Quantitative Finance

Learning Outcomes

Knowledge and Understanding

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

• how to demonstrate understanding of the basic theory of financial econometrics;
• how to demonstrate competence in using an econometrics software package (Eviews).
• how to demonstrate understanding of some specific applications of such theory;
• how to apply such understanding to a specific empirical project;

Subject Specific Intellectual and Research Skills

Having successfully completed this module you will be able to:

• demonstrate quantitative skills in evaluating numerical data.

Transferable and Generic Skills

Having successfully completed this module you will be able to:

• demonstrate skills in utilising analysis software.

The module offers a comprehensive introduction to Quantitative Finance. Students will learn various methods to analyse financial data.

Structure of linear models

• Functional forms
• Log linear models
• Quadratic models
• Lags
• Dummy variables

Exploring data

• Descriptive statistics
• Outliers
• Missing data

Regression analysis

• Ordinary least squares (OLS) estimator
• Classical OLS assumption
• Statistical significance
• Specification tests

Testing for violation of assumptions and their implications

• Heteroskedasticity
• Autocorrelation
• Multicollinearity
• Endogeneity

Analysing panel data

• Fixed effects
• Random effects
• Serial correlation

Limited dependent variable models

• Logit and probit
• Interpretation of analysis and marginal effects
• Predictive analysis

Time series modelling

• Deterministic models
• Stationarity and unit roots
• ARIMA
• Co-integration

Teaching and learning methods

Teaching methods include:

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 lecturer will draw upon market developments current at the time of the course.

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 data (stock market data, firm and industry-specific data).

Learning activities include:

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

Resources & Reading list

General Resources

Journal of Finance. Journal

Journal of Financial and Quantitative Analysis. Journal

Journal of Financial Economics. Journal

Textbooks

Greene, W.H. (2000). Econometric Analysis. New York: Prentice Hall International Inc..

Chiang, A.C. (1984). Fundamental Methods of Mathematical Economics. Singapore: McGraw-Hill.

Hayashi, F. (2000). Econometrics. Princeton: Princeton University Press.

Campbell, J.Y., Lo, A.W. & A.C. MacKinlay (1997). The Econometrics of Financial Markets. Princeton: Princeton University Press.

Brooks, C (2014). Introductory Econometrics for Finance.

Assessment strategy

The assessment is aligned with the learning outcomes and objectives. The students will analyse financial data and will develop statistical models in STATA. They will apply the methods and concepts discussed in the lecture to real cases and various datasets. This will include the assessment of financial statements, stock market data, quantitative modelling in STATA and discussing management implications. The module will focus more on the practical aspects of time series modelling and will highlight applications in practice.

Formative

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

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.

Repeat Information

Repeat type: Internal & External