RMI 3750
Fall 2012
RMI 3750 – Fall 2012
Risk Modeling: Probability Theory and Simulation Analysis in Risk Management
Georgia State University
Professor: Florin Bidian
Class Hours & Location: MW 1:30pm-2:45pm, ADHOLD 331
Office Hours: M 3:00-4:30 and by appointment
Department of Risk Management & Insurance
Office: RCB 1124
Tel: 404-413-7484
Fax: 404-413-7499
E-mail: [email protected]
I.
Prerequisites: Math 1113 (Recommended), CSP 1, 6 and 7.
II. Course Description
This course introduces students to the principles of probability theory and risk simulation
analysis. Specific topics covered include probability theory; descriptive statistics and graphical
representations of data; probability distribution functions including binomial, Poisson, Normal
and other functions; sampling distributions and the Central Limit Theorem; estimation and
goodness-of-fit tests; and static and dynamic Monte Carlo simulation models. Spreadsheet
simulation exercises are used extensively to illustrate the concepts. The applications are drawn
from a variety of areas where risk analysis has become important including finance, insurance,
corporate risk management and personal financial planning.
III. Specific Course Objectives
At the conclusion of this course the student will be able to demonstrate he/she can:
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Summarize data by calculating population summary statistics and through graphical
representations
Calculate probabilities using basic counting rules and Venn Diagrams
Calculate conditional probabilities
Use Bayes Theorem to update conditional probabilities
Calculate probability distribution functions, cumulative distribution functions and
summary statistics for a variety of discrete random variables including binomial,
Geometric, Hypergeomentric, Poisson etc.
Calculate probability distribution functions, cumulative distribution functions and
summary statistics for a variety of continuous random variables including Uniform,
Normal, Lognormal, Gamma, and (generalized) Pareto.
Utilize the Central Limit Theorem to demonstrate the principles of risk management
through diversification
Program a Monte Carlo simulation model to analyze various risk exposures
Develop strategies that will effectively manage or mitigate a risk exposure
IV. Textbook and Other Requirements
 (HS) Hasset, Matthew J. and Donald G. Stewart, Probability for Risk Management
(Winsted, CT: Actex Publishers) 2006.
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You will need access to a computer since Microsoft Excel will be used extensively
throughout the course. Students can use the public computer labs to complete
these assignments.
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You must also have access to the Internet and an e-mail account so you can download
data and Adobe PDF documents that will be made available on uLearn. Please
check your GSU e-mail account and uLearn at least twice a week.
RMI 3750
V.
Fall 2012
Determination of Course Grades
Your course grade will be determined by reviewing your performance in the following areas:
homeworks and quizzes (30%), 2 midterms (20% each), and a final comprehensive exam
(30%). In some of the assignments you will be asked to complete a take-home project in Excel.
You may work with your choice of fellow students to complete homework. Grades will be
converted to letter grade using the following scale:
Letter
Grade
A
AB+
B
B-
Range
93-100
90-93
87-90
83-87
80-83
Letter
Grade
C+
C
CD
F
Range
77-80
73-77
70-73
60-70
0-60
VI. Additional Useful Information
Withdrawing from the Course
The last date to withdraw from this class without automatically receiving a grade of WF is
October 9, 2012. Prior to that date, assignment of a W or WF will be determined by the
grades the student achieved on all homework prior to the date of his or her withdrawal,
regardless of exam scores.
Attendance Policy
It is the student’s responsibility to attend class. Failure to attend class may mean you will
miss an unannounced quiz and will likely make completing the take-home projects difficult.
In addition, excessive absences will affect your ability to perform well on the exams.
Make-up Examinations
Exams will only be given at the time for which they are scheduled. I will offer individual
students the opportunity to reschedule an exam only when approval has been granted
before the scheduled exam. Failure to abide by this rule can result in the student receiving a
score of zero for the missed exam.
Academic Honesty Policy
The University’s policy on academic honesty is the guideline for this course.
consequences of violating the academic honesty policy are serious and severe.
The
The attached course outline provides a general plan for the course; deviations may be
necessary.
RMI 3750
Fall 2012
RMI 3750 Fall 2007 Topics by Week
Week
8/208/22
Topic
Course Introduction
Probability
Assigned
Reading
HS-1, 2
More Probability including Conditional Probabilities, Bayes
Theorem, Independence
HS-3
LABOR DAY – NO CLASS on Monday
Discrete Random Variables, Summarizing Data, Mean,
Variance, Graphical Representations
HS-4
9/10-9/12
Common Discrete Random Variables
HS-5
9/17-9/19
Using Discrete Random Variables
HS 6
9/24-9/26
Using Discrete Random Variables (Cont’d)
Supplements
10/110/3
Introduction to Simulation
Midterm 1 (Wednesday)
Supplements
10/810/10
Simulation (Cont’d)
Continuous Random Variables
HS 7
10/1510/17
Common Continuous Random Variables
HS 8
10/2210/24
Applications of Continuous Random Variables, Central Limit
Theorem
HS 9
10/2910/31
Distribution Fitting - Extreme Value Distributions
Supplements
11/511/7
Simulation analysis: Applications
Midterm 2 (Wednesday)
Supplements
11/1211/14
Simulation analysis: Applications
Supplements
11/1911/21
THANKSGIVING BREAK – NO CLASSES
Supplements
11/2611/28
Simulation analysis: Applications
Supplements
12/312/5
Review for the Final Exam
Final Exam @ 1:30 PM
8/27-8/29
9/39/5