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CFRM 546 A: Financial Risk Management II

Meeting Time: 
TTh 10:00am - 11:50am
LOW 216
Joint Sections: 
CFRM 546 B, CFRM 546 C

Syllabus Description:

The exam will be held on Monday, 5th of  June. 

Usual Class Room.  (LOW-216)

10:30-12:20 p.m



Dear All;

There was a typo in HW 4. 

Q1) It should be  Uniform distribution on (0,2). I have corrected the typo. It is under Files/Homework


Dear All;


For those of you, who need proctor registartion for the upcoming midterm exam can find the information and proctor registration section here



Dear All;


There was a typo in the last question of the homework. The index should go backward.

 I have corrected 5b) in HW 2.




Dear all;

A good reference to get more details about the lecture notes in Time Series is 

[1] Introduction to Time Series and Forecasting by P.J. Brockwell and R.A. Davis.

and to work on more financial applications is 

[3] An Introduction to Analysis of Financial Data with R by Ruey Tsay.




Homework 2 is POSTED

under Files/Homeworks.

The data set to be worked on is SouthernHemisphere.txt. 

It is in the folder R files/datasets. 


Due date is next next Sunday, midnight.

IN Q3 of HW1, probability of each omega_i equals  1/4. Namely, P(w_i) = 1/4 for each i=1,...,4.

I have fixed this typo and updated the homework. 


Midterm Date : 18th of May, Thursday Usual Class Time 10:00AM-11:50AM


Link To MediaStreaming


Here is the link to the Mediasite Catalog for the class.




Syllabus For CFRM 546


Kerem Ugurlu

Teaching Assistant:

Ibrahim Ozdemir


Class Room/Schedule

LOW 216/ Tuesday -Thursday 10:00-11:50 AM


Office Hours

Kerem Ugurlu: Thursday 13:00-14:30 Lewis Hall Office 304


Kerem Ugurlu skypename: kerem.ugurlu1

Ibrahim Ozdemir: Art Building Office 343

email :

Required Software •

R Language for Statistical Computing and Graphics


Recommended  Software •

RStudio integrated development environment for R

Recommended  Textbooks & Slides

Slides for the upcoming week are uploaded on canvas every sunday.

The recommended textbooks for the class are as follows:


[1] Introduction to Time Series and Forecasting by P.J. Brockwell and R.A. Davis.

[2] Quantitative Risk Management: Concepts, Techniques and Tools by Alexander J. McNeil, P. Embrechts, and Rüdiger Frey

[3] An Introduction to Analysis of Financial Data with R by Ruey Tsay.

[4] Mathematical Finance: Theory, Review and Exercises by Emanuela Gianin, and Carlo Sgarra

Weekly Tentative Syllabus


Week 1: [MRE, Chapter 1]

Introducing the Concept of Risk

Risk in Perspective


Week 2: [Gianin, Chapter 12; MRE, Chapter 2]

Risk Measures and Basic Concepts in Risk Management


Week 3:  [Gianin, Chapter 12; MRE, Chapter 2]

Risk Measures and Basic Concepts in Risk Management

Week 4: [Tsay, Chapter 2]

Elimination of Trend and Seasonal Components

Stationary Models, Autocovariance and Autocorrelation

Sample Autocovariance and Autocorrelation


Week5: [Tsay, Chapter 2]

Time Series Analysis (2)

Linear Processes and ARMA models


Week6: [Brockwell, Chapter 5]

Forecasting (prediction) of stationary time series

Week7: [Tsay, Chapter4]

Estimation of time series

ARCH models


Week 8:

Nonlinear time series [Tsay, Chapter4]

GARCH models

Week 9: [MRE, Chapter 7]

Extreme Value Theory


Week 10:

Introduction to Credit Risk [MRE, Chapter 8]


Online assignment submission

R programming assignments will be submitted online to an automated execution and grading system.



There will be 5 assignments.

The assignments contain theory and programming sections.

Each assignment counts towards 10% of your grade.

There will be 1 midterm counting towards 20%.

The final exam will be cumulative and count towards 30% of your final grade.

Academic integrity

Academic integrity is vitally important in the Computational Finance & Risk Management Program; hence our CF&RM Honor Code:

“Cheating, attempted cheating, plagiarism, lying, and stealing in relation to academic work is prohibited”

Specifically, there is a zero-tolerance policy for academic misconduct in the class.

Graduate students at the University of Washington are expected to practice high standards of professional honesty and integrity as described in the Student Academic Responsibility statement:


In regards to software development, the UW CSE Academic Misconduct Policy will also be applied:


This policy states 5 specific rules with the following 2 being critically important:

You must not share actual program code with other students. In particular, you should not ask anyone to give you a copy of their code or, conversely, give your code to another student who asks you for it; nor should you post your solutions on the web, in public repositories, or any other publicly accessible place. Similarly, you should not discuss your algorithmic strategies to such an extent that you and your collaborators end up turning in exactly the same code. Discuss ideas together, but do the coding on your own. You must not look at solution sets or program code from other years, nor should you make your own solutions publicly available even after the due date. Beyond being a clear violation of academic integrity, making use of old solution sets is a dangerous practice. Most assignments change in a variety of ways from year to year as we seek to make them better. Each year, however, some student turns in a solution to an assignment from some prior year, even though that assignment has since changed so that the old solution no longer makes sense. Submitting something that solves a previous year’s assignment perfectly while failing to solve the current one is particularly damaging evidence of Academic Misconduct. Students violating this policy will receive a failing grade for the course and be referred to the Dean of the College of Arts and Sciences per the college’s disciplinary review process:


Students should take the time to review each of the above policies and be conscientious to follow them throughout the course.

Disability accommodations

Students requiring academic accommodations due to a physical, psychological, or sensory disability should request services through Disability Resources for Students:

If you are approved for an academic accommodation, please advise the instructor during the first week of the class.

Changes to the course

This syllabus is the working plan as the course begins. However, the instructor reserves the right to adjust the course schedule, content, assignments, and grading policy as the course proceeds. Each course offering is unique and new materials, technology resources, the availability of guest lecturers, and even the weather can and do affect the course as it progresses. Students should expect minor changes and be flexible and adaptable when changes need to be made.


EDGE team’s troubleshooting information


Please check our guidelines for Using Mediasite. We also recommend that you test your device.

Links to each lecture will appear in the catalog two hours before the live broadcast begins.


Most of our Mediasite recordings are available to download shortly after the live stream has ended. Check out our advice on Downloading Content for more details.


If you need help accessing course recordings, please complete the form at this link; Choose “Mediasite / MediaAMP video”, from the drop-down list for, “What do you need help with?”.


Last updated: 
January 10, 2018 - 9:01pm