Finance and Data Analytics BSc (Hons)

ACFI101 aims to develop a sound understanding of the fundamental principles and techniques of financial accounting. The context and purpose of financial statements is introduced, after which students are introduced to the techniques of recording financial transactions, adjusting financial records and preparing basic financial statements. Successful students will possess a sound base of knowledge for progression towards studying financial reporting in greater depth in the second and final years: the preparation of complex financial statements in conformity with International Financial Reporting Standards (IFRS), both for single entities and groups of companies, and for entities undertaking a wide range of accounting transactions. This module is delivered by means of lectures and tutorials, supported by online self-study question material.

The module aims to provide an introduction to quantitative methods that will assist students in establishing basic quantitative and statistical skills for the study of accounting and finance.

This module will offer students opportunities to develop professional skills such as team work, presentation (oral and written), accessing, organising and presenting relevant information.

This module equips students with the tools to successfully analyse data. The module introduces students to programming with Python and highlights the usefulness of programming for data analytics. The module begins with an overview of various data types/structures. It then covers topics such as mathematical and logical operators, flow control, exception handling, functions, data exploration, and data wrangling. The seminar/lab sessions provide students with the opportunity to apply their knowledge by using Python to extract and analyse data. The assessment is conducted via a group project (50%) and an individual project (50%). Overall, the students will develop a range of skills, including communication skills, IT literacy, numeracy skills, and problem-solving skills.

This module introduces students to fundamental concepts in finance. The course aims to provide a firm foundation for the students to build on later on in the second and third years of their programmes, by covering basic logical and rational analytical tools that underpin financial decisions. The course covers topics such as the structure of firms and time value of money. Building on these notions, we then discuss the valuation of simple securities such as bonds and equities. The course also introduces students to project appraisal techniques.

This module equips students with the building blocks of economics that are important for a good understanding of finance. The course’s main aim is to develop the student’s understanding of decision-making in an uncertain world. The course discusses the concepts of risk, risk aversion, expected utility and their implications for portfolio choice. It also covers behavioural theories. The module presents both the theory and the empirical evidence, thus enabling the students to compare theory and practice.
Throughout the module, students will learn about the applications of these economic principles to decision-making when faced with risk and uncertainty. While the lectures introduce the conceptual framework, the seminars are more problem-based. The assessment is conducted via an individual exam (100%) at the end of the course. Overall, the students will develop a range of skills, including problem-solving and communication skills.

This module equips students with both theoretical and practical knowledge of computational methods used in the financial services industry. The module’s topic coverage includes: series expansion, root-finding, optimisation methods, interpolation techniques, quadrature, and simulation methods. The lectures introduce the key concepts while the seminars are more practical. During the seminars, students will apply their knowledge of computational methods through the use of Python. The assessment is conducted via a mid-term test (30%) and an individual project (70%) at the end of the module. Overall, the students will develop a range of skills, including communication, IT literacy, numeracy, and problem-solving skills.

This module introduces students to the graduate recruitment process by providing them with the skills required to secure a work placement or summer internship. It also provides the opportunity to acquire, develop and apply these skills.   

This module will cover the main issues related to financial reporting and its evaluation and analysis that is relevant for a graduate in finance. The module will also allow cover the topics specified under the heading Financial Reporting and Analysis as envisaged in the CBOK of the CFA. ​

Econometrics for Finance 1 is an important module that equips students with the knowledge of quantitative techniques and the practical expertise needed to solve finance problems. The course involves the analysis of real-world financial datasets to solve finance problems pertinent to a wide range of financial markets. This course is very relevant to students with a keen interest in the quantitative modelling of financial markets or those interested in pursuing an MSc degree in finance or related areas.
The lectures equip students with the theoretical knowledge necessary to formulate, estimate, and correctly interpret multivariate econometric models. In particular, the students will learn about multiple regression models, multiple hypotheses tests, diagnostic checks, and parameter stability. The seminar sessions, which take place in the computer lab, will provide students with the opportunity to apply their knowledge by using Eviews, a statistical software, to analyse real-world data from leading financial databases and solve finance problems. Overall, the students will develop a range of skills, including communication skills, digital fluency, analytical skills, and problem-solving skills. The assessment is conducted via a mid-term multiple choice test (30%), a written coursework (60%), and an individual pre-recorded video presentation (10%) at the end of the course.

This module introduces students to important corporate finance topics. The course will explore several questions including: How do firms choose between different sources of funding: equity and debt financing? Is there an optimal combination of equity and debt financing? How do firms select the projects to invest in? How do investors value a firm? Why do firms get involved in mergers and acquisitions (M&A)?
The course provides a detailed understanding of the key stages of the lifecycle of a firm. It starts by analysing the ways firms raise capital, e.g., initial public offering and bond issuance. It then discusses the various trade-offs associated with equity and debt financing and the optimal capital structure. Next, the course focuses on capital budgeting, namely the decision-making process associated with capital investment. Furthermore, the course sheds light on the valuations of firms and highlights the implications for mergers and acquisitions. Throughout the module, students will be exposed to prominent theories in corporate finance, the empirical evidence, as well as examples from the business world. While the lectures introduce the key concepts, the seminar provide students with the opportunity to discuss case studies and to confront the theories with real data from the finance industry. The assessment is conducted via a practical group project that consists in preparing an M&A pitchbook (40%) and an individual exam (60%). Overall, the students will develop a range of skills, including their commercial awareness, problem-solving, and communication skills.

Database management is increasingly important as digitalisation transforms the financial sector. A thorough understanding of database management systems, data security, and emerging applications for finance is provided. The module equips students with the knowledge and skills relevant to understand the challenges in managing large databases and ensuring data security. During the lectures, students will learn about the key concepts. The seminars are computer-based. In particular, they enable students to gain a practical understanding of database management systems, data security, and their importance for addressing business problems. The assessment is conducted via a group project (50%) and an individual project (50%). Overall, the students will develop a range of skills, including commercial awareness, IT literacy, and problem-solving skills.

This module will offer students the opportunity to critically reflect on the ethical dimension of finance. The module also critically evaluates the regulatory environment in which financial institutions operate.

This module builds on Econometrics for Finance I (ACFI225) to develop the students’ ability to design and implement the right empirical methodology to test finance theories. The emphasis on this module is on the effective use of programming, quantitative techniques, and the relevant data to answer real-world finance questions. The lectures introduce students to finance topics related to predictability, volatility modelling, event studies, and ethical issues in quantitative modelling. The seminar sessions, which take place in the computer lab, are mostly practical. They will provide students with the opportunity to apply their knowledge by using python, a programming language, to extract, process, and analyse data from industry databases. The course will involve the replication of academic studies to illustrate the applications of the concepts. The assessment is conducted via a group project (40%), an individual report (50%), and a presentation (10%) at the end of the course. Overall, the students will develop a range of skills, including communication, digital fluency, analytical, and problem-solving skills.

This module introduces students to key theories related to financial markets. It aims to shed light on a broad range of questions such as: What does finance posit about portfolio choice? What are the determinants of expected returns? How can one identify mispriced securities? Can investors really outperform the stock market?
The course starts with an analysis of portfolio choice. It then explores issues related to the pricing of securities in financial markets. The students will learn about the predictions of the most prominent theories and how to empirically test these predictions. Finally, the course will discuss the evidence from the “real-world”, thus enabling students to compare theory and practice. The seminar sessions will provide students with the opportunity to apply their knowledge by using real-world data to test financial market theories. Students will also develop their commercial awareness by evaluating the implications of the empirical results for market participants. The assessment is conducted via a mid-term MCQ assessment (30%) and an individual report (70%) at the end of the course. Overall, the students will develop a range of skills, including their commercial awareness, digital fluency, and communication skills.

A picture is worth a thousand words! As datasets become larger and more complex, it is critical to effectively and efficiently communicate their key features through visualisation tools. These visualisation tools must be easily understandable by end-users of varying levels of sophistication and languages. How should we design effective visualisation tools? What are the differences between various visual aids? How can we actually create the visual aids of interest? These are some of the questions that this module explores.
The course introduces the principles and techniques of data visualisation. It starts with a detailed discussion of important visualisation principles. It then introduces the students to Tableau, a data visualisation software that is very popular in the industry. Next, the module focuses on the visualisation of datasets across time and the design of maps. Building on this knowledge, the module focuses on interactive visualisations, motions, and dashboards. The students will learn to design effective visualisation tools. The hands-on seminar sessions, which take place in the computer lab, will provide students with the opportunity to apply their knowledge of Tableau to financial data. The assessment is conducted via a group project (30%), a pre-recorded video presentation (10%), and an individual project (60%) at the end of the course. Overall, the students will develop a range of skills, including their problem-solving , digital fluency, and communication skills.

In the last three decades, derivatives have become increasingly important in the world of …finance. Futures and options are now traded actively on many exchanges and OTC around the world. Yet most of our undergraduate finance courses, which mostly study underlying assets and institutions, simply do not have enough time for an in-depth discussion of derivatives. This class presents both a practical and theoretical approach to derivatives markets. The course starts with basic definitions and properties of put and call options, and forward and futures contracts. Payoff diagrams are used to illustrate these basic notions. Determinants of derivatives values are discussed. The basic no-arbitrage pricing relationships between different types of derivatives are established.

The module provides students with an opportunity to undertake an independent empirical research project under supervision and produce a dissertation in the style of an academic paper on a finance topic by drawing from their knowledge and skills. This module is strongly based on the University of Liverpool hallmarks of research-connected teaching, active learning and authentic assessment.

This module develops the students understanding of the banking sector and its interaction with the financial system. The course highlights the importance of banks in the financial system and how they operate. In particular, the course provides insights into their role in helping companies secure funding through capital markets and/or bank lending. The course then turns its attention to other important players in the financial system such as central banks, insurance companies, and pension funds.
By the end of this module, students will have a deep understanding of the business model of each major financial institution and its role in the financial system. While the lectures introduce the key concepts, the seminars provide students with the opportunity to deepen their understanding by analysing case studies and examples from the finance sector. The assessment is conducted via a mid-term MCQ assessment (30%) and a final exam (70%) at the end of the course. Overall, the students will develop a range of skills, including their commercial awareness and lifelong learning skills.

The module on Financial Risk Management covers both the internal aspects of financial institutions and the external factors that affect the investment arena and modern financial markets in general. The degree provides an in-depth understanding of the theoretical foundations that underpin modern investment and risk management techniques. The course has a strong practical dimension so you can acquire a sound knowledge of how to apply these techniques to equity and credit markets as well as investment strategies in general.

This module will provide an advanced, albeit non-technical, critical understanding for students with a variety of academic backgrounds of a number of current issues faced by both academics and practitioners in the area of finance for development. These will include, for example, trying to answer the question of whether foreign aid works, the impact of multinational firms upon the economy of host countries, the evolving roles of the IMF and World Bank and whether microcredit really provides a “silver bullet” solution to poverty. The module will also cover the main principles of Islamic Finance. This a very strongly research-led module. Finally, the module will have a developmental form of assessment in the form of a research-based proposal for a new textbook that will allow students to revisit the knowledge they have acquired in the module from a perspective of their choice like, for instance, de-colonisation of the curriculum, sustainability, environment, fintech, financial inclusion, gender.

The module will introduce students both to the theoretical arguments and the empirical evidence related to financial crises and defaults. The module will discuss in detail the main aspects of the recent financial crisis that shook the world economy including (a) the economic and financial environment in the years just before the crisis, (b) the causes of the crisis and (c) the action taken by policy-makers to deal with the crisis. The module will proceed by discussing the main aspects of the recent Eurozone debt crisis, as well as GREXIT and BREXIT issues. Noting the increasing role of social media both in becoming a popular open forum for analysing economic issues and reflecting public sentiment minute by minute, the module will draw on recent academic work to explain the impact of #Grexit tweets on the Eurozone bond market over and above the impact of economic fundamentals.

Some of the module content will be applied. In particular, using the econometric software EVIEWS and a number of macroeconomic and financial datasets, case studies will be developed to (a) test the adverse impact of excessive debt on economic growth for the G7 economies and (b) provide an empirical assessment of whether financial assets become mispriced prior, during and after financial crises. Students taking this module will need to have basic knowledge of macroeconomic and statistical theory as well as very basic knowledge of simple regression analysis. Prior knowledge of EVIEWS is not essential. A short introduction to EVIEWS will be offered as part of the module.

This module introduces students to cutting-edge techniques in the areas of data mining and machine learning. The module covers topics such as: regularisation techniques, classification techniques, deep learning methods, and natural language processing. The lectures expose students to the main concepts. The seminars provide opportunities for students to apply their knowledge to real-world datasets. The assessment is conducted via a group project (50%) and an individual project (50%). Overall, the students will develop a range of skills including IT literacy and problem-solving.

Behavioural finance attempts to explain several widely cited market phenomena (including e.g. excess volatility, overreaction, bubbles and crises) by drawing on concepts and principles from psychology and their applications in investors’ behaviour. The module provides a thorough introduction to this area, with theoretical analyses being enhanced through the use of short videos, experiments and quantitative finance both during lectures and seminars.

The module covers the history and development of corporate governance, and the key principles and systems that underpin corporate governance today. It also provides the opportunity to assess the practical application of corporate governance systems across major international organisations based on UK regulation.

This module focuses on recent developments in financial technology, their applications, and implications for the finance industry. What are the recent technological innovations relevant for finance? What are the potential benefits, challenges, and unintended consequences of these innovations? What can policymakers do to manage these innovations better? These are some of the questions that the module sets out to explore.
By the end of this module, students will have a deep understanding of the impact of financial technology on major areas of finance, e.g. banking and trading. The emphasis of this module is on commercial awareness, with classrooms discussions strongly encouraged during both the lectures and seminars. The assessment is conducted via a group report (40%), an individual report (50%), and an individual poster presentation (10%) at the end of the course. Overall, the students will significantly improve their commercial awareness and develop a range of skills, including their commercial awareness and leadership skills.

This module develops the student’s understanding of the financial industry by focusing on delegated portfolio management and alternative investments. The course is made up of two components. The first focuses on delegated portfolio managers, namely the financial institutions that manage assets on behalf of investors. In particular, we discuss the role of institutions such as mutual funds, asset managers, hedge funds, and private equity. Furthermore, we evaluate the risk profiles, fee structures, and investment strategies of these entities. The second component of the module focuses on alternative investments such as commodities and real estate assets. The course will discuss the salient features of these assets, their trading, as well as their historical performances.
By the end of this module, students will have a deep understanding of the delegated portfolio management industry. Furthermore, they will expand their knowledge of the asset menu by learning about alternative investments and comparing them to more conventional assets, e.g. stocks and bonds. The course will involve both lectures and seminars. The assessment is conducted via a mixture of a group coursework (30%) and a final exam (70%) at the end of the course. Overall, the students will significantly improve their commercial awareness and communication skills.