Former Employees

M.Sc. Arne Vogler

former Academic Staff

M.Sc. Arne Vogler

Email:

Curriculum Vitae:

since 04/2016

University of Duisburg-Essen

Academic Staff at the Chair for Management Science and Energy Economics
10/2014 - 03/2016

Goethe University Frankfurt

GSEFM Ph.D. programs in Economics
08/2013 - 09/2014

European Commodity Clearing AG

Clearing Initiatives & Cooperations Business Analyst
08/2011 - 07/2013

European Energy Exchange AG

Trainee
2010 - 2011

University of Nottingham

Studies of Economics (M.Sc.)
2007 - 2010

University of Nottingham

Studies of Economics (B.Sc.)

Projects:

StoOpt.NRW

Publications:

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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. CitationDetails
  • 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. Full textCitationDetails
  • Beran, P.; Vogler, A.; Weber, C.: Kurz- und mittelfristige Preisprognosen: Auswahl optimaler Modellierungsansätze unter Berücksichtigung des Prognosehorizonts, VDI-Berichte, 2303. GmbH, Vdi Wissensforum (Ed.), Würzburg 2017. CitationDetails
  • 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. Full textCitationDetails

    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.

Tutored Theses:

  • Kurz- und mittelfristige Strompreisprognose über variierende Prognosehorizonte mit einem hybriden Modellierungsansatz (Master Thesis Business Administration - Energy and Finance, 2018)