| CODE | BKF2110 | |||||||||
| TITLE | Algorithmic Trading | |||||||||
| UM LEVEL | 02 - Years 2, 3 in Modular Undergraduate Course | |||||||||
| MQF LEVEL | 5 | |||||||||
| ECTS CREDITS | 4 | |||||||||
| DEPARTMENT | Banking and Finance | |||||||||
| DESCRIPTION | Financial investors and experts have always attempted to trade and forecast the movement of stock markets. Current market information, news and external factors affect the investors' trading decisions concerning buying and selling. The prediction of financial time series is a very complicated process. An initial look at a financial time series gives the impression that they are random in nature, a characteristic that would make the forecast, and therefore trading, of such series very difficult. The Efficient Market Hypothesis states that the current price contains all of the available information in the market. This leads to the predictability of most financial time series such as stock prices or indices being a rather controversial issue. Algorithmic trading is concerned with designing expert systems for such an unpredictable and unstable entity (financial markets). In this study unit, students will be introduced to various standard techniques that are currently used by various financial institutions in order to trade financial markets. Study-unit Aims: This study-unit, which is lab based, will serve to: - Introduce participants to the principles of financial markets modelling and give an overview of financial trading; - Introduce participants with no previous programming experience to the area of financial systems programming, as well as to the design and application of simple trading strategies; - Develop modelling skills necessary for solving real-life problems in automated trading; - Provide financial evaluation of the developed trading strategies, and give the knowledge and understanding of the mechanisms driving today’s markets and financial institutions. Learning Outcomes: 1. Knowledge & Understanding: By the end of the study-unit the student will be able to: - comprehend the theory and practice of programming trading systems; - comprehend the most common algorithmic trading strategies; - describe mechanisms of program execution and data processing. 2. Skills: By the end of the study-unit the student will be able to: - combine theoretical analysis in the wider context of problem solving and system design; - use problem solving strategies to overcome major obstacles; - demonstrate own learning and performance through lab sessions; - develop problem solving skills through the identification of strategies used to solve problems; - implement simple trading strategies. Main Text/s and any supplementary readings: - K. Kim (2007) Electronic and Algorithmic Trading Technology: The Complete Guide. Academic Press. Supplementary Text - Brandimarte, P. (2002). Numerical Methods in Finance: A MATLAB-BasedIntroduction. John Wiley & Sons. - An Introduction to Matlab by David F. Griffiths. http://www.maths.dundee.ac.uk/~ftp/na-reports/MatlabNotes.pdf |
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| ADDITIONAL NOTES | Pre-requisite Study-unit: BKF1100 | |||||||||
| STUDY-UNIT TYPE | Lecture | |||||||||
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The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication.
The availability of optional units may be subject to timetabling constraints. Units not attracting a sufficient number of registrations may be withdrawn without notice. It should be noted that all the information in the description above applies to study-units available during the academic year 2023/4. It may be subject to change in subsequent years. |
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