Courses Exchange Display 2018-2019
|Course Description||To PDF|
|Course title||Quantitative Techniques for Financial Economics|
Michael Eichler, Nalan Bastürk
For more information: firstname.lastname@example.org; email@example.com
|Language of instruction||English|
The objectives of the course are to provide student in the Financial Economics master programme with a solid knowledge of stochastic models and econometric techniques used in the analysis of financial markets. The students should be able to read and assess the current literature on stochastic models and econometric methods used in security pricing and empirical finance and to apply the acquired techniques in practice.
The course consists of two parts. In the first part, we cover and discuss the theoretical concepts and probability models underlying the pricing, construction, and hedging of (derivative) securities. Key concepts such as arbitrage pricing and risk-neutral valuation are introduced in a formal way and their implementation and use by market practitioners will be discussed. The second part focuses on advanced econometric techniques for modelling financial time series. Topics that are covered include volatility models. Empirical applications will provide students with practical experience in analysing financial time series.
Will be provided.
Solid background in finance and in statistics/econometrics (on the level of a quantitatively oriented economics/finance bachelor). Required concepts from mathematics/statistics are a.o. random variables, probability distributions, statistical tests, regression analysis, ordinary and partil derivatives, exponential function; some basic knowledge in programming (e.g. in VBA, MATLAB, R. OX) will be helpful.
An advanced level of English.
|Teaching methods||PBL / Presentation / Lecture / Assignment|
|Assessment methods||Participation / Written Exam|
|Evaluation in previous academic year||For the complete evaluation of this course please click "here"|
|This course belongs to the following programmes / specialisations||