|Module / ECTS / Path / Specialisation||Module :Financial markets and financial institutions : 3 ECTS.|
|Open for visitors||yes (3 ECTS)|
|Working language :||English|
|Volume of contact hours :||24 h|
|Workload to be expected by the student :||72 h|
Track : Attendance
|LEARNING GOAL 1 : Students will master state-of-the-art knowledge and tools in management fields in general, as well as in areas specific to the specialized field of management.|
|Students will identify a business organization’s operational and managerial challenges in a complex and evolving environment.|
|Students will understand state-of-the-art management concepts and tools and use them appropriately.|
|Students will implement appropriate methodologies to develop appropriate solutions for business issues.|
|LEARNING GOAL 2 : Students will develop advanced-level managerial skills.|
|Students will participate in a decision-making process in a critical way.|
|Students will communicate ideas effectively, both orally and in writing, in a business context.|
|LEARNING GOAL 4: Students will study and work effectively in a multicultural and international environment.|
|Students will analyze business organizations and problems in a multicultural and international environment|
This cours provides an overview about quantitative methods for the anlysis of investments. It starts with a summary of descriptive and inferential concepts to capture the random behaviour of financial assets. These methods are then applied to Market Risk analysis and Capital Asset Pricing Models. Financial Forecasting is dealt within the framework of Stochastic Volatility models. Techniques are illustrated by hands-on (computer supported) exercises and cases.
- Memorize and master descriptive and inferential concepts to capture the random behaviour of financial assets.
- Use software-supported analysis of financial data
- Apply these methods to Market Risk analysis, Capital Asset Pricing and Options.
- Combine models and perform financial forecasting within the framework of Vector autoregressive and stochastic volatility models.
1. The Time Value of Money
2. Discounted cash flow applications
3. Financial Markets and the No Arbitrage Principle
5. Elements from Statistics
6. Probability and Probability Distributions
7. Statistical Inference
8. Market Risk: Value at Risk (VaR)
9. Credit Risk
10. Regression and Correlation Analysis
11. Capital Asset Pricing Model
12. Forecasting the Markets
13. Applied Time Series Analysis
14. Basics from Continuous Time Finance
15. Elements from stochastic calculus
16. Option Pricing: The Binomial Model
17. The Black-Scholes Model
18. Fixed income models
19. Monte Carlo Simulation
20. Quantitative Portfolio Management
1. Quantitative Methods for Investment Analysis. R.A. Defusco, D.W. McLeavey, J.E. Pinto, D.E. Runkle; Chartered Financial Analyst (CFA) Institute 2004
2. Quantitative Finance. Paul Wilmott, Wiley 2004
Schipp, B. and R. Herrera (2013). Value at risk forecasts by extreme value models in a conditional duration framework. Journal of Empirical Finance 23, p. 33-47.
Schipp, B. and R. Herrera (2014). Statistics of extreme events in risk management: The impact of the subprime and global financial crisis on the German stock market. The North American Journal of Economics and Finance, 2014, vol. 29, issue C, pages 218-238.
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