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Description
Data analytics is essential in any financial institution to satisfy compliance demands, contribute to better decision making, enhance performance, and support the implementation of robust financial strategies. Thus, the purpose of this module is to learn the essential aspects of modern financial data analytics and big data applied in finance. In this module we will look into: 1) how data science affects different types of financial strategies 2.) the different types of data and applications, including predictive analytics, market risk, credit risk and customer segmentation. The module will devote particular attention to the modelling aspects of financial data. In so doing, it will provide the standard and most advanced modelling techniques, which include diversification, hedging and their limits. Students will have gained the skills and expertise needed to handle day-to-day financial operations.
On completion of this module, students will be able to:听
- demonstrate understanding of how vulnerability to financial risk arises and how to manage risk effectively in the banking system
- apply advanced modelling techniques of diversification and hedging
- apply statistical and mathematical tools, optimisation techniques and estimation of risk in regard to portfolio optimisation.
Module deliveries for 2024/25 academic year
Last updated
This module description was last updated on 8th April 2024.
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