CF963-7-PT-CO:
Computational Models in Economics and Finance

The details
2023/24
Computational Finance and Economic Agents (Centre for)
Colchester Campus
Spring Special
Postgraduate: Level 7
Current
Monday 15 January 2024
Friday 28 June 2024
20
17 June 2022

 

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

 

(none)

Key module for

MSC L14112 Economics with Data Analytics

Module description

This module introduces students to computational thinking in economics and finance. Students are exposed to a variety of techniques in order to acquire a broad understanding of the challenges and potential the relevant industries are facing. The module takes both a theoretical and a practical approach to provide a competitive skillset.

Module aims

This module aims to introduce students to computational thinking in economics and finance by looking at different relevant models and theories, such as agent-based modelling and mechanism design. Students will also be introduced to various applications, such as financial forecasting and bargaining. Synergy will be explained i.e. students will be explained why some of the research in computation and finance or economics together can achieve something that they cannot achieve without the other.

Module learning outcomes

By the end of this module, students will:

1. understand the basics of computational theories and modelling.
2. understand the synergy between computation and economics/finance
3. appreciate applications of computational thinking in finance and economics

Module information

Topics of study:

Computational Finance:

Studying Financial Markets
Potentials and Limitations of Computation
Machine Learning Overview

Agent-based Approaches:
Agent-based Modelling (Zero-intelligence Agents)
AGT-Equilibria, Bargaining, Oligopolies (Rational Agents)
Mechanism Design

Blockchain:
Distributed Consensus
The Blockchain Protocol

Learning and teaching methods

Lectures discussing the theory of the course. Labs that put the theory to practice. Formative assessment through means like in-class quizzes. Summative assessment through one take-home assignment.

Bibliography

This module does not appear to have any essential texts. To see non - essential items, please refer to the module's reading list.

Assessment items, weightings and deadlines

Coursework / exam Description Deadline Coursework weighting
Coursework   Progress Test    20% 
Coursework   Assignment 1    40% 
Coursework   Assignment 2    40% 

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 Maria Kyropoulou, email: maria.kyropoulou@essex.ac.uk.
Ms Maria Kyropoulou
School Office, email: csee-schooloffice (non-Essex users should add @essex.ac.uk to create full e-mail address), Telephone 01206 872770

 

Availability
No
No
No

External examiner

Dr Anna Jordanous
University of Kent
Senior Lecturer
Resources
Available via Moodle
Of 57 hours, 38 (66.7%) hours available to students:
18 hours not recorded due to service coverage or fault;
1 hours not recorded due to opt-out by lecturer(s), module, or event type.

 

Further information

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