Humboldt-Universität zu Berlin - High Dimensional Nonstationary Time Series

Xinwen Ni, Ph.D.

Contact

  •   E-mail xinwen.ni.1@hu-berlin.de
  •   Phone / Fax
      +49 30 2093-99404
  •   Office / Office hours:
      Dor1, 003 / upon agreement

 

 

Mail address

IRTG 1972

Humboldt-Universität zu Berlin
School of Business and Economics
Dorotheenstr. 1
10117 Berlin
Germany


 

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Education

2012- 2014              M. Sc.  Applied Economics

                               Nanyang Technological University


2014- 2018              Ph.D in Economics (Macro)

                               Nanyang Technological University                               


2018- present           Ph.D in Economics (Statistics)

                               Humboldt University Berlin    

Research Interests

Topic Modeling (LDA and DTM)

Cryptocurrenies

Ragulatory Policy Uncertainty


 

 

Publications and Working Paper

Zhang, Linyun, et al. "Testing how financial development led to energy efficiency? Environmental consideration as a mediating concern." Environmental Science and Pollution Research (2021): 1-12.

 

W. K. Härdle, S. Nasekin, D. K. C. Lee , X. Ni and A. Petukhina Tail Event Driven ASset allocation: evidence from equity and mutual funds markets, CRC 649 Discussion Paper 2015-045

 

Ni XW, Härdle WK, Xie TJ, (2020) A Machine Learning Based Regulatory Risk Index for Cryptocurrencies. Journal of Banking and Finance (JBF), submitted 20200809

Work in Progress

  • Sentiment Measurement with Emojis
  • Regulatory policy uncertainty in cryptocurrency market

 

Scientific Talks

2019

  • Advances in Econometrics Conference, The National Bank of Romania, ULBS, Sibiu, Romania 

  • Singapore Economic Review Conference, NTU, Singapore

  • First Yushan Conference, NCTU, Hsinchu, Taiwan (scheduled)

2020

  • Haindorf Seminar 2020, HU Berlin, Czech Republic
  • Statistics of Machine Learning, Charles University, Prague, Czech Republic

2021

  • Victoria Peak Conference, HKUST, Hong Kong (online)

Teaching

  • Statistics of Financial Markets  (WS 21/22)
  • Statistics of Financial Markets I (WS 19/20)
  • Statistics of Financial Markets II (SoSe 2018)