Beskjeder
Hi,
The final presentation is uploaded. The red square in top right corner indicates what is included in the curriculum for the exam. Compared with the partial presentations there are two changes:
1. Chain Ladder has got a red square.
2. The Compound Poisson with the uncertainty regarding the intensity has a red square removed as we skipped it on the lecture.
We see on Monday to go through the exam from 2023!
On Nov 11 and 12 we are going to finish exercises regarding life insurance and do exercises regarding the option pricing. We should also have time to look at the assignment.
On November 18 and 19 we will look at the exam from the last year and if time allows we will have a Q&A session
On Monday we will have the lecture regarding the option pricing, whereas on Tuesday we will do exercises connected to the life insurance which we were supposed to do this week.
Unfortunately I need to cancel todays exercises
On Tuesday we are going to:
1. Calculate yearly premium and mathematical reserve for pure endowment, term insurance and endowment
2. Do exercises 3.17-3.22
I kindly remind that we will have only lectures on October 14th and 15th.
We are going to look at the 5th set of exercises with a special focus on chain ladder. Exercises are not from the book. Look also at an excel sheet with chain ladder
The assignment is available below and in canvas. The submission must be sent via canvas until October 24th 2:30pm. You need to get at least 40% to pass it. Note that you have only one attempt (though you can submit new versions before the deadline).
We are going to look at exercises from the fourth jupyter notebook:
possibly: 3.4, 3.5,
surely, 3.6, 3.7, 3.8, 3.9, 3.10, 3.11, 3.12, 3.13, 3.14,
We are going to continue exercises regarding the estimation from chapter 7 (7.9-7.13) + Bootstrap
Moreover we will prove the tower property of conditional expectation: if X,Y -indepdendent and f:R^2 -> R is a function then E[f(X,Y)|Y]= E[f(X,y)]|_{y=Y}.
If we have time, we will start the exercises regarding the Non-life insurance and compound Poisson (3.4, 3.5, 3.6 etc.)
From Chapter 2:
Ex. 2.19, 2.20, 2.21, 2.22, 2.23, 2.25, 2.26, 2.27, 2.28, 2.29, 2.30, 2.34, 2.35
From Chapter 7:
7.8, 7.9, 7.10, 7.11, 7.12, 7.13 + an exercise about bootstrap and estimation for lognormal distribution.
This is a kind reminder that we will have a lecture both on Monday sept 8th and Tuesday sept 9th. See you soon
The faculty confirm the date for the mandatory assignment (October 24th)
From Tuesday onward Sept 3rd we will also have a different lecture room (Auditorium 4 VB). That means that the lecture on Monday is still in the room 1119 Abels hus.
Prove formula for mean and standard deviation for MC estimator of mean
Prove formulas for CDF, expectation and variance of lognormal distribution
Example 2.2.3 from the book
Ex.2.1.2.2, 2.4, 2.5, 2.6, 2.9, 2.10, 2.12, 2.18 (not sure)
1. Right click on the link and choose "save as" or similar, depending on the browser
2. Either use the cloud version of Jupyter Notebook (https://jupyterhub.uio.no/ this didnt work today :( )
or
install Anaconda, install in it an R-environment and run it in Jupyter Notebook from Anaconda and open the file. I can show how to do it in case you have some problems. See you on Monday!
Linda (lindabergheim@hotmail.com) has been so kind to agree to be your student representative for this course. In case you have some comments or questions and do not want to ask me directly, please, take contact with her :)