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Computational Finance
INFT13-361
SUBJECT OVERVIEW
| Level: | Undergraduate Subject |
|---|---|
| Faculty/School: | Faculty of Business, School of Information Technology |
| Semesters Offered: | September 2013 - Standard |
| Credit Value: | 10 credit points |
| Subject Enquiries: | Email: business_reception@bond.edu.au |
| Study Abroad availability: | Available to Study Abroad students |
| Subject Outline: | September 2012 [ Standard ] |
University Subject Timetable
Synopsis
The aim of this course is to teach students how to design stockmarket trading strategies, both with and
without Soft Computing (Artificial Intelligence). The course teaches an underlying methodology for designing mechanical trading systems using advanced technologies, which was developed as part of the lecturers own PhD thesis.
The course provides students with access to advanced trading tools and development languages.
Students will learn how to use these tools and languages to create robust trading systems. The course has a strong emphasis on teaching the students how to find the answers to their own trading questions using the tools provided. The course also has a strong research component.
Prior Knowledge
Knowledge using a programming language is preferably but not essential.
Learning Objectives
Students will be expected to:
* Understand the role of mechanical trading systems
* Be able to use advanced tools to study risk/reward relationships in systems they develop
* Understand core issues related to stockmarket trading
* Grasp key trends in trading
* Understand the use of AI in the trading domain
* Be able to evaluate a trading system as fit for purpose
* Understand the role of a trader in the market