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DYNAMIC INTERACTION BETWEEN BITCOIN AND DEVELOPED STOCK MARKETS: EVIDENCE FROM THE DCC-GARCH MODEL WITH WAVELET COHERENCE APPROACH
by
Kumar, Neelesh
, Kumar, Mohit
, Dwivedi Yogita
, Singh, Gopal
, Agrawal, Pravin Kumar
, Mishra Pallavi
, Bajpai Mansi
in
Digital currencies
/ Diversification
/ Securities markets
/ Stochastic models
/ Stock exchanges
/ Volatility
2026
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DYNAMIC INTERACTION BETWEEN BITCOIN AND DEVELOPED STOCK MARKETS: EVIDENCE FROM THE DCC-GARCH MODEL WITH WAVELET COHERENCE APPROACH
by
Kumar, Neelesh
, Kumar, Mohit
, Dwivedi Yogita
, Singh, Gopal
, Agrawal, Pravin Kumar
, Mishra Pallavi
, Bajpai Mansi
in
Digital currencies
/ Diversification
/ Securities markets
/ Stochastic models
/ Stock exchanges
/ Volatility
2026
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While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
DYNAMIC INTERACTION BETWEEN BITCOIN AND DEVELOPED STOCK MARKETS: EVIDENCE FROM THE DCC-GARCH MODEL WITH WAVELET COHERENCE APPROACH
by
Kumar, Neelesh
, Kumar, Mohit
, Dwivedi Yogita
, Singh, Gopal
, Agrawal, Pravin Kumar
, Mishra Pallavi
, Bajpai Mansi
in
Digital currencies
/ Diversification
/ Securities markets
/ Stochastic models
/ Stock exchanges
/ Volatility
2026
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DYNAMIC INTERACTION BETWEEN BITCOIN AND DEVELOPED STOCK MARKETS: EVIDENCE FROM THE DCC-GARCH MODEL WITH WAVELET COHERENCE APPROACH
Journal Article
DYNAMIC INTERACTION BETWEEN BITCOIN AND DEVELOPED STOCK MARKETS: EVIDENCE FROM THE DCC-GARCH MODEL WITH WAVELET COHERENCE APPROACH
2026
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Overview
This study examines the volatility spillover and time–frequency connectedness between Bitcoin (BTC) and major developed stock markets, namely Nasdaq (USA), ASX200 (Australia), CAC40 (France), DAX (Germany), Nikkei 225 (Japan), FTSE 100 (UK), TSX (Canada), Hang Seng (Hong Kong), and Straits Times (Singapore), using the DCC-GARCH model and wavelet coherence techniques. Daily data ranging from April 01, 2015, to March 31, 2025, are collected from the Refinitiv database. The DCC-GARCH results indicate limited evidence of short-run volatility spillovers between Bitcoin and several developed stock markets, while statistically significant long-run spillovers emerge for selected market pairs, suggesting horizon-dependent interdependence. In particular, the Bitcoin–Nasdaq and Bitcoin–Nikkei 225 pairs exhibit both short- and long-run volatility transmission, implying stronger information linkages across investment horizons. The wavelet coherence analysis reveals that co-movement between Bitcoin and developed stock markets is time- and scale-dependent. During relatively tranquil periods, coherence remains weak at high frequencies, indicating potential diversification benefits in the short run. However, during periods of financial stress, statistically significant medium- and long-term coherence emerges within regions inside the Cone of Influence, reflecting temporary increases in market integration and reduced diversification potential. Overall, the findings suggest that Bitcoin’s diversification properties are not uniform across time or investment horizons. The results provide conditional insights for investors and policymakers regarding risk management and portfolio allocation, while emphasizing the importance of accounting for time–frequency dynamics and crisis regimes.
Publisher
De Gruyter Brill Sp. z o.o., Paradigm Publishing Services
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