Course Description

The course discusses scientific approach to decision-making and solving business problems. Several techniques are introduced in applying mathematics to solve management problems quantitatively. The course also deals with the application of mathematics to business and economics. The course further looks at the areas with the determination of the most efficient use of limited resources in optimizing objectives, using the graphical method and algebraic methods.

Course Outcomes

At the end of the course, students will:

• Discuss quantitative techniques in decision making
  
• Demonstrate ability to manipulate mathematical expressions and solve mathematical equations
  
• Formulate business, management and economic issues into mathematical problems and solve them using appropriate quantitative techniques
  
• Apply quantitative techniques in decision making.
  
• Apply mathematics to technical problems in business and management.
  
• Appreciate the value of mathematical reasoning and analysis in daily life situations.

Course Content

• Basic Mathematical Techniques
  
• Matrix Algebra
  
• Solving System of Equation using Linear Model
  
• Differential Calculus
  
• Application of Differentiation
  
• Integral Calculus
• Linear Programming

Compulsory Reading Materials

• Barnett, A., Zielgler, R. & Byleen, E. (2000). Applied mathematics for business, economics, life sciences and social sciences, (7^th ed.). New York: Prentice-Hall, Inc.

Optional Reading Materials

• Dowling, E. T. (1992). Introduction to mathematical economics, (2^nded.). Schaum’s Outline series, Ontario: McGraw-Hill Inc.
  
• Hughes-Hallet, D. & Gleason, M. (1996). Applied calculus for business, social sciences and life sciences, New York: John Wiley and Sons, Inc.
  
• Chiang, A. C. (1984). Fundamental methods of mathematical economics. New York: McGraw-Hill Book Co

Course Description

This module focuses on the theory and application of the Classical Linear Regression Model, the violation of its assumptions and its extensions.  The module provides students with the knowledge and skills to design, undertake, and evaluate empirical work within economics, finance and business.

Learning Outcomes

Upon Completion of the programme, students should be able:

• Develop the basic concepts of regression analysis, providing a firm grounding in the theory of Ordinary Least Squares (OLS) and an appreciation of its limitations;
• Provide a theoretical understanding of the causes, consequences and detection of, and remedies for, the violation of the assumptions of the classical linear regression model;
• Illustrate the application of this theory within a range of economic and financial contexts, introducing the art of model building;
• Familiarize students with a standard statistical/econometric software package (e.g. Views).
• Develop students' skills, in particular: applied analysis; critical thinking; problem solving; academic study skills; self assessment and reflection; and quantitative analysis.

Course Content

• Introduction to empirical methods (Econometrics): economic theory versus empirics.
  
• Review of basic statistics: random variables, probability distributions and sampling theory.
  
• Use IT to access sources of relevant economic and financial information, and transform into usable information relevant to the analysis of business economics and finance.
  
• Development of IT quantitative software including development of intermediate knowledge of spreadsheets. Using workbooks.
  
• Organising and managing data including sorting and filters. Solving problems by analysing data. Solving what-if problems.
  
• The Classical Linear Regression Model: specification, estimation, hypothesis-testing and
  
• Functional form and non-linearity: dummy variables and transformation of variables.
  
• Violations of the assumptions of the classical model: autocorrelation, heteroscedasticity, measurement error, multicollinearity and specification errors.
  
• Dynamic models: distributed lag.
  
• Simultaneous-equations models: basic issues, identification and estimation methods.
  
• Introduction to discrete choice models: Using and interpreting the output of dedicated econometric software (e.g. Eviews).

Compulsory Reading Materials

• Gujarati, D.N. and Porter D. 2010. Essentials of Econometrics; 4th edition. McGraw Hill.

Optional Reading Materials

• Gujarati, D.N. and Porter D. 2009. Basic Econometrics; 5th edition. McGraw Hill.
  
• Gujarati, D (2011). Econometrics by Example. Palgrave MacMillan.
  
• Asteriou, D and Hall S G (2011). Applied Econometrics, Palgrave
  
• Macmillan (2nd edition). Dougherty, C. 2010. Introduction to Econometrics, 4th edition, Oxford.
  
• Wooldridge, J. M. 2009. Introduction to Econometrics 4th ed., South Western College Publishing.
  

Course Description

The goal is to broaden, and selectively deepen, students' understanding of finance, building on their existing knowledge of financial economics. The course will cover a broad range of topics, with both a theoretical and an empirical emphasis. These include topics in corporate finance, investments and performance evaluation and international finance. The course consists of two interchangeable ten-week components, one on investments and international finance, and the other on corporate finance.

Learning Outcomes

The course will:

• Provides students with a way of thinking about investment decisions by examining the empirical behaviour of security prices. 
  
• Students will learn about corporate governance mechanisms and discuss some recent corporate scandals.

Course Content

• Empirical evidence of the CAPM and other asset pricing models
  
• Market efficiency focusing on event studies and investment anomalies
  
• Empirical findings in behaviourial finance.
  
• How to measure the performance of a portfolio manager
  
• Foundations of international finance and explores issues related to international portfolio management.
  
• Examine theory and evidence concerning major corporate financial policy decisions. 
  
• Impact of taxes, financial distress, and asymmetric information on such decisions
  
• Optimal managerial compensation

Compulsory Reading Materials

• Bodie, Kane & Marcus, Investments (Irwin) and Grinblatt & Titman, Financial Markets and Corporate Strategy (Irwin, McGraw-Hill).