ECOM073 - Topics in Financial Econometrics - 2023/24
Topic outline
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Welcome to ECOM073
The module will reaffirm the student's understanding of the classical techniques of regression analysis, which will be extended to encompass financial data modelling. The module will also cover the techniques of time series modelling. It will begin by analysing classical linear stochastic models that are formulated in discrete time. It will proceed to analyse models in continuous time that are a feature of modern financial analysis.
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Forum Description: This is your general discussion forum for the module. This forum is available for everyone to post messages to. Students can raise questions or discuss issues related to the module. Students are encouraged to post to this forum and it will be checked regularly by the module organiser. Students should feel free to reply to other students if they are able to.
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Weight in final mark: 80%.
Further details will be provided closer to the time of the final exam.
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Welcome to Week 1!
This week we would like you to complete:
- Attend the live lecture (overview of the course)
- 9am-- Wednesday, Jan 24, Place: Bancroft: 3.26
- Read attached Introductory Lecture material on this module
- Content topics for this week include: general introduction to the course , weekly work, books, teaching material, examples and why Financial Time Series are so interesting and useful for your further work, e.g. writing your MSc dissertations. This will help you selecting your optional Semester B modules
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This week we would like you to complete:
- Attend the live Lecture 1, January 31, 9am--11 am Wednesday, Place: Bancroft: 3.26
- Study the Lecture 1 material and handout
- Attempt the mini problems of the Quiz 1
- Content topics for this week Lecture 1 include: Graphical analysis, plots, impulse response function
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Opened: Wednesday, 17 January 2024, 9:00 AMClosed: Wednesday, 7 February 2024, 9:00 AM
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This week we would like you to complete:
- Attend the live Lecture 3, 9am-- Wednesday, 7 Febr, Place: Bancroft: 3.26
- Attend Class/Tutorial 11:00-12:00 Thursday, 8 Febr, Place: QB 212 PC lab
- Study the Lecture 2 material and handout
- Attempt the mini problems of the Quiz 2
- Attempt the problem set 1 of Tutorial 1 (results released next week)
- Content topics for this week Lecture 2 include: Introductory concepts. Stylized facts of financial data. Summary statistics. Testing for symmetry and heavy tails. Stationarity, autocorrelation function, white noise sequence
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Opened: Wednesday, 17 January 2024, 9:00 AMClosed: Wednesday, 14 February 2024, 9:00 AM
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This week we would like you to complete:
- Attend the live Lecture 3
- Study the Lecture 3 material and handout
- Attempt the mini problems of the Quiz 3
- Attempt the Problem Set 2 of Tutorial 2 (results released next week)
- Content topics for this week Lecture 3: Testing for correlation. AR, MA and ARMA models.
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Opened: Wednesday, 14 February 2024, 9:00 AMClosed: Wednesday, 21 February 2024, 9:00 AM
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Change of Lecture room:
Lecture will take place in PL-301 (Peter Landin teaching rooms)
It’s number 10 on the map link here:
https://www.qmul.ac.uk/media/qmul/docs/about/Mile-End-campus-map-February-2024.pdf
Wednesday 9:00-11:00amThis week we would like you to complete:
- Attend the live Lecture 4
- Study the Lecture 4 material and handout
- Attempt the mini problems of the Quiz 4
- Attempt the Problem Set 3 of Tutorial 3 (results released next week)
- Content topics for this week include: order selection for AR(p), MA(q), ARMA(p,q) model. Finding the best fitting model. Model selection criteria. Properties of AR(1) model
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Opened: Wednesday, 21 February 2024, 9:00 AMClosed: Wednesday, 28 February 2024, 9:00 AM
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Lecture will take place in PL-301 (Peter Landin teaching rooms)
This week we would like you to complete:
- Attend the live Lecture 5
- Study the Lecture 5 material and handout
- Attempt the mini problems of the Quiz 5
- Attempt the Problem Set 4 of Tutorial 4 (results released next week)
- Content topics for this week include: Model selection and forecasting
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Opened: Wednesday, 28 February 2024, 9:00 AMClosed: Wednesday, 13 March 2024, 9:00 AM
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ECOM073 Midterm test
Wednesday, 27 March, 9:00am-10:00am (60 minutes)
Place: PL-301 (Peter Landin teaching rooms)
Preparation: read the Info on Midterm, see attached solutions of quizzes 2-4
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This week we would like you to complete:
- Attend the live Lecture 6
- Study the Lecture 6 material and handout
- Attempt the mini problems of the Quiz 6
- Attempt the Problem Set 5 of Tutorial 5 (results released next week)
- Content topics for this week include: Non-stationary processes, unit root models, testing for unit root.
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Opened: Wednesday, 13 March 2024, 9:00 AMClosed: Wednesday, 27 March 2024, 9:00 AM
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This week we would like you to complete:
- Attend the live Lecture 7
- We will cover Unit root model (see Lecture 6)
- Prepare for the midterm test on March 27, see information Week 7 section
- Attempt the Problem Set 6 of Tutorial 6 (results released next week)
- Content topics for this week include: Unit root model.
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Midterm test: Wednesday, 9:00-10:00, March 27, 2023 (in person)
Test will take place in PL-301 (Peter Landin teaching rooms)
Preparation for the Midterm test: see material in Week 7 on QMPLUS
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This week we would like you to complete:
- Attend the Lecture 9
- Study the Lecture 9 material and handout
- Content topics for this week include: Introduction to conditional heteroscedasticity: ARCH, GARCH models.
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This week we would like you to complete:
- Attend the Lecture.
- Study the Lecture 9, 8 material and handout
- Attempt the Tutorial 8
- Discuss preparation for the final exam
- Content topics for this week include: GARCH, Seasonal models, VAR models
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Preparation for the final Exam ECOM073
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SCHEDULE -
Lecture: Wednesday 9:00-11:00 am Bancroft: 3.26 (Liudas Giraitis)
Class-Tutorial: Thursday 11:00-12:00pm QB 212 PC lab (Claudio Vallar)Week 1, 24 January, Introduction to the courseWeek 2, 31 January, (lecture 1, no tutorial) )Week 3, 7 February, (lecture 2, Tutorial 1)Week 4, 14 February (lecture 3, Tutorial 2)Week 5, 21 February, (lecture 4, Tutorial 3)
Week 6, 28 February, (lecture 5, Tutorial 4)Week 7, 6 March, Reading week [no teaching]Week 8, 13 March (lecture 6, Tutorial 5)Week 9, 20 March (lecture 7, Tutorial 6)Week 10, 27 March Midterm test [9:00-10:00] (+ Lecture 8, 45min]Week 11, 3 April (lecture 9, Tutorial 7)Week 12, 10 April (lecture 10, Tutorial general overview)The outline of the course
It is based on the following syllabus. Some of the topics will be carried over consecutive weeks:
1. Graphical analysis, plots, impulse response function
2. Introductory concepts. Stylized facts of financial data. Summary statistics. Testing for symmetry and heavy tails. Stationarity, autocorrelation function, white noise sequence
3. Testing for correlation. AR, MA and ARMA models.
4. Linear time series: a) Autoregressive process. AR(1) and AR(2) models: properties and prediction, business cycle. Order determination. Estimation of an AR(1) model. Forecasting.
5. Model selection and forecasting
6. Non-stationary processes, unit root models, testing for unit root.
7. Seasonal time series models
8 . Introduction to conditional heteroscedasticity: ARCH, GARCH models.
9 Regression models with times series errors. Co-integration. Multivariate time series models
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Basic readings:
Lecture Notes
R. S. Tsay. Analysis of Financial Time Series. 2nd edition, Wiley, 2005.
S. Bisgaard and M Kulahci. Time Series Analysis and forecasting by example. Wiley, 2011
Further readings:
Brockwell P. J. and R. A. Davis, Introduction to Time Series and Forecasting, Springer Texts in Statistics, 2002.
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Here is a list of common queries and who to contact:
Contact the PG administration team at pgsefsupport@qmul.ac.uk or in person at Graduate Centre 3.06 about:
- Class swap forms
- Issues with class allocations
- Timetable clashes
- Module registration
- Examination/assessment queries
- Attendance concerns
- Technical issues regarding submitting assignments
- Extenuating Circumstances
- Student support
- Social events and administrative support for student led activities
Contact the Module Organiser and Teaching Assistants (TAs) about:
- Academic content
- General assessment questions
- Office hours
- Feedback on work or assessments
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If you need to submit an Extenuating Circumstances form, please visit the QMUL Guidelines or contact the Student Support mailbox: pgsefsupport@qmul.ac.uk
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This link has information to help students to get the best out of QMPlus - with helpful guides and videos.