## BE368-7-AU-CO:Finance Research Techniques Using Matlab

The details
2023/24
Colchester Campus
Autumn
Current
Thursday 05 October 2023
Friday 15 December 2023
20
15 September 2023

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

(none)

## Key module for

MRESN30012 Finance,
MSC N34212 Financial Engineering and Risk Management,
MSC N34224 Financial Engineering and Risk Management,
MSC N3G312 Finance and Data Analytics

## Module description

The aim of this module is to introduce students to the software package Matlab and to provide them with the necessary skills to utilise the software to analyse financial data.

## Module aims

The aims of this module are:

• Develop and transmit knowledge about the Matlab software package and its usefulness in financial applications.

• Give students knowledge of a number of key concepts in empirical finance and how Matlab can be used to analyse empirical data.

• Provide students with a firm foundation for developing their own programmes in Matlab to tackle non-standard testing problems.

## Module learning outcomes

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

1. Have an understanding of matrix algebra and how matrices and vectors can be manipulated in Matlab.

2. Import data and manipulate series in Matlab to calculate financial measures.

3. Construct an optimal or minimum variance portfolio and the efficient frontier.

4. Understand the concept of regression and perform regressions in Matlab.

5. Test for non-stationarity in financial data and examine the possibility of cointegration between one or more series.

6. Have a basic understanding of the Black-Scholes option pricing model and how option prices can be calculated using a Matlab toolbox.

7. Use loop commands in Matlab to perform multiple calculations and understand the relevance of these commands in performing Monte Carlo simulation exercises.

## Module information

Students will be taught the usefulness of matrix algebra and how vectors and matrices can be manipulated in Matlab. Following this introduction, they will be taught how the software can be used in a number of financial applications including portfolio optimisation, testing for unit roots, cointegration and option pricing. A brief introduction to simulation will also be covered.

## Learning and teaching methods

This module will be delivered via:

• One 1-hour lecture per week.
• One 1-hour class per week.

Students will be assigned to a class and they 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   BE368 Coursework   18/12/2023  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.

Coursework Exam
50% 50%

### Reassessment

Coursework Exam
50% 50%
Module supervisor and teaching staff
Dr Efthimios Nikolakopoulos, email: e.nikolakopoulos@essex.ac.uk.
Dr Efthymios Nikolakopoulos & Dr Servanna Fu

Availability
No
No
Yes

## External examiner

Dr Nikolaos Voukelatos
University of Kent
Senior Lecturer in Finance
Resources
Available via Moodle
Of 20 hours, 16 (80%) hours available to students:
4 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