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Main Author: Takaishi, Tetsuya
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2511.03314
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author Takaishi, Tetsuya
author_facet Takaishi, Tetsuya
contents The finite sample effect on the Hurst exponent (HE) of realized volatility time series is examined using Bitcoin data. This study finds that the HE decreases as the sampling period $Δ$ increases and a simple finite sample ansatz closely fits the HE data. We obtain values of the HE as $Δ\rightarrow 0$, which are smaller than 1/2, indicating rough volatility. The relative error is found to be $1\%$ for the widely used five-minute realized volatility. Performing a multifractal analysis, we find the multifractality in the realized volatility time series, smaller than that of the price-return time series.
format Preprint
id arxiv_https___arxiv_org_abs_2511_03314
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Multifractality and sample size influence on Bitcoin volatility patterns
Takaishi, Tetsuya
Statistical Finance
The finite sample effect on the Hurst exponent (HE) of realized volatility time series is examined using Bitcoin data. This study finds that the HE decreases as the sampling period $Δ$ increases and a simple finite sample ansatz closely fits the HE data. We obtain values of the HE as $Δ\rightarrow 0$, which are smaller than 1/2, indicating rough volatility. The relative error is found to be $1\%$ for the widely used five-minute realized volatility. Performing a multifractal analysis, we find the multifractality in the realized volatility time series, smaller than that of the price-return time series.
title Multifractality and sample size influence on Bitcoin volatility patterns
topic Statistical Finance
url https://arxiv.org/abs/2511.03314