This course aims to equip students with a solid understanding of the latest financial technologies, including blockchain, cryptocurrencies, payment and lending, and robo-advisors, as well as the analytical skills necessary to interpret and leverage financial data through Python programming. It combines theoretical knowledge with hands-on practical skills, preparing students for a variety of roles in the fintech industry.
This course introduces machine learning, artificial intelligence and forecasting with applications in finance. The course will explore recent trends in financial technology (FinTech), which are based on data analytics and recent advances in machine learning. The course is based on Python, which has become the dominant general-purpose programming language in data analytics and machine learning.
This course examines theories and issues relevant to portfolio analysis. Themes include: risk and return; investment motives; the application of modern portfolio theory (including the Capital Asset Pricing Model); information and market efficiency; portfolio analysis and asset pricing; bonds and equities; real estate and derivative markets.
The overall learning aim of this course is to enable students to understand the importance of big data in the context of international business and recent innovations in green finance and FINTECH. In addition, students will learn some basic Python to develop skills in data analytics and machine learning.
The main aim of the course is to introduce the fundamental principles of the theory and practice of business finance and a sound basis for further study of advanced accounting and finance theory and cognate disciplines.
The overall learning aim (goal) of this course is to equip students with good analytical skills in order to develop a framework for business analysis and valuation using financial statement data in a variety of contexts.
This course aims to provide students with the quantitative skills to undertake extended investigation of financial data and assist in financial decision making.