Research and analysis of multifractal characteristics of cryptocurrency markets

This study presents a multifractal analysis of the Bitcoin price time series over the period of 2015 to 2024. The multifractal fluctuation analysis with detrending (MFDFA) method is widely used to study fractal properties in financial time series. The results of the MFDFA indicate that the multifractal spectrum of the Bitcoin price time series has a positive slope. The multifractal spectrum demonstrated greater volatility at small time intervals and more predictable behavior at large. The Hurst exponent, which is a measure of the long-term memory of the time series, is found to be 0.5191. This implies that the Bitcoin have weak autocorrelation and little tendency to trend. The results of the study provide new insights into the complexity of the Bitcoin market and contribute to the ongoing debate on the market efficiency of cryptocurrencies.

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Publication Details

Journal
Forestry Education and Science Current Challenges and Development Prospects
Published
2024-10-31
DOI
https://doi.org/10.36930/conf150.5.18
Citations
1
Primary Topic
Complex Systems and Time Series Analysis
Type
article
Field-Weighted Citation Impact
1.13
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article

Research and analysis of multifractal characteristics of cryptocurrency markets

M. I. Opryshko
1 citations
Forestry Education and Science Current Challenges and Development Prospects
Complex Systems and Time Series Analysis
1.13
article

Research and analysis of multifractal characteristics of cryptocurrency markets

M. I. Opryshko
article en
1 citations

Abstract

This study presents a multifractal analysis of the Bitcoin price time series over the period of 2015 to 2024. The multifractal fluctuation analysis with detrending (MFDFA) method is widely used to study fractal properties in financial time series. The results of the MFDFA indicate that the multifractal spectrum of the Bitcoin price time series has a positive slope. The multifractal spectrum demonstrated greater volatility at small time intervals and more predictable behavior at large. The Hurst exponent, which is a measure of the long-term memory of the time series, is found to be 0.5191. This implies that the Bitcoin have weak autocorrelation and little tendency to trend. The results of the study provide new insights into the complexity of the Bitcoin market and contribute to the ongoing debate on the market efficiency of cryptocurrencies.

Forestry Education and Science Current Challenges and Development Prospects
Ukrainian National Forestry University (UA)
Openalex Percentile: Top 11%
Complex Systems and Time Series Analysis
1.13
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