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Below are the list of course for the M.Sc. Banking and Finance program for the University of Ibadan. Click on the toggle buttons to read each course overview and then procced to download the course modules individually.
The course analyzes financial markets conceptually and theoretically, and emphasizes the role, structure, and activities of financial intermediaries. Demand for and supply of money, the dynamic pattern of financial flows is analyzed by flow of financial funds, and uses/sources of funds, models of the process of financial intermediation and the theory of the banking firm. The crucial role of interest rate and structure of interest rates are analyzed. Also analyzed are the regulatory framework and its impact on banking operations, market structure and performance of the financial intermediation functions of the institutions.
This course will cover areas like nature of the firm and corporate objectives; implementation of the firm’s goals for choice among alternative investment projects (the capital budgeting problems); market evaluation of non-assets under uncertainty and implication for capital budgeting, analysis and illustration with problems of alternative investment criteria; alternative approaches to value of the firm and the cost of capital: discussion of corporate financial problems; e.g. leasing, mergers and acquisitions, and issuance of new securities.
This course aims at giving the students quantitative skills necessary for banking and financial decision- making. The focus of the course will be more of application rather than of the theory per se. It covers descriptive statistics, probability and expectations, discrete and continuous distributions, and statistical decision theory, study of estimation, tests of hypotheses and confidence intervals. Time series Analysis, Index Number with applications in finance, multiple regression, including correlation analysis. Also, it includes inventory, forecasting, queuing models, analysis of variance, and use of computer with application to finance. Linear Programming, simplex algorithm, large mathematical programme, decomposition integral programming, convex and geometric programming, etc.
The course is designed to train students in the skill of scientific information gathering, analysis and interpretation in dealing with problems in finance and related topics. Through reading, assignments and direct experience students are exposed to the art of identification of research gaps and problems which is the fundamental to any research process. Emphasis will be on the following areas: Research Methodology in management and social science; Problems of Research in developing countries; Common errors in Research; Research in Practice: Problem identification, Literature review, Materials and Methods, Results (Data Analysis), Discussion, Summary, Conclusions and Recommendations, Research writing style that is related to the management and social sciences.
Introduction to advanced microeconomic theory: consumer behaviour; theory of production under certainty and uncertainty; welfare economics, general equilibrium models.
Macroeconomics of investment decision; Introduction to advanced macroeconomic theory: macroeconomic statics; comparative statics and dynamics; growth theory; macro dynamic disequilibrium models; business cycles and stabilization theories.
In this introduction to Econometrics, topics to be covered include: the study of the specification of econometric models in economics, banking and finance theory, stochastic disturbances, and the link between conceptual variables and observable economic data were combined. Other topics include estimation of single equation linear; non-linear models by ordinary least squares (OLS) and other methods and estimation of time-series models and simultaneous equation models. Particular attention is given to specifications of problems and errors, and the application of the various tools to aid analysis in finance.
This is a research write up that will be carried out by the student and is meant to address a problem identified at the internship position.
The course contents includes: empirical properties of market prices (fat tails, volatility clusters) and forecasting of prices; Introduction to Inference: statistical models; estimators; confidence intervals; Exploratory data analysis; Likelihood inference: asymptotic results; calculating confidence intervals; likelihood ratio statistic; concepts of financial risk (volatility, Value-at-Risk; univariate and multivariate volatility models (ARCH, GARCH); implementation and evaluation of risk forecasts; endogenous risk; credit markets and liquidity, introduction of pricing financial securities; introduction to Brownian motion and stochastic calculus; introduction to portfolio theory, the CAPM, factor models and measuring risk and return; Applied research tools; Risk Analysis; introduction to the concepts used in derivatives pricing and present Monte Carlo simulation methods; Financial Stochastic Processes; Foundations of Financial Markets; Spreadsheet Modelling for Quantitative Finance
Introduction to Analytics (business analytics concepts and frameworks; technologies and tools required for descriptive analytics, predictive analytics, and prescriptive analytics; frameworks for putting analytics to work; technologies and tools required for business analytics; the governance, oversight and business value gained from business analytics within organizations; ethical and social implications of business analytics; future directions for business analytics); Linear Regression; Time Series Analysis; Visualization/ Data Issues; Data Mining – Cluster Analysis; Data Mining – Market Basket Analysis; Spreadsheet Models; Linear Optimization; Integer Linear Optimization; Nonlinear Optimization; Monte Carlo Simulation; What is Fin Tech; Financial Innovation: Theory, History, Today Payments, Cryptocurrencies and Block chain; Digital Finance and Alternative Finance; Data & Tech Fin; Privacy and financial data ; The Future of Data-Driven Finance.
This course is concerned with the special statistical characteristics that arise when modelling, they include: Introduction to Econometrics, Data Types, Sources of Economic Data; Introduction STATA software, Descriptive Analysis using STATA; Linear Regression Analysis, Non-linear Regression Models (Polynomial Models, Log Linear Models, Log-log Models); Goodness-of-fit, Detecting outliers, Specification tests, Joint tests, and other modelling issues in Regression Analysis; Models with Binary and Multinomial Dependent Variables; Models with Ordinal and Count Dependent Variables Limited Dependent Variable Models—Tobit Regression; Quantile Regression Analysis—Introduction; Applications of Quantile Regression; Heteroskedasticity—Detection and remedial actions; Generalized Least Squares Regression and Robust Standard Errors; Regression with Stationary Time-Series Data, Finite Distributed Lags, Serial Correlations; Autoregressive Distributed Lag Models and their applications Instrumental Variables, Models with Random Regressions; Modelling Conditional Volatility—ARCH/GARCH models; Applications of ARCH/GARCH models; Nonstationary Variables—Detection and their Impact; Regression Analysis with; Nonstationary Variables, Panel Data Models
Introduction to Corporate Treasury Management – Overview of Corporate Treasury; treasury exposures; the role of the treasury and treasurer – (raising capital, managing bank relationships, money management, managing corporate risks); Treasury organisation and its structure; corporate strategy of treasury; treasury control framework; Treasury performance management. Cash Management: Cash management objectives; Cash flow forecasting; Excess liquidity: short-tern investing; Using longer-dated instruments; Short-term borrowing. Risk Management: Why manage financial risk? Principal treasury related financial risks; The management of financial risks; identification of financial risks; measurement and ranking of treasury risks; Currency Risk Management: Identifying the risks; accounting risks: What they are and why they are important; pricing risks; strategic risks.
Modelling assets return volatility: extensions of the basic ARCH/GARCH class of models, both univariate and multivariate; Evaluating forecasts of risks and returns, the efficient market hypothesis and market predictability; Risk management and Value-at-Risk: models, backtesting; Modelling high frequency financial data
An overview of business ethics; the foundation of ethical thought; emerging business ethical issues; ethical corporate behaviour and its development, ethical leadership; ethical decision-making, ethical dilemmas in organisation, social responsibility of business and corporate fundamental principles; conceptual framework guiding compliance with the fundamental principles; threats and safeguards; corporate governance theories; NSE’s and CBN’s codes of corporate governance; board conflict management, board governance mechanisms. Ethics in functional areas like marketing, finance, human resource, and information technology; environmental ethics, and corruption. Impacts of ethics on the on the current business environment; International codes of ethical standards and organisations such as OECD, World Bank, EU, GRI, etc.
Introduction to enterprise systems; Evolution of enterprise systems; Concept of enterprise resource planning (ERP); Supply chain management; Customer relationship management; Business process management; Enterprise systems implementation life cycle, and use in organizations; Contemporary issues in enterprise systems practice; Architecture of integrated enterprise systems; Implementation tools and methodology of ERP; Enterprise systems integration; Knowledge management; Change management and vendor product selection.
Objective of Financial Statement Analysis (FSA), An Overview of FSA – Components of FSA; Objective of Statement Logic (SL), An Overview of SL; Business Characteristics; Perspectives in FSA and Logical Relationships, Overview of Asset and Financial Structure of a Firm; Overview of Asset Conversion Cycle (ACC); Concept of Working Investment (WI); Overview of Risks – Business and Financial Risks; An Overview of Shrinkage; Perspective in FSA and Logical Relationships; Debt-Servicing Ability; Balance sheet Building and Identification; Financial Structure Identification; Analyzing Operations Management & Profitability; Analyzing Assets Management & Efficiency; Analyzing Liability Management and Cashflow Statement.
Review of fundamental concepts of investment; types and classifications of investment, utility analysis of investment choice: the utility theory; the axiomatic basis of expected utility; risk – uncertainty and return; risk aversion and investment behaviour capital market theory: nature and functions of the capital market; the capital market theory; assumptions underlying the capital market theory; the capital asset pricing model (CAPM); the separation theorem; the arbitrage pricing theory (APT); the capital market in Nigeria, portfolio theory and capital market analysis: portfolio risk and return; selecting the “best portfolio, common stock analysis: stock market efficiency; efficient pricing and security screening; the efficient market hypothesis
Review of fundamental concepts of investment; types and classifications of investment, utility analysis of investment choice: the utility theory; the axiomatic basis of expected utility; risk – uncertainty and return; risk aversion and investment behaviour capital market theory: nature and functions of the capital market; the capital market theory; assumptions underlying the capital market theory; the capital asset pricing model (CAPM); the separation theorem; the arbitrage pricing theory (APT); the capital market in Nigeria, portfolio theory and capital market analysis: portfolio risk and return; selecting the “best portfolio, common stock analysis: stock market efficiency; efficient pricing and security screening; the efficient market hypothesis
The course looks at the economic role of derivatives, valuation of derivatives, derivative trading strategies, and managing risk with derivatives. Topics covered include: introduction to derivatives: forwards, futures, swaps and options; Arbitrage, no-arbitrage and hedging; Interest rates and interest rate derivatives; The Black-Scholes formula and assumptions, Model calibration, Implied volatility, Delta-Gamma-Vega hedging, Greeks, Exotic options; Credit and credit derivatives; One-period Binomial model for option pricing; Multi-period models, Pricing via martingales, Binomial martingale representation theorem, Discrete time changes of measure; Trinomial models, Complete markets, Convergence of the binomial to the Black-Scholes model; Application of Ito’s formula, the Brownian martingale representation theorem and Girsanov’s theorem to derive the Black-Scholes formula; Commodities and Energy derivatives.
Course content focuses on the environment in which the international financial manager operates. Students will study the risks of doing business overseas and the tools available to minimize those risks. Foreign exchange risks, political risk, working capital management, long-term investments and financing, and accounting and control are examined within this context.
This course focused on the basic principles of lending and credit administration in credit organizations, the lending environment and credit analysis. Topics covered include: Reconciliation of liquidity, profitability and solvency; Lending policies, concepts, principles and practices; Credit culture, credit standards; Credit terms and conditions; Communication of approvals; Monitoring and advances control; major sources of Frauds in lending and their mitigations; Credit risk management; Loan pricing and syndication; Feasibility study analysis and project financing; Debt recovery strategies; Definition and identification of problem loans; Early warning signals.
This course is designed to provide an advanced level of introduction to the topics in decision analysis and performance improvement. It consistent of two main parts: risk analysis (RS) and decision analysis (DS) under uncertainty, multiple criteria decision analysis (MCDA), data envelopment analysis (DEA) and multiple objective linear programming (MOLP). The emphasis of the course is on how data and human judgement s can be combined to support decision and performance analysis in a robust way and what models, methods, algorithms, and software systems can be used in the process to improve the quality of the analysis.
The course covers the nature, characteristics and consequences of financial services, and the need for products to be marketed in a special way. The course enables students to skilfully apply marketing concepts, functions, strategies, and techniques for efficient provision of banking financial services. It also requires background knowledge of banking theory and practice for efficient application of marketing principles to enhance financial services delivery at profit.
The course is expected to provide detailed and comprehensive analysis in major areas of Islamic Banking and Finance. Relevant theory would be covered to indicate development, practical application and use of all products in the global Islamic finance markets:
This course provides a broad introduction to the regulation and management of financial institutions in Nigeria and beyond, covering a range of banking and non-banking firms. It covers areas such as: History of the Banking industry in Nigeria and beyond; the evolution of the various regulatory agencies; Rationale for regulation of financial institutions; Goals of regulation; Different approaches to regulation; the Four Pillar Theory; Restrictions imposed upon banks and other financial institutions; the rise of Shadow Banking System; Consumer protection
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