BE369-7-SP-CO:
Data Analysis: Cross Sectional, Panel and Qualitative Data Methods

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

 

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

 

(none)

Key module for

MRESN30012 Finance,
MSC N3C112 Financial Technology (Finance),
MSC N3C124 Financial Technology (Finance)

Module description

The primary purpose of this module is to provide the student with an understanding of non-time-series data analytic approaches in finance. It covers methods for cross-sectional, panel and qualitative analysis and their applications. All topics are illustrated with relevant examples. The weight given to topics reflects the extent to which methods are used in finance and therefore panel methods are emphasised.

Module aims

The aims of this module are:



  • To enable students to understand the different methods of data analysis in finance.

  • To enable students to critically evaluate the techniques above and apply them in corporate finance and banking.

  • To understand the nature and scope of financial research and its relevance to finance practice.

  • To understand and discuss critically the relevant literature on financial research.

  • To demonstrate a critical appreciation of various research approaches along with an awareness of both their contribution and limitations.

  • To evaluate different research methods (qualitative and quantitative) and understand their benefits and limitations.

Module learning outcomes

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



  1. Demonstrate a critical understanding of the use of cross-sectional, panel and qualitative data which can be used in areas of finance such as corporate finance and banking and their applications.

  2. Acquire experience of gathering and analysing qualitative and quantitative data.

  3. Use a personal computer to code, transform and analyse panel, cross-sectional and survey data.

  4. Utilise and source information from the library, internet and database sources.

  5. Undertake predictive estimations and tests of hypotheses using financial data.

Module information

Students must have a basic background in econometrics. The course assumes an understanding of core econometrics and time series methods.


Cross-sectional data are organised over individual groups (eg households, firms or countries) and have no time dimension. They may include discontinuous data (eg binary). Qualitative or categorical data are essentially non-numerical. Examples include survey responses, textual analysis of social media or interviews. Panel data or longitudinal data are multi-dimensional data involving measurements over time. As such, panel data consists of researcher's observations of numerous phenomena that were collected over several time periods for the same group of units or entities. For example, a panel data set may be one that follows a given sample of individuals over time and records observations or information on each individual in the sample. The nature and advantages of panel data has led to numerous applications in finance and economics research.

Learning and teaching methods

This module will be delivered via:

  • One seminar per week.

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 words take home assignment   19/03/2024  100% 
Exam  Main exam: In-Person, Open Book, 120 minutes during Summer (Main Period) 
Exam  Reassessment Main exam: In-Person, Open Book, 120 minutes during September (Reassessment Period) 

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
50% 50%

Reassessment

Coursework Exam
50% 50%
Module supervisor and teaching staff
Prof Sotirios Kokas, email: skokas@essex.ac.uk.
Dr Sotirios Kokas, Dr Onur Sefiloglu & Prof Shahzad Uddin
ebspgtad@essex.ac.uk

 

Availability
No
No
Yes

External examiner

Dr Aris Kartsaklas
Brunel University London
Senior Lecturer
Resources
Available via Moodle
Of 16 hours, 16 (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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