COURSE UNIT TITLE

: LOSS MODELS

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
STA 5094 LOSS MODELS ELECTIVE 3 0 0 8

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR GÜÇKAN YAPAR

Offered to

Statistics (English)
STATISTICS (ENGLISH)
Statistics (English)

Course Objective

The objective of this course is to cover actuarial models of loss contingencies. We will cover statistical concepts of location and dispersion, inferences from insurance data.

Learning Outcomes of the Course Unit

1   Review the theory of probabilty.
2   Learn estimation theory
3   Learn properties of estimators
4   Generate interpolating and smoothing
5   Generate simulation

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Review of Probability
2 Review of Mathematical Statistics
3 Non-parametric Empirical Point Estimation
4 Kernel Smoothing Estimators
5 Emprical Estimation from Grouped Data
6 Estimation from Censored and Truncated Data
7 Properties of Survival Estimators
8 Moments
9 Percentile Matching
10 Discussion and problem solving
11 Maximum Likelihood Estimation
12 Interpolating and Smoothing
13 Simulation, homework
14 Review

Recomended or Required Reading

Textbook(s):
Stuart A. Klugman, Harry H. Panjer, Gordon E. Willmot, Loss Models: From Data to Decisions,2nd Edition, John Wiley and Sons Inc., 1999.

Planned Learning Activities and Teaching Methods

The course consists of lecture, class discussion and problem solving.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 ASG ASSIGNMENT
3 FIN FINAL EXAM
4 FCG FINAL COURSE GRADE MTE * 0.30 +ASG * 0.20 +FIN * 0.50
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 + ASG * 0.20 + RST * 0.50


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

Exams, homework.

Language of Instruction

English

Course Policies and Rules

Attendance to at least 70% for the lectures is an essential requirement of this course and is the responsibility of the student. It is necessary that attendance to the lecture and homework delivery must be on time. Any unethical behavior that occurs either in presentations or in exams will be dealt with as outlined in school policy. You can find the undergraduate policy at http://web.deu.edu.tr/fen.

Contact Details for the Lecturer(s)

DEU Faculty of Science, Department of Statistics
e-mail: guckan.yapar@deu.edu.tr
Tel: 0232 301 85 59

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 15 3 42
Preparations before/after weekly lectures 15 3 42
Preparation for final exam 1 32 32
Preparation for midterm exam 1 28 28
Preparing assignments 1 40 40
Final 1 2 2
Midterm 1 2 2
TOTAL WORKLOAD (hours) 188

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10
LO.1555
LO.2555
LO.3555
LO.4555
LO.5555

CONTACT INFORMATION
Dokuz Eylül Üniversitesi Cumhuriyet Bulvarı No: 144 35210 Alsancak / İZMİR
Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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