Module ECOS2161: INTRODUCTION TO FINANCIAL ECONOMETRICS

Department: ECONOMICS FINANCE AND BUSINESS (BUSINESS FINANCE) [Queen's Campus, Stockton]

ECOS2161: INTRODUCTION TO FINANCIAL ECONOMETRICS

Prerequisites

• Successful completion of level 1 core modules.

Corequisites

• Successful completion of level 2 core modules.

Excluded Combination of Modules

• None.

Aims

• To develop knowledge and understanding of key issues and concepts in Financial Econometrics.
• To equip students with the skills required in order to undertake an applied financial Econometrics project and to prepare students for Financial Econometrics at higher levels.
• To offer the opportunity to develop key skills.

Content

• Review of Statistics: random variables, probability distributions, hypothesis tests.
• ordinary least squares: bivariate regression, multivariate regression, hypothesis tests.
• The Random Walk and Stock Market Efficiency: unit roots and tests of market efficiency.
• Co-integration: testing for co-integration, using co-integration analysis to model stock market comovement.
• Forecasting and Causality: The Box-Jenkins approach, Granger Causality.
• Stock Market Volatility: autocoregressive conditional heteroscedasticity (ARCH), generalised ARCH (GARCH), using ARCH and GARCH to model stock market volatility.

Learning Outcomes

• To develop knowledge and understanding of key issues and concepts in Financial Econometrics.
• To equip students with the skills required in order to undertake an applied financial Econometrics project and to prepare students for Financial Econometrics at higher levels.
• To offer the opportunity to develop key skills.
• On completion of the module: students should have knowledge and understanding of the key theoretical and practical issues in Financial Econometrics.
• students should be able to apply the key components of Financial Econometrics and an econometrics software package to statistically analyse financial data as part of a Financial Econometrics project, and interpret the results of that analysis.

• Econometric analysis
• Time series analysis
• statistics
• Econometric software packages
• Model specification and calibration

• Written Communication- by completing the summative assignment
• Planning, Organisation and Time Management- e.g. by preparing for examinations
• Problem solving and Analysis- by applying the necessary analytical and quantitative skills to identify and empirically test theoretical relationships
• Initiative- by collecting information for the summative assignment, searching relevant literature and information in preparation for the summative assignment.
• Numeracy- e.g. by applying an array of core mathematical-statistical skills to answer a range of examination questions;
• Computer Literacy and Information Retrieval- by word-processing the summative assignment

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

• Lectures will enable the key theoretical issues to be covered.
• Preparation for and participation in tutorial classes
• Formative assessment is by means of two formative exercises - formative 1: the single variable model, formative 2: the multivariable model and special econometric issues.
• Summative assessment is by means of an unseen written examination of 1 hour and 30 minutes duration, plus a written assignment of 1500 words.

Teaching Methods and Learning Hours

Summative Assessment

Formative Assessment:

Two formative exercises - formative 1: the single variable model, formative 2: the multivariable model and special econometric issues.

■ Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University