| CODE | INS5029 | ||||||||||||
| TITLE | Advanced Econometrics for Risk Management | ||||||||||||
| UM LEVEL | 05 - Postgraduate Modular Diploma or Degree Course | ||||||||||||
| MQF LEVEL | 7 | ||||||||||||
| ECTS CREDITS | 5 | ||||||||||||
| DEPARTMENT | Insurance and Risk Management | ||||||||||||
| DESCRIPTION | This study-unit will provide a rigorous treatment of the key econometric tools and techniques used within risk management, particularly in the financial sector. In recent years risk management has become increasingly quantitative in focus, largely due to improvements in both data availability as well as the reliability of statistical and mathematical modelling. This study-unit will present a detailed treatment of the econometric concepts that have become standard within the industry, including cross-sectional, time series and panel data analysis techniques, coupled with several real-world examples and case studies in order to allow students to apply the tools learned in class. The study-unit will also include a number of practical sessions using specialised software like SPSS and Stata in order to further illustrate the concepts covered while also familiarising students with the powerful software tools at their disposal. A select list of topics covered by this module include: - Statistical inference and causality; - Volatility analysis using ARCH, GARCH; - Stationarity and cointegration; - Vector Auto Regression Models; - Fixed Effects and Random Effects Estimators. Study-Unit Aims: - To provide students with a detailed treatment of the most salient econometric tools and techniques used within quantitative risk management; - To develop a critical understanding of the strengths and weaknesses of each tool, and deploy such methods in the analysis of real-world data. Learning Outcomes: 1. Knowledge & Understanding: By the end of the study-unit the student will be able to: - Evaluate and measure risks within the financial services sector and beyond using advanced econometrics techniques; - Assess the various quantitative tools and models that can be used to analyse risk, in order to select the most appropriate tool depending on the scenario at hand; - Design appropriate econometric models in order to analyse real world data, both as part of independent research as well as their careers. 2. Skills: By the end of the study-unit the student will be able to: - Analyse data using advanced quantitative techniques and interpret findings in a meaningful manner; - Critique various determinants of risk using quantitative evidence, both in a written and oral form; - Deploy the concepts learned to undertake their own independent research, as well as to supplement understanding of risk management in their future careers. Main Text/s and any supplementary readings: Main Texts: - Angrist, J. D., & Pischke, J. S., (2008). Mostly harmless econometrics: An empiricist's companion. Princeton university press. |
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| STUDY-UNIT TYPE | Lecture | ||||||||||||
| METHOD OF ASSESSMENT |
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| LECTURER/S | Jonathan Spiteri |
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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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