COURSE NUMBER: MBA240.11A

 

This course is cross-listed with the EWMBA Program.

 

IMPORTANT NOTES

1. This course has a take-home final exam on Sunday, April 13, 8:00 AM – 8:00 PM. Although you have a 12-hour period to finish the exam, it is designed to finish in 4-6 hours. You may work on the exam at home or on campus, and you may use any resource except another person. The exam is distributed and submitted electronically, so you can take the exam from anywhere in the world. Therefore, no exceptions are granted for taking the exam either earlier or later. Please plan accordingly.

 

2. This course requires use of a laptop during the 2 Sunday classes. Please plan accordingly.

 

COURSE TITLE: Risk Management via Optimization and Simulation

 

UNITS OF CREDIT: 1 Unit

 

INSTRUCTOR: Andy Shogan

 

E-MAIL ADDRESS: andy@haas.berkeley.edu

 

CLASS WEB-PAGE LOCATION: bSpace

 

MEETING DAY(S)/TIME: Sunday, February 23 & Sunday, March 16, 9:00 AM - 5:00 PM.

 

Please note the unorthodox nature of this course, which meets all day on two Sundays (2/23 & 3/16). To earn a passing grade, you must attend BOTH class sessions in their entirety.

 

PREREQUISITE(S): Fall Semester core courses (or consent of instructor)

 

CLASS FORMAT: This will be a lecture-based course.

 

REQUIRED READINGS: There is a textbook.

 

BASIS FOR FINAL GRADE: 2 Group Problem Sets (10%), 2 Group Assignments (40%), Take-home Final Exam on Sunday, 4/13 (50%). In prior offerings of this course, students have indicated that the workload was appropriate for a 1-unit course.

 

ABSTRACT OF COURSE'S CONTENT AND OBJECTIVES:

In many MBA programs (but not Haas), this course is part of the core curriculum and has the title of “Decision Models” or some variant thereof.  This course surveys how to formulate, solve, and interpret mathematical models – optimization and simulation   that assist a manager in his/her decision making.  The course covers decision models that are widely used in diverse businesses and industries, models with which all successful managers should be familiar. The course has two primary goals: make all students intelligent consumers of decision models developed by others, and motivate many students to be suppliers of decision models to their colleagues at work. Until recently, decision models were for experts only. However, given the past decade’s advances in computer hardware/software and in data collection/storage/retrieval, today's managers can quickly and inexpensively perform on their laptops what once required significant investments of time, space, and dollars. Therefore, an important aspect of this course is the use of Risk Solver Platform (http://www.solver.com/platform/risk-solver-platform.htm), integrated software that you own, learn, and apply during the course (and hopefully afterwards!).

 

Below is a summary of the course’s two major topics:

 

SESSION #1 (Sunday, February 23)

OPTIMIZATION USING RISK SOLVER PLATFORM.

 

Topics covered include:

 

· What is a Linear Program, and what is an Integer Linear Program?

 

· Applications of linear programming and integer linear programming to operations management and to financial management.

 

· How Risk Solver Platform, an add-in to Excel, can be used to solve a linear program or an integer linear program. (Although Excel was designed initially to answer the question "What if?", Risk Solver Platform enables Excel to answer the question "What's best?".)

 

SESSION #2 (Sunday, March 16)

SIMULATION & RISK MANAGEMENT USING RISK SOLVER PLATFORM.

Topics covered include:

 

· Why managers should confront uncertainties instead of ignoring them.

 

· How a manager can get into trouble by not understanding the Flaw of Averages. (That is, the mean of a function of random variables does not in general equal the function of the means of the random variables.)

 

· The world is not always Normal! (That is, in addition to the Normal Probability Distribution, there are other probability distributions with which a manager should be familiar.)

 

· What is simulation (sometimes referred to as Monte Carlo simulation)?

 

· How Risk Solver Platform, an add-in to Excel, can be used to conduct a simulation within a spreadsheet.

 

· What is risk, and how can it be measured and managed?

 

· The trade-off between return and risk. (For example, the best decision might not be the decision that maximizes expected profit but instead might be a decision that has a lower-than-maximum expected profit but a significantly lower downside risk.)

 

· Applications of simulation to operations management, developing a "business plan" for a new venture, obtaining portfolio insurance via a put option, adding "leverage" to a portfolio via a call option, yield management in the airline and hotel industries, and Value-at-Risk.

BIOGRAPHICAL SKETCH: ANDY SHOGAN joined the Haas School’s faculty in 1974 after receiving an A.B. in Mathematics from Princeton and a Ph.D. in Operations Research from Stanford. At the Haas School, Andy served several times as chair of the Operations & Information Technology Group, and, during the period 1991-2007, he served as the Haas School’s Associate Dean for Instruction.  In 2007, Andy was awarded the Chancellor’s Distinguished Service Award for his long-time service to both Haas and the University. For his teaching, Andy has twice received the Haas School’s Cheit Award for Teaching Excellence (once from the Full-Time MBA students and once from the EWMBA students), and he has received the campus-wide Distinguished Teaching Award from the University’s faculty. In addition to being a Haas faculty member, Andy is a Visiting Professor at Switzerland’s Lorange Institute of Business (formerly GSBA Zurich) and Denmark’s AVT Business School, where he regularly teaches operations management and spreadsheet modeling in the schools’ Executive MBA Programs, and where he has twice received awards for teaching excellence. Andy has taught a variety of executive education programs in the United States, China, Thailand, Taiwan, Jamaica, Mexico, and Switzerland. In 1988, his textbook Management Science was published by Prentice-Hall. Andy and his wife of 41 years are both natives of Pittsburgh, PA, now reside in Orinda, CA, and have 3 sons, 2 daughters-in-law, and 2 grandsons & 1 granddaughter.