TY  - JOUR
A1  - Golland, Alexander
T1  - Neuregelungen zum Datenschutz: Ein Update für Website-Betreiber. Reform des Telekommunikations- und Telemedienrechts verabschiedet
JF  - NWB Rechnungswesen - BBK
Y1  - 2021
SN  - 0340-9848
IS  - 14
SP  - 672
EP  - 674
ER  - 
TY  - JOUR
A1  - Golland, Alexander
T1  - Rezension zu: Voigt – Die räumliche Anwendbarkeit der EU Datenschutz-Grundverordnung auf Auftragsverarbeiter im Drittland (2020)
JF  - DSB Datenschutz-Berater
Y1  - 2021
SN  - 0170-7256
VL  - 45
IS  - 2
SP  - 64
PB  - DFV Mediengruppe
CY  - Frankfurt a.M.
ER  - 
TY  - JOUR
A1  - Golland, Alexander
T1  - Bußgelder wegen Datenschutzverstößen – Vermeidung und Verteidigung.
Deutsche Aufsichtsbehörden setzen seit vergangenem Jahr zunehmend auf Sanktion
JF  - NWB Steuer- und Wirtschaftsrecht
Y1  - 2021
SN  - 0028-3460
VL  - 36
SP  - 2678
EP  - 2687
PB  - NWB-Verlag
CY  - Herne
ER  - 
TY  - CHAP
A1  - Schulte, Maximilian
A1  - Eggert, Mathias
T1  - Predicting hourly bitcoin prices based on long short-term memory neural networks
T2  - Proceedings of the International Conference on Wirtschaftsinformatik (WI) 2021
N2  - 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 movements 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 %.
Y1  - 2021
N1  - 16th International Conference on Wirtschaftsinformatik,
March 2021, Essen, Germany
ER  -