Humboldt-Universität zu Berlin - High Dimensional Nonstationary Time Series

E-mail:

danial.saef [at] hu-berlin.de

+49 30 2093-99599

Office:

Office hours:

Dorotheenstr. 1, room 004
Upon agreement

IRTG 1792
School of Business and Economics
Humboldt-Universität zu Berlin
Unter den Linden 6
10099 Berlin, Germany

PhD student in Statistics, Humboldt-Universität zu Berlin

M. Sc. in Economics, Maastricht University

B. Sc. in Economics, University of Cologne

Peer-reviewed publications

• Regime-Based Implied Stochastic Volatility Model for Crypto Option Pricing (with Yuanrong Wang, Tomaso Aste); Companion Proceedings of the ACM Web Conference 2023

Working Papers

• Data Analytics Driven Controlling: bridging statistical modeling and managerial intuition (with Kainat Khowaja, Sergej Sizov, Wolfgang K. Härdle)  

• Understanding jumps in high frequency digital asset markets (with Odett Nagy, Sergej Sizov, Wolfgang K. Härdle)

• Variational Heteroscedastic Volatility Model (with Zexuan Yin, Paolo Barucca) 

Scientific Talks

2023

• ACM Web Conference 2023, University of Texas at Austin, TX, US.

2022

• 14th Annual SoFiE Conference, University of Cambridge, Cambridge, UK

2021

• COST FinAI Annual Meeting, Bucharest University of Economic Studies, Bucharest, Romania
• “Crypto-Currencies in a Digital economy” (CCC3), Blockchain Research Center of Humboldt University of Berlin, Berlin, Germany

2020

• Second Yushan Conference, NCTU, Hsinchu, Taiwan (postponed until 2021)
• 14th International Conference on Business Excellence, Bucharest University of Economic Studies, Bucharest, Romania
• Stat of ML Conference, Charles University, Prague, Czech Republic

Research Interests

• New methods for nonstationary processes

• Forecasting high dimensional time series

• Econometric models for jumps in asset prices and volatility

• Cryptocurrencies

Download the codes and view live talks:

•    www.quantlet.de

•  www.quantinar.com