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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, Georg and Zhang, Yanfen (2020). On Cointegration and Cryptocurrency Dynamics, Digital Finance (revision requested)

Keilbar, Georg and Wang, Weining (2020). Modelling Systemic Risk using Neural Network Quantile Regression, Empirical Economics (revision requested) 

 

Work in Progress

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

A projection based approach for interactive fixed effects panel data models (with Juan Manuel Rodriguez-Poo, Alexandra Soberon and Weining Wang)

SGD for high dimensional quantile estimation (with Likai Chen and Wei Biao Wu)

 

Scientific Talks

2020

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

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

 

Research Interests

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

 

Teaching