Wintersemester 2022/2023

• Machine Learning (Exercises)
• Projektstudium: Data Mining

Sommersemester 2022

• Data Mining
• Statistics and Finance with Excel
• Projekt: Data Science, Decision Science and Artificial Intelligence
• Projektstudium: Data Science and Decision Science

• Interpretable Machine Learning
• Machine Learning in Finance

• seit Dezember 2019: Wissenschaftlicher Mitarbeiter, Lehrstuhl für Statistik,
  Wirtschaftswissenschaftliche Fakultät, Universität Augsburg

   

• Oktober 2014 – September 2019:

  Economics (M.Sc.) an der Ruppert-Karls Universität Heidelberg

  Volkswirtschaftslehre (B.Sc.) an der Ludwig-Maximilians Universität München

  Schwerpunkte in den Bereichen Ökonometrie, Monetary Economics und Machine Learning

Pfahler, J.F. Exchange Rate Forecasting with Advanced Machine Learning Methods. J. Risk Financial Manag. 2022, 15, 2. https://doi.org/10.3390/jrfm15010002

Fottner, A., Okhrin Y., Pfahler, J. , Wustl, J., Reddit financial image post sentiment dataset, Data in Brief, Volume 45, 2022, 108759, ISSN 2352-3409, https://doi.org/10.1016/j.dib.2022.108759.

Okhrin, Y.,Wustl, J., Pfahler, J., Predicting Stock Market Returns by any Memes Necessary. Working paper. 2022.

Pfahler, J., Fottner, A., Okhrin, Y., J., Explainable k-Mediods Clustering. Working paper. 2022.

Distler C., Pfahler, J., Relevance-based Clustering for Pattern Recognition in Financial Time Series. Working paper. 2022.