Comparative analysis of stationarity for Bitcoin and the S&P500

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Hauptverfasser: Tang, Yaoyue, Arias-Calluari, Karina, Harré, Michael S.
Format: Preprint
Veröffentlicht: 2024
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author Tang, Yaoyue
Arias-Calluari, Karina
Harré, Michael S.
author_facet Tang, Yaoyue
Arias-Calluari, Karina
Harré, Michael S.
contents This paper compares and contrasts stationarity between the conventional stock market and cryptocurrency. The dataset used for the analysis is the intraday price indices of the S&P500 from 1996 to 2023 and the intraday Bitcoin indices from 2019 to 2023, both in USD. We adopt the definition of `wide sense stationary', which constrains the time independence of the first and second moments of a time series. The testing method used in this paper follows the Wiener-Khinchin Theorem, i.e., that for a wide sense stationary process, the power spectral density and the autocorrelation are a Fourier transform pair. We demonstrate that localized stationarity can be achieved by truncating the time series into segments, and for each segment, detrending and normalizing the price return are required. These results show that the S&P500 price return can achieve stationarity for the full 28-year period with a detrending window of 12 months and a constrained normalization window of 10 minutes. With truncated segments, a larger normalization window can be used to establish stationarity, indicating that within the segment the data is more homogeneous. For Bitcoin price return, the segment with higher volatility presents stationarity with a normalization window of 60 minutes, whereas stationarity cannot be established in other segments.
format Preprint
id arxiv_https___arxiv_org_abs_2408_02973
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Comparative analysis of stationarity for Bitcoin and the S&P500
Tang, Yaoyue
Arias-Calluari, Karina
Harré, Michael S.
Statistical Finance
Statistical Mechanics
This paper compares and contrasts stationarity between the conventional stock market and cryptocurrency. The dataset used for the analysis is the intraday price indices of the S&P500 from 1996 to 2023 and the intraday Bitcoin indices from 2019 to 2023, both in USD. We adopt the definition of `wide sense stationary', which constrains the time independence of the first and second moments of a time series. The testing method used in this paper follows the Wiener-Khinchin Theorem, i.e., that for a wide sense stationary process, the power spectral density and the autocorrelation are a Fourier transform pair. We demonstrate that localized stationarity can be achieved by truncating the time series into segments, and for each segment, detrending and normalizing the price return are required. These results show that the S&P500 price return can achieve stationarity for the full 28-year period with a detrending window of 12 months and a constrained normalization window of 10 minutes. With truncated segments, a larger normalization window can be used to establish stationarity, indicating that within the segment the data is more homogeneous. For Bitcoin price return, the segment with higher volatility presents stationarity with a normalization window of 60 minutes, whereas stationarity cannot be established in other segments.
title Comparative analysis of stationarity for Bitcoin and the S&P500
topic Statistical Finance
Statistical Mechanics
url https://arxiv.org/abs/2408.02973