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Humboldt-Universität zu Berlin - High Dimensional Nonstationary Time Series

Georg Keilbar

Contact

E-mail:

georg.keilbar [at] hu-berlin.de

Phone:

+49 30 2093 99596

Office:

Office hours:

Dorotheenstr. 1, room 0.04

Upon agreement

Postal address:

IRTG 1792 "High Dimensional Nonstationary Time Series"
School of Business and Economics
Humboldt-Universität zu Berlin
Unter den Linden 6
10099 Berlin, Germany

Education

09/2020 - 12/2020 Visiting researcher, University of Chicago, USA (scheduled)
10/2019 - 02/2020 Visiting researcher, Xiamen University, China
2018 - present PhD student in Statistics, Humboldt-Universität zu Berlin  
2018 M.Sc. in Economics, Humboldt-Universität zu Berlin  
   

Working Papers

Keilbar, G. and Wang., W. (2019). Modelling Systemic Risk using Neural Network Quantile Regression, IRTG 1792 Discussion Paper

Keilbar, G. and Zhang, Y. (2020). On Cointegration and Cryptocurrency Dynamics, IRTG 1792 Discussion Paper

 

Work in Progress

Testing for Neglected Nonlinearity in the Conditional Quantile using Neural Networks (with W. Wang)

A projection based approach for interactive fixed effects panel data models (with J.M. Rodriguez-Poo, A. Saberon and W. Wang)

 

Scientific Talks

2019

  • Economic Applications of Quantile Regression 2.0, Nova SBE, Lissabon
  • 12th Annual SoFiE Conference, Fudan University, Shanghai
  • Stat of ML Conference, Charles University, Prague
  • First Yushan Conference, NCTU, Hsinchu, Taiwan

2020

  • Fudan Quantitative Economics and Finance Seminar, Fudan University, Shanghai

 

Research Interests

  • Quantile Regression
  • Non- and Semiparametric Statistics
  • Financial Econometrics
  • Empirical Process Methods

 

Teaching