Time-Frequency Nexus Between Bitcoin and Developed Stock Markets in the Asia-Pacific

Abstract

This study investigates the connectedness between Bitcoin prices and major stock indices in the Asia-Pacific region from February 2012 to August 2019. Based on the wavelet transform framework, we find evidence of significant unidirectional association from Bitcoin to the selected markets in the short, medium, and long-run in the Asia-Pacific region. Overall, Asia-Pacific equity markets and Bitcoin cryptocurrency are weakly correlated at higher frequencies throughout the sample period, but the dependence of Bitcoin on the equity markets steadily increases at lower frequencies. Further, we construct the wavelet-based Granger causality test at different time scales to provide additional support to our connectedness results. Our findings provide important implications for policymakers, portfolio managers, and investors who are invited to take into account the dynamic linkages between Bitcoin and equity markets.

Oil prices and agricultural commodity markets: Evidence from pre and during COVID-19 outbreak

“…It starts with the novel spillover index developed by Diebold and Yilmaz (2012) that allows for identification of time-varying net directional spillover effects between crude oil and agriculture commodity markets ( Hung, 2020a ). We also select wavelet coherence analysis, which provides dynamic connectedness between crude oil and agriculture commodity prices for different investment horizons ( Dahir et al, 2018 ; Hung, 2020c ).…”

“…We may assess the extent of information spillover across assets under examination at any particular date ( Maghyereh et al, 2016 ; Hung, 2020b ). In constant to the standard time-series frameworks that estimate the time-series in the time domain or frequency domain, the wavelet coherence technique explores the time and frequency elements of the time-series together at the same time ( Tiwari et al, 2020 ; Hung, 2020c ). This technique captures slow and existent interdependence among markets than standard methods that only consider the time domain perspective ( Bouri et al, 2020 ; Al-Yahyaee et al, 2020 ).…”

“…Financial commodity markets are known to have fluctuations not only frequencies but also at different time horizons, especially in the Covid-19 crisis period. Using wavelets allows estimating coherence and connectedness in both short and long run horizons, which is crucial for policymakers and investors that seek for series degree of dependence ( Madaleno and Pinho, 2014 ; Dahir et al, 2018 ; Hung, 2020c ). Besides, we apply the spillover index of Diebold and Yilmaz (2012) to measure the direction of spillovers across crude oil prices and agricultural commodity markets.…”

Co-movements between Bitcoin and other asset classes in India

“…More precisely, we attempt to fill the gap in the literature by examining how information is transmitted between these economic variables through short-, medium-and long-term frequencies at different time scales using wavelet analysis. The wavelet analysis has significant superiority over the conventional time-domain techniques applied in past studies (Bouri et al, 2020;Hung, 2020;Mensi et al, 2020). These techniques expand the entire time series into a time-frequency space where both time and frequency-varying information of the series can be visualized in a highly intuitive way.…”

“…In a similar spirit, given evidence on the role of Bitcoin as an investment asset, the problem of its causal association with other financial assets, including equities, bonds, currencies and commodities, needs to be taken into consideration (Hung, 2020;Ji et al, 2018;Maghyereh and Abdoh, 2020;Corbet et al, 2020). Specifically, remarkable variations between Bitcoin and other financial assets have potential influences on international investors' asset allocation decisions and policymakers in nations that are likely to consider Bitcoin as officially digital currencies.…”