Last Name:
First Name:
University ID:
ACTSC 431 or ACTSC 831:
ACTSC 431/831, Spring 2016
Midterm Exam 1, May 30, 2016
Time: 10:00 am - 11:20 am
Instructions:
Problem 5 is only for ACTSC 831 students.
Table of Common Distributions for ACTSC 431/831
1. Discrete Distributions
(a) Poisson with parameter > 0: A random variable X is said to have a Poisson distribution denoted by X P () if X has the foll
ACTSC 431 - Loss Models 1
Exercise 2
1. Suppose that the ground-up loss r.v. X has a mixture of two Pareto distributions:
FX (x) = 1 a
1
1 + x
(1 a)
2
2 + x
+2
for x 0.
,
Determine the mean and the s
Answers to Assignment 3 - ACTSC 431/831
1. Let X have the P areto(3, 50) distribution, p1 = Prcfw_5 < X < 10 = 0.172611 and
p2 = Prcfw_X > E (X ) = 0.296296.
(a)
i. We have E (N1 ) = E (E (N1 |N ) = 1
LOSS MODEL 1ACTSC 431/831, Spring 2014
Instructor:
Lectures:
Tutorials:
Oce hours:
Dr. Chengguo Weng, M3 3136, ext.31132, [email protected]
1:00-02:20pm Wednesday and Friday, EV3 1408.
Scheduled eve
Last Name:
First Name:
University ID:
ACTSC 431 or ACTSC 831:
ACTSC 431/831, Spring 2016
Midterm Exam 2, July 6, 2016
Time: 10:00 am - 11:20 am
Instructions:
Problem 6 is only for ACTSC 831 students.
ACTSC431/831
Spring 2014
Homework Set II (Due June 2, 2014)
1. 75% of claims have a normal distribution with a mean of 3,000 and a variance of 1,000,000. The
remaining 25% have a normal distribution w
ACTSC431/831
Spring 2014
Homework Set I (Due May 21, 2014)
1. For two random variables X and Y , eY (30) = ex (30) + 4. Let X have a uniform distribution
on the interval from 0 to 100 and let Y have a
ACTSC431/831
Spring 2014
Homework Set III (Due June 16, 2014)
1. For i = 1, . . . , n let Si have independent compound Poisson frequency distributions with
Poisson parameter i and a secondary distribu
ACTSC431/831
Spring 2014
Homework Set IV (Due July 2, 2014)
1. Losses have a Pareto distribution with = 2 and = k. there is an ordinary deductible of
2k. Determine the loss elimination ratio before an
ACTSC 431/831 - Loss Models I
Lecture 1
May 5, 2014
Lecture 1,
ACTSC 431/831 - Loss Models I
1/20
Course Information
Instructor: Dr. Xiaoying Han
Oce: 4101 M3
E-mail: [email protected]
Course Web: U
ACTSC 431/831 - Loss Models I
Lecture 2
May 7, 2014
Lecture 2,
ACTSC 431/831 - Loss Models I
1/10
Examples
Ex2.1 X4 - the total dollars in medical malpractice claims paid in
one year owing to events a
ACTSC 431/831 - Loss Models I
Lecture 5
May 21, 2014
Lecture 5,
ACTSC 431/831 - Loss Models I
1/7
Creating New Distributions
Given distributions of a continuous random variable X, seek
distributions o
Chapter 1. Introduction and Overview
Course objective: As the name of the course suggests, it is to introduce various mathematical
models which can be used by insurers to forecast and predict future i
Actsc 431: Term Test 1 (Version 1) - Spring 2013
Department of Statistics and Actuarial Science, University of Waterloo
June 3, 2013
Last name:
First name:
I.D.#:
Notes:
Show all work.
Aid: Calculat
Actsc 431 Notes
1
Introduction
In insurance loss modelling, two popular models in the literature include the individual risk
model and the collective risk model.
Individual risk model: Here, we consi
ASSIGNMENT 4 ACTSC 431/831, FALL 2012
Due at the beginning of the class on Friday, November 9
1. Let N L be the number of losses. The size of the j th loss is Xj . Assume that N L , X1 , X2 , . are
in
Practice Questions - Set 3 Solution
1. This years ground-up loss r.v. X has a distribution given by an equal mixture of two exponential
distributions, one with a mean of 250 and the other with a mean
Actsc 431 - Term Test 1 Info
Your rst term test will be held on Monday October 7 from 3:30pm to 4:20pm (50 minutes
long).
It will cover the material up to and including page 23 of the online notes (
Actsc 431: Term Test 1 - Fall 2013
Department of Statistics and Actuarial Science, University of Waterloo
October 7, 2013
Last name:
First name:
I.D.#:
Notes:
Show all work.
Aid: Calculator (Financi
Actsc 431: Term Test 2 (Version 1) - Spring 2013
Department of Statistics and Actuarial Science, University of Waterloo
June 25, 2013
Last name:
First name:
I.D.#:
Notes:
Show all work.
Aid: Calcula
Actsc 431: Term Test 2 - Fall 2013
Department of Statistics and Actuarial Science, University of Waterloo
October 28, 2013
Last name:
First name:
I.D.#:
Notes:
Show all work.
Aid: Calculator (Financ
Actsc 431: Term Test 1 (Version 1) - Spring 2013
Department of Statistics and Actuarial Science, University of Waterloo
June 3, 2013
Last name:
First name:
I.D.#:
Notes:
Show all work.
Aid: Calculat
Example 13: Suppose Y | = EXP
distribution of Y .
1
and let GAM (, ). Find the unconditional
Given the conditional distribution of Y given = , we have
SY | (y |) = P (Y > y | = ) = ey
Now, the uncondi
ACTSC 431/831 - Convolution Method
1. Suppose N BIN (3, 0.6), and M is such that P (M = 0) = 0.2 and P (M = 4) = 0.8. Let
S = M1 + M2 + + MN and fk n = P (S = k |N = n). Then
fk n
k=0
k=4
k=8
k = 12
n
Question of the Day - June 18
Due on June 19, 2013 by 4:00pm - Submit to Dropbox on Learn
Assume
S1 has a compound Poisson distribution with parameter 4 and a BIN (1, p) secondary
distribution, and
Actsc 431 Notes
1
Introduction
In insurance loss modelling, two popular models in the literature include the individual risk
model and the collective risk model.
Individual risk model: Here, we consi
Practice Questions - Set 2
1. Suppose that X | = EXP () and has p.d.f.
f () =
p1
, 0 < < , v > 0, 0 < p < 1.
(p)(1 p)( )p
(a) Show that X GAM (p, ).
(b) We have seen that the gamma distribution is a s
ACTSC 431/831 - Loss Models I
Lecture 4
May 14, 2014
Lecture 4,
ACTSC 431/831 - Loss Models I
1/10
Measures of Risk
description of risk exposure
the degree to which the company is subject to particu