International Finance (with optional Placement/Project year) MSc

The module will enable you understand business concepts, techniques and methodologies of strategic financial management, which are essential to decision-making. 

Indictive contents are:-

• Strategic Management Accounting, The role of Management accountants, Costing, Budgeting.
• Strategic financial accounting – Analysis of financial reports and financial accounts, Ratio analysis.
• Non-financial reporting and analysis, SWOT, PEST and other models.

This module aims to equip students with adequate financial knowledge of corporate finance including investing, financing and dividend decisions in an international context. 

The indicative contents of the module are as follows:-

• Corporate Investment decisions and International Finance
• Global Contexts for investment decision making and strategy
• International context of Corporate Finance planning
• Capital structure and corporate value
• Shareholder value - Financial market structures and products
• The relationship between economic events, interest rates and foreign currency 
• Workings of the capital and money markets

The intention of this module is equip students with the skill set of analysis data to enhance the quality of financial decision making. There is solid evidence to suggest that for you to competitive as a finance, fintech, banking or accounting graduate, you must possess the skill of data story telling - analyse and interpret data to justify decision made by the organisation. It is therefore not surprising to see that jobs advertised within your course area tend to include the skill of data analysis as an essential criteria in most cases. This module seeks to address the specific need of quantitative data analysis skills captured in all subject benchmarks within the subject grouping of your course. Therefore, to help you develop these set of skills, the following indicative contents will be covered in this module. 

• Data - sources of financial data collection, instrumentation for collecting financial data, databases such as FAME-Financial Analysis Made Easy (FAME), Yahoo Finance, Investing.com, Ms Office 365 (powered by Refinitiv). 
• Techniques for cleaning data for further analysis - missing data and removing text from data in Ms Excel
• Introduction to software for analysis data - for example, MS Excel, SPSS, STATA and AMOS. The use of Analysis ToolPak and Solver in Ms Excel. 
• Descriptive statistics - measures of central tendency - arithmetic, geometric and harmonic means, median and mode. Measures of dispersion - standard deviation, variance, quartiles, coefficient of variation, covariance, skewness and kurtosis.
• Hypothesis testing, the null and alternative hypotheses, 1-tail and 2-tail, levels of significance and confidence intervals.
• Predictive analytics (inferential statistics) - forecasting techniques - correlations, regression, t-test, time series analysis (auto regressions and moving averages).
• Applications of quantitative techniques for investment appraisal analysis, portfolio optimisation, Monte Carlo simulation, currency dashboards, market risk estimation (beta).
• Data visualisation techniques using advanced Ms Excel.

The coverage of these key data analytics techniques will give you the confidence to contribute to financial decision making using available data. Note that, you will cover these topics in an experiential learning setting - full participation using your laptop or assigned computers to examine each of the topics. There is an expectation that the confidence gained through the manipulation of data with software and key statistical concepts will give you the competitive edge along your career. 

This module develops students' research skills via studying various research methodologies and methods including how to collect and analyse quantitative and qualitative data in accounting and finance. 

Indictive contents include:-

• Developing the research idea (case study, business development proposal and dissertation)
• Theory, literature and hypotheses 
• Research ethics in accounting and finance
• Data collection, sources, measurements, cleaning, summary (descriptive statistics)
• Big Data (4Vs - Volume, Velocity, Veracity and Variety)
• Inferential statistics (predictive analytics)
• Quantitative and qualitative research approaches
• Software - Power BI, SPSS, AMOS, Advanced Ms Excel, Stata, NVivo and others
• Specific techniques for case study, business development proposal and dissertation. 

This module develops students' awareness and understanding of corporate governance frameworks in accounting and finance. It also covers the nature of financial and non-financial risks and the key components of risk management systems as well as the analysis and application of corporate governance principles in relation to risk management.

Indictive contents are as follows:-

• The development and the changing nature of corporate governance regulations
• Corporate governance theories.
• Challenges in corporate governance.
• Corporate governance standards, best practice and recommendations.
• Corporate governance in private and public organisations.
• Internal control systems.
• Enterprise risk.
• Strategic risk.
• Cyber risk.
• Reputational risk.
• Economic and credit risk
• Interest rate and currency risk.

This module involves an independent study and a research project in accordance with established research principles involving the completion of the following elements:

• Introduction to Accounting and Finance research
• Critical review of literature for an Accounting and Finance research project
• Evaluation of appropriate data collection methods
• Data analysis techniques for various research strategies
• Resource and risk planning in research
• Undertaking Accounting and Finance research

This module provides opportunities for students to solve business case studies (including live cases) and justify the solutions that have been put forward from an available pool of different solutions and scenarios. 

Indicative contents:-

• Introduction to Case Study Analysis – mini, macro, and integrated business case study
• A modelled approach to case study analysis for decision making
• Assessing the challenges within the live case study
• Problem Identification & Analysis
• Assumption setting and strategic business planning related to case study
• Objectives, strategies, action plans, by function to time scales
• Application of key quantitative and qualitative techniques
• Monitoring, review & control planning for performance
• How to write a case study report
• Pitfalls of case study analysis

The module is your independent final project, similar to a dissertation.

In this module, you'll take the lead in creating a comprehensive business proposal. You will begin by researching the legal requirements necessary to start a business and then move on to developing its strategic direction, including defining its mission, vision, and identifying valuable market opportunities.

You are expected to incorporate financial details, exploring funding options and developing financial forecasts. Your project also involves conducting a thorough stakeholder analysis, honing your networking skills, and pitching your business idea to potential investors through the report.

This module places a strong emphasis on ethical and sustainable business practices, challenging you to incorporate these critical elements into your proposal. Through this project, you will demonstrate your ability to synthesise and apply your learning to develop a well-rounded, strategically sound business proposal based on rigorous research and comprehensive analysis. This is your opportunity to showcase your entrepreneurial skills and innovative thinking in a real-world context.