Cryptocurrency price drivers: Wavelet coherence analysis revisited

Cryptocurrencies have experienced recent surges in interest and price. It has been discovered that there are time intervals where cryptocurrency prices and certain online and social media factors appear related. In addition it has been noted that cryptocurrencies are prone to experience intervals of...

Full description

Saved in:
Bibliographic Details
Published in:PloS one 2018-04, Vol.13 (4), p.e0195200-e0195200
Main Authors: Phillips, Ross C, Gorse, Denise
Format: Article
Language:English
Subjects:
Analysis
Coherence analysis
Computer and Information Sciences
Computer science
Cryptocurrencies
Data collection
Digital currencies
Digital media
Energy economics
Hypotheses
Internet
Intervals
Markets
Normal distribution
Physical Sciences
Prices
Research and Analysis Methods
Security
Social media
Social networks
Social Sciences
Society
Stock exchanges
Surges
Wavelet analysis
Wavelet transforms
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Cryptocurrencies have experienced recent surges in interest and price. It has been discovered that there are time intervals where cryptocurrency prices and certain online and social media factors appear related. In addition it has been noted that cryptocurrencies are prone to experience intervals of bubble-like price growth. The hypothesis investigated here is that relationships between online factors and price are dependent on market regime. In this paper, wavelet coherence is used to study co-movement between a cryptocurrency price and its related factors, for a number of examples. This is used alongside a well-known test for financial asset bubbles to explore whether relationships change dependent on regime. The primary finding of this work is that medium-term positive correlations between online factors and price strengthen significantly during bubble-like regimes of the price series; this explains why these relationships have previously been seen to appear and disappear over time. A secondary finding is that short-term relationships between the chosen factors and price appear to be caused by particular market events (such as hacks / security breaches), and are not consistent from one time interval to another in the effect of the factor upon the price. In addition, for the first time, wavelet coherence is used to explore the relationships between different cryptocurrencies.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0195200