Courses NonDegree Display 2024-2025
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Course title | Empirical Analysis of Financial Markets | |||||||||||||||||||||||||||||||||||||||
Course code | EBC4010 | |||||||||||||||||||||||||||||||||||||||
ECTS credits | 6,5 | |||||||||||||||||||||||||||||||||||||||
Assessment | Whole/Half Grades | |||||||||||||||||||||||||||||||||||||||
Period |
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Level | Advanced | |||||||||||||||||||||||||||||||||||||||
Coordinator |
Peter Schotman For more information: p.schotman@maastrichtuniversity.nl |
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Language of instruction | English | |||||||||||||||||||||||||||||||||||||||
Goals |
The purpose of the course is to provide students with an overview of empirical methods and stylised facts that will enable them to make their own assessment of events on financial markets.
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Description |
In this course we consider in depth the fluctuations of stock prices. The purpose of the course is to provide you with an overview of recent empirical research in asset pricing and portfolio management. How are theoretical models of asset pricing being tested in practice? What are the strengths and weaknesses of various methodologies? What kind of statistical techniques are used?
Statistical methods in empirical asset pricing have evolved into a separate field called financial econometrics. These techniques are specifically designed to answer typical questions in finance. Examples are models of risk that look at how risk is measured, how it evolves over time, and how risks in different stocks are related. It also considers probabilities of crashes, bankruptcies and defaults, and statstical tests for the performance of trading strategies. A more recent development are prediction models that build on insights from machine learning and advances in big data methodologies. These techniques seem to uncover new patterns in stock prices. From an investment perspective it is is important to assess whether such new facts will remain or will be arbtiraged away as sson as large investors start trading to exploit these patterns. In the course we will review and discuss interpretations of new techniques and empirical findings. A second aim of the course is to let you gain some experience in doing empirical research. An important aspect of the course is learning about the characteristics of stock returns by doing a small research project. The research projects are concerned with predictability of stock returns and the profitability of various trading strategies based on (seeming) anomalies. At the end of the course you should be able to make your own assessment about events on financial markets. Are reported superior returns pure chance, statistical illusion, a reward for risk or really an anomaly? |
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Literature |
recent research papers - recent journal articles
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Prerequisites |
This course is in transition for the master Business Research.
See the Master Education and Examination Regulations for more information. The following rule applies to master Business Research students who started the programme prior to academic year 2024-2025. TRANSITIONAL REGULATION (EBC4010): The master Business Research has been discontinued. Courses of the Business Research master’s programme will continue to be offered until and including academic year 2025-2026 with exam opportunities running until and including 2026-2027. PREREQUISITES: Knowledge of basics of asset pricing and portfolio management, and linear regression models. Exchange students need to have obtained a Bachelor degree in economics or business administration, and sufficient quantitative background. Exchange students need to major in finance in their master. An advanced level of English |
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Teaching methods (indicative; course manual is definitive) | Lecture / Assignment / Groupwork / Research | |||||||||||||||||||||||||||||||||||||||
Assessment methods (indicative; course manual is definitive) | Final Paper / Written Exam / Assignment / Presentation | |||||||||||||||||||||||||||||||||||||||
Evaluation in previous academic year | For the complete evaluation of this course please click "here" | |||||||||||||||||||||||||||||||||||||||
This course belongs to the following programmes / specialisations |
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