Communication

All written communication for the course will take place through the Brightspace. Please remember to consult the course page regularly to keep up with any updates and course announcements.

Before emailing a question, please fully read this syllabus and explore the associated resources. The answers to many questions can be found in this document and students may be referred back to the syllabus if the answer is already available. Please allow at least two (2) business days for responses to inquiries before pursuing another route of communication.

Your feedback is very welcome! In addition, I encourage you to get in touch with me as early as possible if you have any concerns about the course.

Official Course Description

Introduction to econometric methods used to analyze financial data. Topics covered may include modelling of stock prices and asset returns, tests of market efficiency, modelling volatility, event study analysis, and analysis of high-frequency data.

Prerequisite: ECO 2151 (ECO3151) or MAT 3375.

Indigenous Affirmation

ANISHINÀBE

Ni manàdjiyànànig Màmìwininì Anishinàbeg, ogog kà nàgadawàbandadjig iyo akì eko weshkad. Ako nongom ega wìkàd kì mìgiwewàdj.

Ni manàdjiyànànig kakina Anishinàbeg ondaje kaye ogog kakina eniyagizidjig enigokamigàg Kanadàng eji ondàpinangig endàwàdjin Odàwàng.

Ninisidawinawànànig kenawendamòdjig kije kikenindamàwin; weshkinìgidjig kaye kejeyàdizidjig. Nigijeweninmànànig ogog kà nìgànì sòngideyedjig; weshkad, nongom; kaye àyànikàdj.

Listen to the audio file

ENGLISH

We pay respect to the Algonquin people, who are the traditional guardians of this land. We acknowledge their longstanding relationship with this territory, which remains unceded.

We pay respect to all Indigenous people in this region, from all nations across Canada, who call Ottawa home. We acknowledge the traditional knowledge keepers, both young and old.

And we honour their courageous leaders: past, present, and future.

Inclusion

The University of Ottawa aims to be an equitable and inclusive institution, actively participating in ensuring the wellbeing of students, personnel and faculty members. The University is committed to eliminating obstacles to student inclusion in accordance with theOntario Human Rights Code. The Code provides that every person has the right to equal treatment with respect to goods, services, facilities, housing, contracts and employment as well as  membership  in  trade  or  professional  associations  and  unions  without  discrimination  because  of  ‘’Race, Ancestry, Place of origin, Colour, Ethnic origin, Citizenship, Creed, Sex, Sexual orientation, Gender identity, Gender expression, Age, Record of offence (in employment only), Receipt of public assistance, Marital status, Family status, Disability’’ .

TheHuman Rights Office of the University of Ottawaadds ‘’although the Human Rights Code does not provide a definition of discrimination, the notion of discrimination covers unfair treatment on the basis of race, disability, sex, or any other personal characteristic. It can take many different forms, can target a single person or a group and can be part of a system.’’

If you have experienced discrimination or harassment, you can seek confidential assistance through the University Human Rights Office to discuss your situation and/orto file a formal complaint.

The following uOttawa Campus based services are available to you and your fellow students:

uOttawa Counselling Serviceincluding Individual Counselling provided by uOttawa Counsellor, Pierre Bercy who specializes in anti-black racism;

University of Ottawa Students’ Union (UOSU)Resources for/from the Black Community,Centre for Students with Disabilities,Racialized and Indigenous Students Experience Centre,Womxns Resource CentreanduOttawa Pride Center

Anti-racism student committee (Email:car.arc.uottawa@gmail.com)

Mashkawazìwogamig:Indigenous Resource Center

University of Ottawa’s Human Rights Officeincludingpolicies on accessibility.

Course Learning Outcomes

General Course Learning Outcomes

By the end of the course, students will be able to:

- apply statistical analysis and advanced econometric and mathematical techniques to examine a range of issues in financial economics and macroeconomics;

-  find,  interpret  and  understand  financial  and  macroeconomic  data  and  use  scientific  methods to  confront theoretical models with empirical evidence;

- appreciate the limits of the techniques under study in the course and understand how these limits might affect our analysis and interpretation of the results;

- formulate and conduct independent research studies, and communicate the methods and results of economic

analysis in written form.

In addition, the course aims to:

- promote students to work autonomously and to behave consistently with academic integrity;

- help students identify their professional and educational goals beyond the degree.

Specific Course Learning Outcomes

The objective of this course is to introduce students to the methods used for the analysis of time series and financial data. Students will first develop an understanding of univariate and multivariate time series models, their identification and estimation, and the techniques used for model evaluation. They will then learn how to apply time series models for forecasting purposes. Finally, students will become familiar with the methods used for modeling volatility and correlation in the data, and with their use in macroeconomics and financial economics.

By the end of the course, students will also be able to implement the concepts learned in class to address empirical questions using statistical software and real world data.

Teaching Methods

Classes will consist of lectures delivered in person. Some of the lectures will include tutorials and examples using statistical software or brief activities for the students to carry out on their own. The material covered in this course is fairly advanced, so I strongly encourage you to ask questions during the lectures or come to my office hours if there is anything that is unclear or that you would like to discuss further.

In addition, please be advised that learning how to use statistical software for the type of analysis studied during this course takes time and practice. I recommend that you start getting familiar with the software and data work as soon as possible, and I suggest that you talk to your classmates and help each other in developing the skills that you need for this part of the course.

This course offers the following experiential learning activities:

Collection and manipulation of real-world data.

Empirical analysis of past data and forecasting of future economic scenarios.

Practical use of statistical software.

Class recording policy

Classes  or  synchronous  online  sessions   may   be   recorded   if   required  to   meet   an  approved  academic accommodation plan for one or more students. Access to recordings for those students will only be available through Brightspace and will be removed after 150 days. Recordings are the intellectual property of the professor and are protected by copyright. Students authorized to receive recordings are not permitted to share or download them, and they will lose the right to their accommodation if they do.

Required Materials

The information presented during the lectures will be sufficient to complete the homework assignments and write the exams. I will also provide students with practice questions during the course, and I will not use exercises from any textbook.  However,  please  note that  most of the  lectures will follow the  material covered in “Financial Econometric Modeling” (Stan Hurn; Vance L. Martin; Jun Yu; Peter C.B. Phillips), so students may find it useful to read this textbook.

Technology and Statistical Software: This course requires a computer with a good internet connection and a smartphone/tablet or printer and scanner.

The assignments and final exam require the use of statistical software. You can choose one of the following: STATA, R, Matlab. I am most familiar with STATA and Matlab, so these are the platforms that I will use for the in- class examples and tutorials. Please also be aware that I might not always be able to help you if you encounter issues with R. Students can download STATA at the link provided in the Department of Economics webpage. R is available for free and can be downloaded from: https://www.r-project.org/. Matlab is available in the Vanier computer labs.

The computer labs in Vanier (VNR) are located in rooms 2008, 2015 and 2025 . You can access the labs online at

the following link:https://studentlabs.uottawa.ca/

Recommended Materials

Recommended textbook: Financial  Econometric  Modeling  by Stan Hurn; Vance  L. Martin; Jun Yu;  Peter C.B. Phillips. Oxford University Press, 2020.

ISBNs: MATT0Q4LCP, 9780190857066, 9780190857073, 9780190857127, 0190857072

I  might  recommend  additional  readings,  for  instance  research  papers  and  lecture  notes;  these  will  be communicated during the course and made available to students through the Brightspace.

Assessment Strategy

The  final  grades  for the  ECO4185  course  will  be  computed  based  on:  participation  (5%);  three  homework assignments (10% each), one midterm exam (25%), and the final exam (40%).

Participation: Participation points can be earned by completing short quizzes and/or other activities concerning the material covered in class. There are a total of 7 participation points but students only need to complete 5 of them to receive the full 5% participation mark. The points are to be completed through the Brightspace. The classes that include a participation point will be communicated in advance and I will leave about 10 minutes at the end of the lecture for you to complete the assigned quiz/activity.

Homework: Homework assignments will consist of problems and empirical questions. The empirical questions will require the use of statistical software.  The assignments are to be completed individually. There will be a total of 3 assignments for the course, each worth 10% of the overall mark (for a total of 30%).

Exams: The midterm exam will cover all material through the immediately preceding lecture, unless you are given different instructions. The final exam is cumulative. Exam questions will be drawn from the lectures, the practice material, and the  homework assignments.  In the final  exam, some of the  questions will  require the  use of statistical software.          The midterm exam will take place in person, in the same classroom where the lectures are held. The final exam is a take-home exam that will take place online. The exam will be made available to students on the Brightspace and

answers are to be submitted through the Brightspace by 5:00pm on April 17th. More detailed instructions and information about the format of the exams will be given during the course.

Bonus marks: The midterm and final exams will normally include one/two bonus questions, which give extra points if answered correctly. In addition, if you complete more than the 5 required participation points, I will count the extra ones as a bonus (1% each). Please note that no additional bonuses will be granted.

Policy on the EIN grade (incomplete):

In all economics courses, students who fail to complete work (either a single piece of work or a combination of work) worth a total of 25% or more of the final grade will receive a grade of EIN in the course. The EIN grade is equivalent   to   a   failure    mark    (F).   See    Regulation    10.6 (https://www.uottawa.ca/administration-and- governance/academic-regulation-10-grading-system) for details.

Please note that a denied request for a deferral may therefore lead to a failure mark.

Assessment Policies and Expectations

Attendance

To ensure they succeed in all courses of their program of study, students have the responsibility to participate in the various learning and assessment activities for each of their courses.

Class attendance is necessary to successfully complete this course. The material covered in the course is advanced and quite technical, so it is essential that students attend the lectures and keep up with the readings in order to avoid falling behind.

Time Commitment

In order to succeed in a 3-credit course, alongside the standard 3 hours of in-class instruction, students should expect to spend a minimum of 6 hours per week outside of the classroom engaged in activities related to the course, e.g. homework, reading, studying, etc., and should expect a minimum time commitment of 9 hours per week per course (on average).

Language Expectations

This course is delivered in English, and in-class interactions, including the online discussion boards, and feedback will also be managed in English. As part of your evaluation will be on your writing abilities, it is recommended to take the appropriate measures to avoid mistakes such as spelling, syntax, punctuation, inappropriate use of terms, etc. You may be penalized up to 15% for poorly written materials, to the professor’s discretion.

Late Assignments

All assignments are to be submitted by their due date and time.

Quizzes and other activities counting towards participation points must be completed by the due date and time, no  late  submissions  will  be  accepted.  Late  homework  assignments  will  receive  a  penalty  of  20%  for  each subsequent calendar day (including weekends) following the due date to a maximum of 3 days. After 3 days all outstanding assignments will be given a zero grade.

Exceptions are made only for illness or other serious situations deemed as such by the instructor. University regulations require all absences from exams and all late submissions due to illness to be supported by a medical certificate. Absence for any other serious reason must be justified in writing, to the professor, within five business days following the date of the exam or submission of an assignment.

The Faculty reserves the right to accept or refuse the reason; reasons such as travel, jobs, or any misreading of the examination timetable are not acceptable.

Missed exams and requests for deferral

An absence from an evaluation that is not excused will result in a mark of zero. According toAcademic Regulation I-9.5, students can request to be excused from only one evaluation per course. An absence will be excused only in the case of illness or other serious situations. The  Faculty reserves the right to accept or refuse the reason. Conflicts due to travel, jobs, or any misreading of the examination timetable are not acceptable reasons.

Students who wish to be excused for an absence must complete a deferral formand submit credible external documentation (e.g. medical certificate, police report, death certificate, etc.) within five working days of the evaluation. Students whose request is approved will be required to write a deferred evaluation, except where the professor offers a re-weighting scheme. (If available, such a scheme is described in this syllabus.) A deferred evaluation must be taken as soon as possible after the original date, but in any case no later than (6) months after

the end of the term (Academic Regulation I-9.5).

Students should reflect deeply before requesting a deferred evaluation, since they can only receive one deferral per course. Students who are struggling to keep up with their schedule may find it worthwhile to withdraw from the course and take it again at a later date. In Winter 2023, the deadline to withdraw from a course (without financial reimbursement) is March 31. For further information, consult the link:https://www.uottawa.ca/course-

enrolment/withdrawing-from-a-course

Course policy for the Midterm Exam: Students who  miss the  midterm exam for a valid  reason and  have an approved request for a deferred mark will write a makeup exam on Friday, February 17th, 2023.

The date of the deferred final exam is May 12th or 13th, 2023 (still to be determined).

Exam conflicts

Any conflict with a midterm exam schedule should be reported to the Professor at the beginning of the term.

This request is especially applicable to the type 3 conflict (two in-class exams back-to-back) for students with special learning needs.

Any conflict with a final exam schedule should be reported to the Faculty’s undergraduate office as soon as

the final examination schedule is released.

Course Calendar

The chapters refer to “Financial Econometric Modeling” (Stan Hurn; Vance L. Martin; Jun Yu; Peter C.B. Phillips). A more detailed list of readings for each class will be communicated through the Brightspace.