BE356-7-SP-CO:
Financial Modelling

The details
2023/24
Essex Business School
Colchester Campus
Spring
Postgraduate: Level 7
Current
Monday 15 January 2024
Friday 22 March 2024
20
09 January 2024

 

Requisites for this module
(none)
(none)
(none)
(none)

 

(none)

Key module for

MRESN30012 Finance,
MSC L11412 Financial Econometrics,
MSC N3G312 Finance and Data Analytics

Module description

<p>This module provides an introduction to some core topics in financial econometrics that are useful in financial research.


It is a technical course that will only suit students with a good background in econometrics who are comfortable with technical material including some matrix algebra. If you do not have this background you will struggle with the assessment. While practically oriented, it does involve some theoretical econometrics.</p>

Module aims

The aims of this module are:



  • To enable students to acquire the skills and techniques necessary to understand and critically evaluate the research areas covered.

  • To enable students to develop and apply a subset of those skills and techniques in coursework.

Module learning outcomes

No information available.

Module information

By the end of this module, students will be expected to be able to:



  1. Understand and apply the following methods: OLS, hypothesis testing techniques, VARs, SUR, ARCH, GARCH and HAR, non-stationarity and cointegration, tests of the EMH, predictability of asset returns, long-horizon regressions, time variation in returns, point and density forecasting and forecast evaluation.

  2. Be familiar with econometric software (primarily EViews) and be able to implement financial applications. 


Skills for Your Professional Life (Transferable Skills)


This module will deliver skills that will be useful in your future professional life including:



  1. Written Communication (through coursework).

  2. Research Skills (a key objective in this module).

  3. Critical Thinking.

  4. Digital and Technical Fluency (using econometric software).

  5. Data and Analytics.

Learning and teaching methods

The main learning and teaching methods are the lectures and classes. There are additional contact hours with lecturers outside the classroom available to students.

Bibliography

This module does not appear to have a published bibliography for this year.

Assessment items, weightings and deadlines

Coursework / exam Description Deadline Coursework weighting
Coursework   Take home assignment  22/03/2024  50% 
Coursework   Take home assignment - 2   07/05/2024  50% 

Exam format definitions

  • Remote, open book: Your exam will take place remotely via an online learning platform. You may refer to any physical or electronic materials during the exam.
  • In-person, open book: Your exam will take place on campus under invigilation. You may refer to any physical materials such as paper study notes or a textbook during the exam. Electronic devices may not be used in the exam.
  • In-person, open book (restricted): The exam will take place on campus under invigilation. You may refer only to specific physical materials such as a named textbook during the exam. Permitted materials will be specified by your department. Electronic devices may not be used in the exam.
  • In-person, closed book: The exam will take place on campus under invigilation. You may not refer to any physical materials or electronic devices during the exam. There may be times when a paper dictionary, for example, may be permitted in an otherwise closed book exam. Any exceptions will be specified by your department.

Your department will provide further guidance before your exams.

Overall assessment

Coursework Exam
100% 0%

Reassessment

Coursework Exam
100% 0%
Module supervisor and teaching staff
Dr Lazaros Symeonidis, email: l.symeonidis@essex.ac.uk.
Dr Lazaros Symeonidis and Dr Eirini Bersimi
ebspgtad@essex.ac.uk

 

Availability
No
No
Yes

External examiner

Dr Aris Kartsaklas
Brunel University London
Senior Lecturer
Resources
Available via Moodle
Of 17 hours, 17 (100%) hours available to students:
0 hours not recorded due to service coverage or fault;
0 hours not recorded due to opt-out by lecturer(s), module, or event type.

 

Further information
Essex Business School

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