Financial Econometrics 1 provides you with the necessary skills to undertake quantitative research in finance. Lectures will introduce a broad range of topics (e.g. regression). However, you will discover that by understanding and applying some basic concepts various issues can be analysed in a similar manner. In particular, we will introduce basic theoretical concepts developed in statistics and econometrics. Understanding the main theoretical methods is essential to appreciate the analytical tools and their applications to finance. Tutorials take place in labs where you will be able to conduct your own research via the software EViews. The module introduces empirical methods used in finance and is a prerequisite for Financial Econometrics 2 in the 2nd semester.
The module is intended to build on Financial Econometrics 1 and offers a deep understanding to undertake empirical research in finance. Lectures will cover topics from introductory level to more advanced econometrics material. The students will learn how to use the EViews software through practical examples, and be able to conduct their own empirical research via the software.
This module will provide students with a solid understanding of key concepts, tools and insights of financial economics. Upon completion, students should be confident in using standard techniques to address issues like the functions and functioning of financial markets, and their efficiency properties, as well as be able to deal with standard application of financial theory to equity and bond pricing.
This module provides a deep insight in some key theories and topics in Financial Management. The module looks at how firms and corporation manage financial investment and decisions in the long term and short term. The module will discuss topics ranging from how firms evaluate financial performance, decision regarding investment in capital, how firms decide in dividend policy.
This module provides a solid mathematical introduction to the subject of Compound Interest Theory and its application to the analysis of a wide variety of complex financial problems, including those associated with mortgage and commercial loans, the valuation of securities, consumer credit transactions, and the appraisal of investment projects. The investment and risk characteristics of the standard asset classes available for investment purposes are also briefly considered, as is the topic of asset-liability matching. The module also provides introductions to the term structure of interest rates, simple stochastic interest rate models, the concept of no-arbitrage pricing of forward contracts, and behavioural economics. Pre-requisite for MATH6127
This module provides a solid mathematical introduction to the subject of Compound Interest Theory and its application to the analysis of a wide variety of complex financial problems, including those associated with mortgage and commercial loans, the valuation of securities, consumer credit transactions, and the appraisal of investment projects. The investment and risk characteristics of the standard asset classes available for investment purposes are also briefly considered, as is the topic of asset-liability matching. The module also provides introductions to the term structure of interest rates, simple stochastic interest rate models, the concept of no-arbitrage pricing of forward contracts, and behavioural economics.
The module aims to introduce the students to the basics of portfolio theory. Beginning with a summary of the reasons why both private investors and large institutional investors might wish to own share portfolios, the module progresses to consider how risk and return vary as share prices move and introduces the student to the basics of Markowitz portfolio theory. Illustrative two-asset cases will then be considered before the risk/reward diagram for an N asset portfolio is examined. The notions of short selling and riskless assets will then be introduced to the student and incorporated into the theory. Finally, the student will learn how to solve the general Markowitz portfolio problem to determine the Optimum portfolio, the Capital Market Line and the Market Price of Risk. If time permits, discussion will also take place of more advanced models of portfolio theory.
Students will be introduced to the regulation of financial reporting; the information perspective to financial reporting; the valuation relevance of financial reporting; economic consequences and Positive Accounting Theory; Earnings management.
The module explores bank regulations as well as theoretical and practical techniques to measure market risk, interest rate risk and credit risk. It also discusses the theoretical and practical aspects of the risk management techniques employed in the financial services industry to hedge market risk, interest rate risk and credit risk.
The module seeks to equip students with essential practical and technical skills that are critical for success in the financial sector. It is designed to develop students' competencies in key areas such as financial data analysis, financial modelling, programming for finance, use of industry-standard databases, and effective communication of financial information. Through a combination of workshops, case studies, simulations, and certifications, students will acquire the applied knowledge and transferable skills that are highly valued by employers across a range of financial careers.
Many real-world engineering structures are too complex for their behaviour to be understood using an ‘exact’ analytical or theoretical method alone. Therefore, in practice we often use approximate numerical or simulation-based tools for structural analysis, of which Finite Element Analysis (FEA) is the most established. The Finite Element Method (FEM) unlocks the ability for engineers to predict the performance of complex structures in detail, including their deformations and stresses generated by mechanical loads, and their free and forced vibration. However, the predictions obtained from these simulations are only as reliable as the data used to generate them, and this is limited by necessary simplifications and assumptions. A skilled FE analyst understands the assumptions and limitations of the method, and they can make best use of the range of commercial FEA software packages available by drawing on an understanding of the theory behind the simulations. This module is aimed at providing the requisite background theory and practical experience of solving problems using the Finite Element Method. It provides fundamental knowledge and an understanding of the technique of FEM, equipping students with tools to analyse engineering structures problems using FEM and typical commercial FEA packages.
