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

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 Lagrange Regularization Method 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 Log-Periodic Power-Law Singularity (LPPLS) model is based on the LPPLS Confidence Indicators, defined as the fraction of qualified fits of the LPPLS model over multiple time windows. Furthermore, for various fictitious 'present' times t ₂ before the crashes, we employ a clustering method to group the predicted critical times t _c of the LPPLS fits over different time scales, where t _c 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.

SUBMITTER: Gerlach JC

PROVIDER: S-EPMC6689597 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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

Gerlach J C JC Demos G G Sornette D D

Royal Society open science 20190724 7

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 <i>Lagrange Regularization Method</i> for detecting the beginning of a new market regime, we identify three major peaks and 10 additional smaller peaks, that h ...[more]

PMID: 31417685

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Project description:BACKGROUND:Rubella is a vaccine-preventable contagious disease causing an estimated 100,000 children to be born with congenital rubella syndrome each year globally. Studies documented that 18 rubella outbreaks were occurred each year in Ethiopia. Yeka sub-city woreda 13 public health emergency management office reported two measles suspected cases on 8 February, 2018. We investigated this outbreak to identify its etiology, describe the outbreak and implement control measures. METHODS:We described the outbreak using descriptive epidemiology. The study population was defined as students learning in the school where the outbreak occurred. Suspected rubella case was defined as student with generalized rash whereas confirmed case was suspected case tested positive for rubella IgM. Questionnaires, checklists and students record review were used to collect data. We searched for new cases in classes daily and excluded them from classes. The school environment was assessed and the outbreak was described in person and time. RESULTS:We identified 58 cases (median age: 4.6 years; IQR: 4-5 years) with six of them rubella IgM positive and 52 epidemiologically linked. The outbreak began on 8 February 2018 having multiple intermittent peaks during its course reaching its highest peak at 2 April, 2018 and ended on 20 April, 2018. Index cases were reported from two classes; however, cases were occurred in 13/15(86.67%) of the classes during the entire outbreak. Fifty five percent (32/58) and 45/58(77.59%) of the cases were females and 3-5 years children, respectively. Overall attack rate was 58/531(4.05%). Attack rate was higher in females 32/252 (12.7%) than in males 26/279 (9.32%), and higher 45/275(16.36%) in 3-5 years than those in 5-8 years 13/256(5.08%) children. Case fatality ratio was zero. All cases were vaccinated against measles but unvaccinated against rubella. CONCLUSIONS:Attack rate was higher in females than in males and higher in 3-5 years than 5-8 years children. We recommended establishing rubella surveillance system, conducting sero-prevalence of rubella among child bearing age females and establishing CRS surveillance among young infants to provide evidence-based information for RCV introduction. It was also recommended to develop a national rubella surveillance guideline which aid to exclude rubella cases from schools during outbreak.

Dataset Information

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

Publications

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

Similar Datasets

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