| CODE | BFI5333 | ||||||||||||
| TITLE | Financial Econometrics | ||||||||||||
| UM LEVEL | 05 - Postgraduate Modular Diploma or Degree Course | ||||||||||||
| MQF LEVEL | 7 | ||||||||||||
| ECTS CREDITS | 5 | ||||||||||||
| DEPARTMENT | Banking, Finance and Investments | ||||||||||||
| DESCRIPTION | This study-unit builds on undergraduate knowledge in financial econometrics and provides students with an advanced overview of the theory, tools, and terminology related to financialeconometrics. This study-unit offers an advanced understanding of topics such as probability and statistics theory, differential calculus applied to finance, data types, the classical linear regression model, OLS assumptions, estimation, sampling, estimator properties of the OLS estimators, precision and standard errors, statistical inference and hypothesis testing, violations of CLRM, heteroscedasticity, nonnormality and autocorrelation, multicollinearity, dummies, parameter stability tests, nonlinear regression, reparameterization, diagnostics, Maximum likelihood, method of moments, Limited dependent variable models etc. The application of techniques is illustrated through the use of Eviews and Excel, both of which students are encouraged to familiarise themselves with. Study-Unit Aims: The aim of this study-unit is to provide an advanced knowledge of Financial Econometrics. The study-unit aims at introducing students with the theory and practice of financial econometrics. The study-unit will also show how these techniques and tools can be used to resolve empirical questions in finance research or as practitioners. Learning Outcomes: 1. Knowledge & Understanding: By the end of the study-unit the student will be able to: - Explain probability and statistics theory and differential calculus applied to finance; - Discuss the scope of Econometrics for Banking and Finance; - List and distinguish data types and corresponding modelling techniques suitable; - Explain the classical linear regression model and OLS assumptions; - Describe estimation, sampling, estimator properties of the OLS estimators, precision and standard errors; - Explain the concepts of statistical inference and hypothesis testing to the CLRM; - Detect and remedy the violations of CLRM; - Explain the concepts of heteroscedasticity, nonnormality, autocorrelation, multicollinearity; - Explain how statistical anomalies are solved with the use of dummies; - Explain nonlinear regression, reparameterization and diagnostics; - Explain estimation methods e.g., Maximum likelihood, method of moments etc. 2. Skills: By the end of the study-unit the student will be able to: - Apply regression analysis in financial applications; - Model, estimate and forecast under the MCLR approach; - Apply econometric techniques and the extent of information they provide out of data samples; - Apply econometrics in the context of finance and banking; - Perform parameter stability tests. Main Text/s and any supplementary readings: Main Texts: - Ch.1-Ch.4 & Appendices 1, 2 &3. Book title: 鈥淚ntroductory Econometrics for Finance鈥�, Chris Brooks [CB], Cambridge University Press, Eds. 2008, ISBN: 978-0-521-69468-1 Additional Notes: - New Slides by Prof. Dr. S. Bekiros |
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| ADDITIONAL NOTES | Pre-requisite Qualifications: B.Com. (Hons.) Banking & Finance, B.Com. Banking & Finance Major or equivalent |
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| STUDY-UNIT TYPE | Lecture | ||||||||||||
| METHOD OF ASSESSMENT |
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| LECTURER/S | Christian Manicaro |
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The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication.
The availability of optional units may be subject to timetabling constraints. Units not attracting a sufficient number of registrations may be withdrawn without notice. It should be noted that all the information in the description above applies to study-units available during the academic year 2025/6. It may be subject to change in subsequent years. |
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