Comparative analysis of stationarity for Bitcoin and the S&P500
Yaoyue Tang, Karina Arias-Calluari, Michael S. Harr\'e

TL;DR
This study compares stationarity properties of Bitcoin and S&P 500 intraday returns, showing that stationarity can be achieved through segmentation, detrending, and normalization, with different parameters for each asset class.
Contribution
It introduces a method to analyze and achieve stationarity in financial time series by segmenting data and applying specific detrending and normalization techniques.
Findings
S&P 500 returns are stationary over 28 years with specific detrending and normalization windows.
Bitcoin returns show stationarity only in high-volatility segments with longer normalization windows.
Segmenting data improves stationarity analysis and modeling of financial time series.
Abstract
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…
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Taxonomy
TopicsBlockchain Technology Applications and Security
