.py
• dedication_PyomoAbstract.py
• dedication-Pyomo.dat
• AMPL
• dedication.mod
• dedication.dat
• dedication.run
• dedication-AMPL.dat
• ZMPL
• dedication.zpl
• dedication2.zpl
• Arbitrage Detection
• Python
• arbitrage_typeA.py
• AMPL
• arbitrage_typeA.mod
• arbitrage_typeB.mod
• arbitrage.dat
• arbitrage2.dat
• Portfolio Optimization
• Python
• portfolio-KY-Pyomo.py
• portfolio-Markowitz-Pyomo.py
• DJIA.dat
• AMPL
• portfolio.mod
• portfolio2.mod
• portfolio.dat
• DJIA.dat
• CMOs.xls
• CMOSmall.xls
• DE.mod
• DE.dat
• randomLP.mod
• saa.run
• saa.mod

Scripts

• yahoo.py (a Python package for downloading quotes from Yahoo)
• returns.py (script for downloading returns data)

Software

• Get AMPL
• Get COIN
• Get Python

Reference Texts

• Course Text: Optimization Methods in Finance, by Cornuejols and Tutuncu, Cambridge University Press (2007).
• Optimization in Operations Research, R.L. Rardin, Prentice Hall (1997).
• Introduction to Mathematical Programming, W.L. Winston and M. Venkataramanan, Duxbury Press (2002).
• AMPL: A Modeling Language for Math Programming, R. Fourer, D. M. Gay, and B. W. Kernighan, Duxbury Press (1999).
• Operations Research Models and Methods, P. Jensen — a fantastic on-line introduction to OR including Excel add-ins.
• Model Building in Mathematical Programming, H.P. Williams, Wiley (1999).
• How to Model It: Problem Solving for the Computer Age, K.A. Smith and A.L. Bleloch (1984).

On-line References

• Collateralized Mortgage Obligations
• Wikipedia
• Freddie Mac Guide
• Portfolio Optimization
• Portfolio Optimization
• How Many Mutual Funds Routinely Route the Market?
• Risk Measures
• Shortfall as a Risk Measure
• VaR versus CVaR
• How do We Measure Risk”

AMPL Pointers

• AMPL Web site
• AMPL Book: Chapter 1
• A Modeling Language for Mathematical Programming
• Submitting AMPL models over the Web
• Examples using AMPL — includes the McDonald’s Diet Problem
• AMPL in Action (Case Studies using AMPL)
• New Features Page (useful reference)
• List of built-in suffixes
• AMPL/CPLEX Reference Guide

Tutorials and Guides

• What is Operations Research? — The Bureau of Labor Statistics’ over view of this career field
• INFORMS Web site — the professional society for Operations Research and Management Science (OR/MS)
• INFORMS News Room — lots of information about OR/MS
• The INFORMS OR/MS Resource Collection — an extensive collection of OR links
• INFORMS Student Union — INFORMS resources for students
• The World of Operations Reearch and Management Science
• Math World — an amazing on-line mathematics encyclopedia.
• The INFORMS OR/MS Resource Collection — an extensive collection of OR links
• NEOS Guide — a good overview of optimization
• e-Optimization.com
• Harvey Greenburg’s Courseware Page
• Harvey Greenburg’s Mathematical Programming Glossary
• Guide to Optimization Software
• IFORS tutORial Project
• The Traveling Salesman Problem — a page devoted to the world’s best-known optimization problem
• J.E. Beaseley’s OR Notes

Interactive Optimization

• NEOS Server — solve optimization problems over the Web
• NEOS Case Studies — includes an interactive version of the Diet Problem
• Tutorial on Spreadsheet Optimization
• The Remote Interactive Optimization Testbed (RIOT) Page
• NEOS Java Graphical LP Solver
• LP exlorer — 2 dimensional linear programs
• List of Java Applets at the INFORMS Resources site

Case Studies

• Math Programming in Action
• Cap Gemini Enrst and Young Case Studies Database
• LINDO Model Library
• Application Showcase at e-optimization.com
• Facility location case study
• NEOS Case Studies — includes an interactive version of the Diet Problem

List of Pointers to More Sites

• Introduction to Optimization course at MIT — lots of good pointers to sites about optimization.
• OR/MS pointers at OpsResearch.com
• Yahoo’s Operations Research page
• John Mitchell’s optimization pointers
• Kevin Wayne’s OR/CS links