@article{Knueppel2002,
  author    = {Kn{\"u}ppel, Mark},
  title     = {Pro-Forma-Angaben},
  series = {Handbuch der Bilanzierung : das gesamte Wissen zur Rechnungslegung nach HGB, EStG und IFRS / Federmann, Rudolf ; Gnam, Arnulf ; Ammedick, Oliver},
  journal   = {Handbuch der Bilanzierung : das gesamte Wissen zur Rechnungslegung nach HGB, EStG und IFRS / Federmann, Rudolf ; Gnam, Arnulf ; Ammedick, Oliver},
  publisher = {Haufe},
  address   = {Freiburg},
  pages     = {1950 -- 1952},
  year      = {2002},
  language  = {de}
}
@article{Rick1996,
  author    = {Rick, Heino},
  title     = {Privatnutzung von Firmenfahrzeugen},
  series = {DN-Woche (1996)},
  journal   = {DN-Woche (1996)},
  year      = {1996},
  language  = {de}
}
@article{GlaserSchmitz2007,
  author    = {Glaser, Markus and Schmitz, Philipp},
  title     = {Privatanleger am Optionsscheinmarkt},
  series = {Zeitschrift f{\"u}r Bankrecht und Bankwirtschaft : ZBB},
  volume    = {Jg. 19},
  journal   = {Zeitschrift f{\"u}r Bankrecht und Bankwirtschaft : ZBB},
  number    = {H. 3},
  issn      = {0936-2800},
  pages     = {214 -- 230},
  year      = {2007},
  language  = {de}
}
@article{GlaserSchmitz2006,
  author    = {Glaser, Markus and Schmitz, Philipp},
  title     = {Privatanleger am Optionsscheinmarkt},
  pages     = {1 -- 46},
  year      = {2006},
  language  = {de}
}
@inproceedings{HerzwurmKramsPietsch2010,
  author    = {Herzwurm, Georg and Krams, Benedikt and Pietsch, Wolfram},
  title     = {Preisfindung von IT-Produkten durch retrograde Kalkulation},
  series = {Multikonferenz Wirtschaftsinformatik : MKWI 2010, G{\"o}ttingen, 23.-25.2.2010},
  booktitle = {Multikonferenz Wirtschaftsinformatik : MKWI 2010, G{\"o}ttingen, 23.-25.2.2010},
  edition   = {Online-Ausg.},
  organization    = {Multikonferenz Wirtschaftsinformatik <2010, G{\"o}ttingen>},
  pages     = {529 -- 539},
  year      = {2010},
  language  = {de}
}
@techreport{ViethEschweiler2003,
  type      = {Working Paper},
  author    = {Vieth, Matthias and Eschweiler, Maurice},
  title     = {Preisdeterminanten bei Spielertransfers in der Fußball-Bundesliga - Eine theoretische und empirische Analyse},
  series = {Betriebswirtschaftliches Institut f{\"u}r Anlagen und Systemtechnologien / Arbeitspapiere},
  journal   = {Betriebswirtschaftliches Institut f{\"u}r Anlagen und Systemtechnologien / Arbeitspapiere},
  number    = {32},
  publisher = {IAS},
  address   = {M{\"u}nster},
  organization    = {Betriebswirtschaftliches Institut f{\"u}r Anlagen und Systemtechnologien},
  pages     = {VI, 40 Seiten},
  year      = {2003},
  language  = {de}
}
@article{ViethEschweiler2004,
  author    = {Vieth, Matthias and Eschweiler, M.},
  title     = {Preisdeterminanten bei Spielertransfers in der Fussball-Bundesliga - eine empirische Analyse},
  series = {Die Betriebswirtschaft},
  volume    = {64},
  journal   = {Die Betriebswirtschaft},
  number    = {6},
  issn      = {0342-7064},
  pages     = {671 -- 692},
  year      = {2004},
  language  = {de}
}
@inproceedings{SchulteEggert2021,
  author    = {Schulte, Maximilian and Eggert, Mathias},
  title     = {Predicting hourly bitcoin prices based on long short-term memory neural networks},
  series = {Proceedings of the International Conference on Wirtschaftsinformatik (WI) 2021},
  booktitle = {Proceedings of the International Conference on Wirtschaftsinformatik (WI) 2021},
  pages     = {16 Seiten},
  year      = {2021},
  abstract  = {Bitcoin is a cryptocurrency and is considered a high-risk asset class whose price changes are difficult to predict. Current research focusses on daily price movements with a limited number of predictors. The paper at hand aims at identifying measurable indicators for Bitcoin price movement s and the development of a suitable forecasting model for hourly changes. The paper provides three research contributions. First, a set of significant indicators for predicting the Bitcoin price is identified. Second, the results of a trained Long Short-term Memory (LSTM) neural network that predicts price changes on an hourly basis is presented and compared with other algorithms. Third, the results foster discussions of the applicability of neural nets for stock price predictions. In total, 47 input features for a period of over 10 months could be retrieved to train a neural net that predicts the Bitcoin price movements with an error rate of 3.52 \%.},
  language  = {en}
}
@book{BirleKleinMueller2014,
  author    = {Birle, J{\"u}rgen P. and Klein, Hartmut and M{\"u}ller, Thomas},
  title     = {Praxishandbuch der GmbH : Gesellschafts- und Steuerrecht},
  edition   = {3. Aufl.},
  publisher = {NWB-Verl.},
  address   = {Herne},
  isbn      = {978-3-482-56963-0},
  pages     = {1105 S.},
  year      = {2014},
  language  = {de}
}
@techreport{Vieth2004,
  type      = {Working Paper},
  author    = {Vieth, Matthias},
  title     = {Positionierung von Business Schools in Deutschland mit Co-plot},
  series = {Betriebswirtschaftliches Institut f{\"u}r Anlagen und Systemtechnologien / Arbeitspapiere},
  journal   = {Betriebswirtschaftliches Institut f{\"u}r Anlagen und Systemtechnologien / Arbeitspapiere},
  publisher = {IAS},
  address   = {M{\"u}nster},
  organization    = {Betriebswirtschaftliches Institut f{\"u}r Anlagen und Systemtechnologien},
  pages     = {VIII, 78 Seiten},
  year      = {2004},
  language  = {de}
}