Research Associate

vor 3 Wochen

Dresden, Deutschland Technische Universität Dresden Vollzeit

Technische Universität Dresden (TUD), as a University of Excellence, is one of the leading and most
dynamic research institutions in the country. Founded in 1828, today it is a globally oriented,
regionally anchored top university as it focuses on the grand challenges of the 21st century. lt
develops innovative solutions for the world's most pressing issues. In research and academic
programs, the university unites the natural and engineering sciences with the humanities, social
sciences and medicine. This wide range of disciplines is a special feature, facilitating interdisciplinarity
and transfer of science to society. As a modern employer, it offers attractive working conditions to all
employees in teaching, research, technology and administration. The goal is to promote and develop
their individual abilities while empowering everyone to reach their full potential. TUD embodies a
university culture that is characterized by cosmopolitanism, mutual appreciation, thriving innovation
and active participation. For TUD diversity is an essential feature and a quality criterion of an excellent
university. Accordingly, we welcome all applicants who would like to commit themselves, their
achievements and productivity to the success of the whole institution.

At the **"Friedrich List" Faculty of Transport and Traffic Sciences**, **Institute of Transport and**
**Economics**, the **Chair of Econometrics and Statistics, esp. in the Transport Sector** offers a position
as

**Research Associate** (M/F/x)***

starting **as soon as possible**._ _The position comprises 75% of the fulltime weekly hours and is limited
to 3 years. The period of employment is governed by the Fixed Term Research Contracts Act
(Wissenschaftszeitvertragsgesetz-WissZeitVG). The position offers the chance to obtain further
academic qualification (e.g. PhD)._ _

**Tasks**: Research work to fulfill below-listed objectives. Own research activities as well as publications
in international journals are explicitly desired and expected. The following goals are to be advanced
within the framework of a DFG project:
1. Develop estimators of the higher realized moments of daily returns based on the high
- frequency data.

2. Estimate the conditional distribution of the daily returns and forecast it. Based on moment
estimation, to derive an ex-post approximation of the conditional distribution of returns based
on intra-day information.

3. Develop a model to predict future ex-post density approximations. Using the modified CAViaR
model in which the quantile regression takes realized skewness and kurtosis into account, we
aim at a simultaneous estimation of ES and VaR.

**Requirements**: university degree in statistics, econometrics or mathematics; profound knowledge of
modern programming and a suitable language, e.g., Python or R; knowledge of data analysis, ability
to work independently in a goal
- and project-oriented manner. Knowledge in stochastic processes and
financial econometrics is advantageous.

TUD strives to employ more women in academia and research. We therefore expressly encourage
women to apply. The University is a certified family-friendly university and offers a Dual Career
equally qualified, those with disabilities or with equivalent status pursuant to the German Social Code
IX (SGB IX) will receive priority for employment.

date of the university central mail service applies), preferably via the TU Dresden SecureMail Portal

**dresden.de** or to**:TU Dresden, Fakultät Verkehrswissenschaften „Friedrich List“, Institut für**
**Wirtschaft und Verkehr, Professur für Ökonometrie und Statistik, insbesondere im**
**Verkehrswesen, Herrn Prof. Dr. Ostap Okhrin, Helmholtzstr. 10, 01069 Dresden, Germany**.
interviews cannot be reimbursed.

**Reference to data protection**: Your data protection rights, the purpose for which your data will be processed,
- dresden.de/karriere/datenschutzhinweis.

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