ACSC/STAT 4703 - Fall 2020


Actuarial Models II

This is the page where I post material related to the ACSC/STAT 4703 course I am teaching in FALL 2020.

 

  • Office hours: Monday 12:30-13:30,Tuesday 9:00-10:00,Thursday 11:30-12:30
  • Office: 102 Chase building
  • If you want to come to my office at a different time please email me:tkenney@mathstat.dal.ca
  • Midterm Exam: Friday 28th February, in class.
  • Here are some practice questions for the Midterm exam. Here are the model solutions.
  • Here is the formula sheet for the midterm exam.
  • Here is the midterm. Here are the model solutions.
  • Textbook: Loss Models: From Data to Decisions (Fourth Edition) by S. A. Klugman, H. J. Panjer and G. E. Wilmot, published by Wiley, 2012
  • Additional reading Society of Actuaries, SHORT-TERM ACTUARIAL MATHEMATICS STUDY NOTEs Available here, here, here, here, and here.
  • Additional reading Introduction to Ratemaking and Loss Reserving for Property and Casualty Insurance (Fourth Edition), 2015, by Brown and Lennox
  • Final Exam: TBA, during exam period 8-24 April.
  • Corona Virus

  • Classes to be moved online from 23rd March. Videos are available on Brightspace
  • Homework due dates moved back - see below.
  • Online open-book final exam will be held using Brightspace<\a>.
  • Handouts

    Course Handout

    Class Questions

    Answers to Class Questions

    (These are partly for my reference, so are not totally complete.)

    R code for some of the class questions

    A few useful R tips.

    Planned material

    Lecture time is limited, so I plan to use it explaining concepts and giving examples, rather than reading the textbook. Therefore, to get the most out of each lecture, you should read the relevant material before the lecture. Here is the list of what I expect to cover in each lecture. This is subject to change - make sure to check regularly for changes.

    Week beginning Monday Wednesday Friday
    6th January Introduction and Preliminaries
    SNOW DAY 9 Aggregate Loss Models:
  • 9.1 Introduction
  • 9.2 Model choices
  • 9.3 The compound model for aggregate claims
  • 13th January
  • 9.4 Analytic results
  • 9.5 Computing the aggregate claims distribution
  • 9.6 the recursive method
  • 9.6.1 Applications to compound frequency models
  • 9.6.2 Overflow/Underflow problems
  • 9.6.3 Numerical stability
  • 9.6.4 Continuous severity
  • 9.6.5 Constructing arithmetic distributions
  • 20th January
  • 9.6.5 Constructing arithmetic distributions (cont.)
  • 9.7 The impact of individual policy modifications on aggregate payments
  • 9.8 The individual risk model
  • 9.8 The individual risk model (cont.)
  • 27th January 16 Model selection
  • 16.3 Graphical comparison of density and distribution functions
  • 16.4 Hypothesis tests
  • 16.4 Hypothesis tests (cont.)
  • Score based approaches - AIC, BIC
  • 16.5 Model Selection
  • 3rd February IRLRPCI 2 Types of short-term insurance coverage IRLRPCI 2 Types of short-term insurance coverage (cont.) MUNROE DAY
    10th February IRLRPCI 4 Loss Reserving
  • 4.1 Introduction
  • 4.2 How outstanding claim payments arise
  • 4.3 Definition of terms
  • 4.4 Professional considerations
  • 4.5 Checking the data
  • 4.6 Loss reserving methods
  • 4.6 Loss reserving methods (cont.)
  • 4.7 Discounting loss reserves
  • 4.7 Discounting loss reserves (cont.)
  • Revision chapters 9, 16, IRLRCPI 2, 4
    17th February STUDY BREAK
    24th February Revision chapters 9, 16, IRLRCPI 2, 4 Revision chapters 9, 16, IRLRCPI 2, 4 Revision chapters 9, 16, IRLRCPI 2, 4
    2nd March

    MIDTERM

    EXAMINATION

    17 Introduction and limited fluctuation credibility
  • 17.2 Limited fluctuation credibility theory
  • 17.3 Full credibility
  • 17.4 Partial credibility
  • 17.5 Problems with this approach
  • 18 Greatest accuracy credibility
  • 18.2 Conditional distributions and expectation
  • 9th March
  • 18.3 Bayesian methodology
  • 18.4 The credibility premium
  • 18.5 The Buhlmann model
  • 18.6 The Buhlmann-Straub model
  • 18.6 The Buhlmann-Straub model (cont.)
  • 18.7 exact credibility
  • 19 Empirical Bayes parameter estimation
  • 19.2 Nonparametric estimation
  • 19.3 Semiparametric estimation
  • 16th March CLASSES SUSPENDED
    23rd March
  • 19.3 Semiparametric estimation
  • IRLRPCI 3 Ratemaking
  • 3.1 Introduction
  • 3.2 Objectives of ratemaking
  • 3.3 Frequency and severity
  • 3.4 Data for ratemaking
  • 3.5 Premium data
  • 3.6 The exposure unit
  • 3.7 The expected effective period
  • 3.8 Ingredients of ratemaking
  • 3.9 Rate changes
  • 30th March
  • 3.9 Rate changes (cont.)
  • IRLRPCI 5 Intermediate topics
  • 5.1 Individual risk rating plans
  • 5.2 Increased limits factors
  • 5.3 Reinsurance
  • 6th April Revision END OF LECTURES

    Homework

    Assignment 1 Due Friday 31st January. Model Solutions
    Assignment 2 Due Monday 10th February. Model Solutions
    Assignment 3 Due Friday 14th February. Model Solutions
    Assignment 4 Due Friday 13th March. Model Solutions
    Assignment 5 Due Friday 27th March.
    Assignment 6 Due Friday 3rd April.
    Assignment 7 Due Monday 6th April.