Dissection of Bitcoin's multiscale bubble history from January 2012 to February 2018.

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ID: 101838
2019
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Abstract
We present a detailed bubble analysis of the Bitcoin to US Dollar price dynamics from January 2012 to February 2018. We introduce a robust automatic peak detection method that classifies price time series into periods of uninterrupted market growth (drawups) and regimes of uninterrupted market decrease (drawdowns). In combination with the for detecting the beginning of a new market regime, we identify three major peaks and 10 additional smaller peaks, that have punctuated the dynamics of Bitcoin price during the analysed time period. We explain this classification of long and short bubbles by a number of quantitative metrics and graphs to understand the main socio-economic drivers behind the ascent of Bitcoin over this period. Then, a detailed analysis of the growing risks associated with the three long bubbles using the (LPPLS) model is based on the , defined as the fraction of qualified fits of the LPPLS model over multiple time windows. Furthermore, for various fictitious 'present' times before the crashes, we employ a clustering method to group the predicted critical times of the LPPLS fits over different time scales, where is the most probable time for the ending of the bubble. Each cluster is proposed as a plausible scenario for the subsequent Bitcoin price evolution. We present these predictions for the three long bubbles and the four short bubbles that our time scale of analysis was able to resolve. Overall, our predictive scheme provides useful information to warn of an imminent crash risk.
Reference Key
gerlach2019dissectionroyal Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Gerlach, J C;Demos, G;Sornette, D;
Journal Royal Society open science
Year 2019
DOI
10.1098/rsos.180643
URL
Keywords
bitcoin k-means clustering forecasting log-periodic power-law singularity analysis market crashes multiscale bubble indicator

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