Can uncertainty indices predict Bitcoin prices? A revisited analysis using partial and multivariate wavelet approaches

Khamis Hamed Al-Yahyaee, Mobeen Ur Rehman, Walid Mensi*, Idries Mohammad Wanas Al-Jarrah

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

87 Citations (Scopus)

Abstract

This paper uses bivariate and multivariate wavelet approaches to revisit the co-movements between the Volatility Uncertainty Index (VIX) and Bitcoin (BTC). This is achieved by accounting for the impacts of the three major global factors, namely the U.S. Economic Policy Uncertainty Index (EPU), the Crude Oil Volatility Index (OVX), and the Geopolitical Risk Index (GPR). To do this, we use Wavelet Coherence (WC), Cross Wavelet Transform (CWT), Power Wavelet Coherence (PWC), and Multiple Wavelet Coherence (MWC) approaches. The results show that the BTC-VIX relationship varies across time and at high and low frequencies. Moreover, we find positive (or in-phase) co-movements between both variables while a negative co-movement (out-of-phase) is observed at both high and low frequencies. VIX news has a prediction power on BTC price returns over different frequencies. The results of PWC and MWC show that OVX, EPU, and GPR factors affect the BTC-VIX nexus under different frequencies. Finally, correlations between BTC-uncertainty indices are dependent upon investment horizons. The results of our research are of interest and importance to investors, portfolio managers, and policy-makers, as the results have practical applications to inform their decision-making.

Original languageEnglish
Pages (from-to)47-56
Number of pages10
JournalNorth American Journal of Economics and Finance
Volume49
DOIs
Publication statusPublished - Jul 2019

Keywords

  • Bitcoin
  • Bivariate and multivariate wavelet approaches
  • Uncertainty indices

ASJC Scopus subject areas

  • Finance
  • Economics and Econometrics

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