To provide an opportunity to undertake a sustained piece of individually researched academic study. Inter alia this provides a context within which research skills may be developed and demonstrated.
Finance with Python is a critical module for you to learn computer programming and perform financial data analysis. This module covers the use of Python in finance, including financial data analysis and statistical modelling, which includes an introduction to Python programming language, libraries, and tools commonly used in finance, such as NumPy, Pandas, Matplotlib, Jupyter Notebook and Google Colab. Lectures are followed by in-depth practical examples using tools that show real-world implications.
• Introduction. • Conceptualising Financial Statements. • Introduction to Double Entry & Accounting Equation & Trial Balance. • Adjustments: Accruals, Prepayments & Bad Debt. • Assets, Inventory, Depreciation and Disposal. • Sources of finance and Capital Structure. • Interpretation of accounts and the Business Model.
Financial accounting relates to the measurement and recording of business transactions. It underlies the annual reports published by companies which shareholders and other stakeholder use to assess the past performance of the business and make decisions about the future. We will consider how these reports are prepared and the ways in which management might influence the recording and presentation of the underlying transactions.
The module is intended to introduce students to regulation in financial reporting and to examine specific problem areas using a conceptual framework as a basis of the analysis. This allows an evaluation of current external reporting practice within the context of accounting theory. This will involve an examination of the regulatory framework of financial reporting, i.e. UK Company law, the UK Accounting Standards Board and the International Accounting Standards Board. Significant accounting issues which have been the subject of legislation or accounting standards will be analysed.
The module builds on MANG6030 Financial Accounting 1 and exposes students to various accounting theories and approaches to further their understanding of accounting developments nationally (UK) and internationally. The module also exposes students to some of the complex and current issues related to accounting measurements, employee benefits, financial instruments and group accounts.
It is a continuation module from financial accounting 2. Students will be exposed to more advanced knowledge of accounting such as consolidated group financial statements, financial instruments and share based payment.
Capital markets require information in order to function effectively, for example in the valuation of firm shares and other financial securities. An important element of the available information, for example, concerns financial performance. However, the process of measuring a firm’s financial performance is inherently subjective. For example, the measurement of profit (earnings) is dependent on a variety of estimates surrounding the recognition and quantification of revenues and expenses and the recognition and valuation of assets and liabilities. Furthermore, firm managers and accountants have to make choices of equally acceptable accounting policies subject to a number of economic incentives of both the internal and external economic agents of a firm. In the context in which financial reports are prepared, the outcome of the reporting process is essentially a trade-off between multiple incentives, for example, of the information preparers and the needs of other economic agents external to the firm concerned. This can be a problem because external economic agents may not be able to directly observe the processes, judgements and incentives facing information preparers. Therefore, this module will provide you with the opportunity to learn how to evaluate the extent to which financial accounting and reporting processes produce relevant information. You will learn the incentives facing firms, managers and accountants in providing financial accounting and other related information to external users, and the techniques and procedures that external users may employ in processing the information.
This module offers a comprehensive exploration into the intricacies of managing financial risks within the shipping industry. From foundational principles surrounding shipping markets to advanced applications of financial derivatives, this course equips students with a deep understanding of risk factors such as freight rates, bunker price volatility, credit risks, and interest rate impacts. By integrating theoretical learning with practical applications, including the strategic use of real options and ship price risk management, the module prepares students for careers in shipping and finance, where they can apply their skills to effectively navigate and mitigate risks in global shipping operations.
The module studies quantitative techniques for pricing the main financial derivatives available for trading in financial markets. This is done under assumptions imposing absence of arbitrage opportunities in financial markets. The module focuses on futures and forwards on bonds and stocks, swap contracts and stock options. The module also introduces students to more advanced techniques for pricing derivatives such as binomial trees and Black-Scholes model.
The module will introduce you to various topics drawn from the modern empirical finance literature and to the underlying econometric techniques used to evaluate alternative models of the dynamics of asset prices and returns. Knowledge of basic econometrics (such as that covered by ECON6068 Quantitative Economics) is a pre-requisite. Software such as EViews or R will be used to give practical illustrations. Successful completion of this module is of particular value if you intend to prepare an empirical dissertation involving financial applications as the final component of your MSc programme.
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.
