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Courses on Probability Theory

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1.
Module Name: Introductory Econometrics
Code: P12205
Credits: 10
Semester: Spring 2011/12
Delivery: 16 one-hour lectures + 4 one-hour workshops
Aims:
The main aims of this module are: to introduce students to the principles, uses and interpretation of regression analysis most commonly employed in applied economics; to provide participants with sufficient knowledge of regression methods to critically evaluate and interpret empirical research.
On completion of this module students should be able to: demonstrate understanding of the assumptions and properties underlying regression analysis and the principle of ‘least squares’; interpret and manipulate the coefficients of multiple regression and performance criteria; conduct diagnostic checking of the validity of regression equations coefficients; appreciate the problems of misspecification, multicollinearity, heteroscedasticity and autocorrelation.
Content:
1. Simple Regression Analysis 2. Multiple Regression Analysis 3. Dummy Variables 4. Heteroscedasticity 5. Autocorrelation
Main Textbook: Dougherty, C. (2011). Introduction to Econometrics, 4th edition, Oxford.

2.
Module Name: Computational Finance
Code: P12614
Credits: 10
Semester: Spring 2011/12
Programme classes: 12 1-2 hour lectures/workshops
Aims:
The module aims to describe and analyse the general finance topics and introduces students to implement basic computational approaches to financial problems using Microsoft Excel. It stresses the fundamentals of finance; provides students with a knowledge and understanding on the key finance subjects such as money market, return metric, portfolio modelling, asset pricing, etc.; and equips students with the essential techniques applied in financial calculations.
Contents:
1. Lecture Topic 1: Money Market Instrument : Introduction to the course; Interest rate types;

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