Cryptocurrencies, Metcalfe's law and LPPL models

Arbeitspapier

In this paper we investigate the statistical properties of cryptocurrencies by using alpha-stable distributions. We also study the benefits of the Metcalfe's law (the value of a network is proportional to the square of the number of connected users of the system) for the evaluation of cryptocurrencies. As the results showed a potential for herding behaviour, we used LPPL models to capture the behaviour of cryptocurrencies exchange rates during an endogenous bubble and to predict the most probable time of the regime switching.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: IRTG 1792 Discussion Paper ; No. 2018-056

Classification and Topics

• Classification: Wirtschaft ; Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes ; Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models ; Model Construction and Estimation ; Forecasting Models; Simulation Methods ; Financial Econometrics ; Demand for Money ; Monetary Systems; Standards; Regimes; Government and the Monetary System; Payment Systems ; Money and Interest Rates: Forecasting and Simulation: Models and Applications ; Money Supply; Credit; Money Multipliers ; Financial Forecasting and Simulation
• Subject: cryptocurrency ; Bitcoin ; CRIX ; Log-Periodic Power Law ; Metcalfe's law ; stable distribution

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Pele, Daniel Traian ; Mazurencu-Marinescu-Pele, Miruna
• Event: Veröffentlichung
• (who): Humboldt-Universität zu Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series"
• (where): Berlin
• (when): 2018

Further information

• Handle: http://hdl.handle.net/10419/230767
• Last update: 10.03.2025, 11:42 AM CET