PURPOSE OF THE PROGRAMME

The programme aims to develop sound conceptual, technical, analytical and problem-solving skills that are required to succeed in the Finance and Banking profession. Students will be expected to exercise their analytical abilities and develop effective verbal and written communication skills.

3. ENTRY REQUIREMENTS

To qualify for admission into the Master of Commerce degree in Finance and Digital Banking programme, a candidate should have an honours degree in Finance, Banking, Economics, Accounting or their equivalents.

4.CAREER OPPORTUNITIES AND FURTHER EDUCATION

• The Master of Commerce degreein Finance and Digital Banking provides employment opportunities in the following institutions; Commercial Banks, Merchant Banks, Building Societies, Discount Houses, Finance Houses, Asset Management Companies, Stock Exchanges, Stock Broking Firms, Insurance Companies, Microfinance Institutions, Central Banks and Academic institutions. The programme hence enables careers in the above institutions as Executive Bank Managers, Retail Banking Managers, Treasury Managers, Treasury Dealers, Financial Advisors and Financial Analysts, Bank Examiners, Risk Managers, Personal Bankers, Customer Relationship Managers, Credit Analysts, Business Development Managers and Lecturers.  There is also a possibility for entrepreneurship in the form of micro-financing and financial consultancy.
• Holders of the Master of Commerce in Finance and Digital Banking Degree are eligible for Doctoral studies in specialised areas Finance and Digital Banking.

 

5. GENERAL PROVISIONS

ormal examinations will be held at the end of each semester.

For a student to be admitted to the examinations they must have:

5.2.1 Satisfactorily attempted approved modules of study including submission of required written assignments.

5.2.2 Attended compulsory classes

5.2.3 Participated in prescribed seminars, tutorials and practical classes.

5.2.4 Paid the prescribed fees in accordance with the General Regulations.

5.3 Formal examinations will normally be written papers, but in some cases the examiner may test the candidate orally.

5.4 Continuous assessment shall account for 40% of the overall assessment, while the final examination will account for 60% of the overall assessment.

5.5 The aggregate pass mark shall be 50%.

A student requires a minimum of 360 credits to complete this programme.

6. ASSESSMENT

Refer to Section 6 of the General Regulations and Section 5 of the Faculty    Regulations.

7. PROVISION FOR PROGRESSION

Refer to Section 6 of the Faculty Regulations.

 PROGRAMME STRUCTURE

Level 1 Semester 1

Code	Module Description	Credits
MFDB732	Advanced Financial Econometrics and Data Analysis	18
MFDB733	Advanced Corporate Financial Strategy	18
MFDB734	Digital Banking and New Customer Experience	18
MFDB731	Global Financial Markets	18
MFDB735	Monetary Systems and Digital Finance	18
MFDB736	Research Methodologies	18

Level 1 Semester 2

Code	Module Description	Credits
MFDB738	Financial Modelling and Forecasting	18
MFDB739	Strategic Risk Management	18
MFDB740	Applied Treasury Management	18
MFDB737	Strategic Investment Management	18
MFDB741	Financial Analytics and Machine Learning	18

Level 2 Semester 1

Code	Module Description	Credits
MFDB831	Corporate Governance and Ethics	18
MFDB832	SQL For Financial Data	18
MFDB833	Dissertation	90

MODULE SYNOPSES

MFDB731 Global Financial Markets

This module aims to provide an in-depth knowledge of financial markets and the main types of securities traded in these markets. The module will focus on money and capital markets products, futures, swaps and options. The module will strike a balance between the theoretical paradigms and the empirical literature and the important links between theory and the real world. The emphasis will be on both principles and problem-solving.

MFDB732 Advanced Financial Econometrics and Data Analysis

This module aims to explain how econometric methods can be used to learn about the future behaviour of the prices of financial assets by using information on the history of asset prices and the prices of derivative securities. The specific objectives of the course are to introduce a range of statistical techniques and indicate criteria by which one might judge the appropriateness of each method, identify the decision situation in a problem, formulate and solve econometrics problems and formulate and solve multi-stage problems. The following shall be covered, linear regression, multiple linear regression, qualitative response regression models, panel data regression time series analysis, etc. Emphasis will also be put on the ability of students to interpret the statistical results and make decisions based on the results.

MFDB733 Advanced Corporate Financial Strategy

The module is an extension of advanced corporate finance. The module aims to develop and apply the fundamental ideas and tools for corporate finance to real-world decisions. The module will focus on corporate strategy, capital structure, dividend policy, capital budgeting, real options, mergers, acquisition and restructuring. After completion of this module, students are expected to be able to value, analyse and make informed financial decisions for business organisations.

MFDB734 Digital Banking and New Customer Experience

This module intended to provide students with a critical and in-depth understanding of digital banking products. This module will enable the students to understand the significance and application of various digital banking products such as credit and debit cards, mobile money services, internet banking and ATMs. The emphasis will be on how electronic banking platforms can facilitate a good customer experience, the risks involved with such platforms and the benefits that such platforms have to the financial sector and the economy.

MFDB735 Monetary Systems and Digital Finance

The module aims to provide students with mastery of global monetary systems, the role of the Central Banks, and the evolution of modern payment systems, which includes digital currencies and the future of monetary systems, crypto-currencies and central bank digital currencies (CBDC): digital assets and blockchain technology. The module will also look at the global financial system’s history and how they currently function. Students will also understand the theoretical and empirical underpinnings of money, central banking and monetary policies.

MFDB736 Research Methodologies

This course covers how they are used to examining relating to their studies. Quantitative, qualitative and mixed measures are all differentiated in this course. Students will be practically exposed to the main components of a research framework, i.e., problem definition, research design, data collection, ethical issues in research, report writing, and presentation. Once equipped with this knowledge, participants would be well‐placed to conduct disciplined research under supervision in an area of their choosing.

MFDB737 Strategic Investment Management

This course focuses on the theory and practice of modern portfolio management. In addition to providing in-depth discussions of portfolio construction, monitoring and evaluation will allow students to gain hands-on experience through case studies and portfolio simulation. Topics covered in this course include Adaptive Market Efficiency, Black-Litterman Portfolio Selection, Asset Price Bubbles and Systemic Risk, International Equity and Bond Investing, Derivatives and Portfolio Management.

MFDB738 Financial Modelling and Forecasting

The module aims to provide hands-on specialisation to students with sound knowledge of modelling techniques and typical applications for investment analysis, company valuation, forecasting, and spreadsheet models. The module teaches how spreadsheets work and how they may be used to build scenarios, predict performance and make informed business and financial decisions. It also teaches how to manage large datasets efficiently, extract meaningful information from them, and present information effectively. By the end of the module, students should be able to use different computer software to solve corporate finance problems such as optimisation of lifetime investments, asset pricing, Capital Budgeting, Decision Tree Analysis, Sensitivity Analysis, Computer Simulations, and Business and Securities Valuations.

MFDB739 Strategic Risk Management

Given the volatile global economic environment, organisations are vulnerable to financial risk, particularly funding and liquidity, market, credit, and operational risk. This module covers one of the core functions of finance, namely risk management. On successful completion of this module, the student should be able to understand risk and a risk management framework,  identify the types of financial risk faced by an organisation, apply a practical approach to assessing, monitoring and managing an organisation’s financial risk,  understand the funding, liquidity, interest rate, foreign exchange, commodity price, credit and operational risk faced by organisations, advise an organisation on managing long term investments, understand the nature and characteristics of derivatives, advise an organisation on the types of financial instruments that could be used to manage best manage an organisation’s financial risk best, demonstrate the practical elements of accounting for derivatives for both embedded derivatives and derivatives used for hedging purposes.

MFDB740 Applied Treasury Management

This module concerns how the Treasury function operates in financial and non-financial environments. The key objective of the module is to equip students with an understanding of a wide range of theoretical financial concepts, tools and techniques as applied to treasury activities, including the key functions of an Active Treasury Department and the latest trends in Treasury Management. The module covers concepts such as the trade-off between risk and return, asset allocation, and security analysis in the investment management process. It further examines the design and implementation of formal performance measurement and management control systems in a business-, particularly a banking institution. Furthermore, the module synthesizes the theory and practice of treasury management.

MFDB741 Financial Analytics and Machine Learning

This course teaches you why, when, and how to apply financial analytics in real-world situations. You will explore techniques to analyse time series and panel data and how to evaluate the risk-reward trade-off expounded in modern portfolio theory. The course delves deeper and explores best practices in understanding time-series data, creating forecasts, and determining the estimates’ efficacy using concepts such as the Receiver Operator Curve and the Kolmogorov-Smirnov tests, to mention just a few.

MFDB831 Corporate Governance and Ethics

Governance is a continually developing subject, and promising candidates will be aware of any major developments that have occurred at the time they take their examination. This course introduces students to corporate governance principles with a strong Zimbabwe emphasis, and it is expected that Zimbabwe’s corporate governance will be the focus of the study. Students are expected to demonstrate a good knowledge of the principles and provisions of corporate governance as regulated by the Companies Act (Chapter 24:03) and Zimbabwe Stock Exchange Act (Chapter 24:18) (ZSE) listing requirements, Public Finance Management Act (Chapter 22:19) (PFMA) as well as the rules of various professional bodies such as the Institute of Directors of Zimbabwe (IoDZ). Moreover, good knowledge and understanding of the code of corporate governance in other countries will be acceptable, particularly the King III report of South Africa.

MFDB832 SQL for Financial Data

This course is intended to build on the financial modelling course and introduces students to topics such as SQL basics, data wrangling, SQL analysis, AB testing, distributed computing using Apache Spark, and more. These topics will prepare students to apply SQL creatively to analyse and explore data; demonstrate efficiency in writing queries; create data analysis datasets; conduct feature engineering; use SQL with other data analysis and machine learning toolsets; and use SQL with unstructured data sets.

MFDB833 Dissertation

The dissertation shall be undertaken once the research method course has been completed. The student will submit a project report, which will be evaluated (end-semester assessment) by the duly appointed examiner(s). This evaluation will be based on the