Quantitative Research in Finance

Learning Outcomes

Knowledge and Understanding

Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:

• demonstrate a critical understanding of the basic theory of financial econometrics;
• apply such understanding to a specific empirical project;
• have a good understanding of the characteristics of financial data and interpret them within existing economic and/or financial theories;
• demonstrate a critical understanding of some specific applications of such theory;

Transferable and Generic Skills

Having successfully completed this module you will be able to:

• demonstrate skills in utilising analysis software.
• apply knowledge learned in the class to particular problems.

Subject Specific Intellectual and Research Skills

Having successfully completed this module you will be able to:

• apply your understanding on the theory of financial econometrics to a specific empirical project
• demonstrate quantitative skills in evaluating numerical data.

The module offers both fundamental and comprehensive introduction to Quantitative Research in Finance. Students will learn various (fundamental and advanced) methods to analyse financial data.

Topics covered in this module will include.

Part 1: Introduction to the Theory of Econometrics

• Introduction to simple and multiple regression
• Hypothesis testing and the use of diagnostic statistics
• ARCH and GARCH models
• Introduction to Eviews/ Applications of taught subjects using EVIEWS

Part 2: Applications

• Reflections of models on volatility
• Prices, Dividends and Returns
• Volatility Clustering and Volatility Forecasting

Weekly lectures will provide an overview of the main issues arising in the unit, and will be supplemented by weekly empirical and theoretical exercises. Exercises will support student learning by providing opportunities for students to attempt, and gain feedback on, numerical and problem-solving exercises. Students will also have the opportunity for both directed and non-directed independent reading

The module will be taught by a mixture of methods ranging from guided background reading, lectures, group work and the exploration of mini case studies and datasets. The practical (“Lab”) session actively introduces students to the use of econometrics software in performing “Real World” analyses of financial data.

The lecturer will introduce the concepts, and participants will have the opportunity to practice and apply the methods discussed. We will do a step-by-step analysis of different financial (and wherever required economic) data

Learning activities include:

• Eviews based exercises in class
• A group work
• Discussion of findings in class

Formative

This is how we’ll give you feedback as you are learning. It is not a formal test or exam.

Computer practicals

• Assessment Type: Formative
• Feedback: Students will get feedback in terms of their success in completing the computer labs following each lecture. Their ability to complete the set tasks will provide feedback on their progress and flag any issues.
• Final Assessment: No
• Group Work: No

Summative

This is how we’ll formally assess what you have learned in this module.

Referral

This is how we’ll assess you if you don’t meet the criteria to pass this module.

Repeat

An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.