M.Sc. Arne Vogler

ehem. Wissenschaftlicher Mitarbeiter

M.Sc. Arne Vogler

E-Mail:

Lebenslauf:

seit
04/2016
Universität Duisburg Essen
Wissenschaftlicher Mitarbeiter am Lehrstuhl für Energiewirtschaft10/2014-
03/2016
Goethe-Universität Frankfurt
GSEFM Ph.D. Programme in Volkswirtschaftslehre08/2013-
09/2014
European Commodity Clearing AG
Clearing Initiatives & Cooperations Business Analyst08/2011-
07/2013
European Energy Exchange AG
Trainee2010-
2011
University of Nottingham
Studium zum Master of Science in Volkswirtschaftslehre2007-
2010
University of Nottingham
Studium zum Bachelor of Science in Volkswirtschaftslehre

Projekte:

StoOpt.NRW

Publikationen:

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  • Vogler, A.; Ziel, F.: On the Evaluation of Binary Event Probability Predictions in Electricity Price Forecasting - Details, 11/2019. Essen 2019. BIB DownloadDetails
  • Beran, P.; Furtwängler, C.; Jahns, C.; Syben, O.; Vogler, A.; Warszawski, M.; Weber, C.: IT-Werkzeuge und -Systeme für die nachhaltige Bewirtschaftung von KWK- und Speichersystemen - Stochastische Optimierung von Multi-Asset-Systemen in NRW (StoOpt.NRW), Aachen, Essen 2019. VolltextBIB DownloadDetails
  • Beran, P.; Vogler, A.; Weber, C.: Kurz- und mittelfristige Preisprognosen: Auswahl optimaler Modellierungsansätze unter Berücksichtigung des Prognosehorizonts, VDI-Berichte, 2303. GmbH, Vdi Wissensforum (Hrsg.), Würzburg 2017. BIB DownloadDetails
  • Pape, C.; Vogler, A.; Woll, O.; Weber, C.: Forecasting the distributions of hourly electricity spot prices - Accounting for serial correlation patterns and non-normality of price distributions, 05/2017. Essen 2017. VolltextBIB DownloadDetails

    We present a stochastic modelling approach to describe the dynamics of hourly electricity prices. The suggested methodology is a stepwise combination of several mathematical operations to adequately characterize the distribution of electricity spot prices. The basic idea is to analyze day-ahead prices as panel of 24 cross-sectional hours and to identify principal components of hourly prices to account for the cross correlation between hours. Moreover, non-normality of residuals is addressed by performing a normal quantile transformation and specifying appropriate stochastic processes for time series before fit. We highlight the importance of adequate distributional forecasts and present a framework to evaluate the distribution forecast accuracy. The application for German electricity prices 2015 reveal that: (i) An autoregressive specification of the stochastic component delivers the best distribution but not always the best point forecasting results. (ii) Only a complete evaluation of point, interval and density forecast, including formal statistical tests, can ensure a correct model choice.

Begleitete Abschlussarbeiten:

  • Kurz- und mittelfristige Strompreisprognose über variierende Prognosehorizonte mit einem hybriden Modellierungsansatz (Masterarbeit BWL - Energy and Finance, 2018)