BE953-7-AU-CO:
Research Methods in Finance

The details
2023/24
Essex Business School
Colchester Campus
Autumn
Postgraduate: Level 7
Current
Thursday 05 October 2023
Friday 15 December 2023
20
28 July 2023

 

Requisites for this module
(none)
BE399
(none)
(none)

 

BE361, BE362

Key module for

MSC N42012 Accounting and Finance,
MSC N42024 Accounting and Finance,
MSC N31012 Banking and Finance,
MSC N31024 Banking and Finance,
MRESN30012 Finance,
MSC N30012 Finance,
MSC N30024 Finance,
MSC N39012 Investment and Wealth Management,
MSC N39024 Investment and Wealth Management,
MSC N30212 Finance and Management,
MSC N30224 Finance and Management,
MSC N34212 Financial Engineering and Risk Management,
MSC N34224 Financial Engineering and Risk Management,
MSC N3G312 Finance and Data Analytics,
MSC N35112 Finance and Global Trading,
MPHDN30048 Finance,
MPHDN30084 Finance,
PHD N30048 Finance,
PHD N30084 Finance,
MACCN440 Accounting and Finance,
MACCN441 Accounting and Finance (Including Placement Year),
MACCN442 Accounting and Finance (Including Year Abroad)

Module description

The primary purpose of this module is to provide the student with the basic econometric tools and experience necessary to begin conducting empirical research in finance.


The first part of this module covers a review of statistics and basic econometric models. The second part will concentrate on the application of econometric techniques in finance by considering such topics as (G)ARCH models, unit roots and cointegration.

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 literature.

  • To enable students to develop and apply those skills and techniques when writing their dissertations over the spring and summer terms.

Module learning outcomes

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



  1. To understand the OLS estimator and its limitations.

  2. To undertake estimation and tests of hypotheses using financial data.

  3. To use the EViews econometric package to obtain estimates and to be able to interpret the output from the package.

  4. To understand the econometric content in applied finance journals.

Module information

No additional information available.

Learning and teaching methods

This module will be delivered via:

  • One 2-hour lecture each week.
  • One 1-hour class each week.

Students will be assigned to a class and must attend that class.

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   2,000 word assignment   05/12/2023  50% 
Coursework   2,000 word assignment  29/01/2024  50% 

Additional coursework information

  • Two pieces of coursework (2,000 words each).

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 Christos Argyropoulos, email: c.argyropoulos@essex.ac.uk.
Dr Christos Argyropoulos
E: ebspgtad@essex.ac.uk

 

Availability
No
No
Yes

External examiner

Dr Nikolaos Voukelatos
University of Kent
Senior Lecturer in Finance
Resources
Available via Moodle
Of 48 hours, 30 (62.5%) hours available to students:
18 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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