Keyword search (4,163 papers available)

"Lahmiri S" Authored Publications:

Title Authors PubMed ID
1 Energy Measures as Biomarkers of SARS-CoV-2 Variants and Receptors Ghannoum Al Chawaf K; Lahmiri S; 41596038
JMSB
2 A Deep Learning-Based Ensemble System for Brent and WTI Crude Oil Price Analysis and Prediction Zhang Y; Lahmiri S; 41294965
JMSB
3 Distinguishing Between Healthy and Unhealthy Newborns Based on Acoustic Features and Deep Learning Neural Networks Tuned by Bayesian Optimization and Random Search Algorithm Lahmiri S; Tadj C; Gargour C; 41294952
ENCS
4 An Effective and Fast Model for Characterization of Cardiac Arrhythmia and Congestive Heart Failure Lahmiri S; Bekiros S; 40218199
JMSB
5 Fractals in Neuroimaging Lahmiri S; Boukadoum M; Di Ieva A; 38468046
JMSB
6 The effect of COVID-19 pandemic on return-volume and return-volatility relationships in cryptocurrency markets Foroutan P; Lahmiri S; 36068915
CONCORDIA
7 Nonlinear Statistical Analysis of Normal and Pathological Infant Cry Signals in Cepstrum Domain by Multifractal Wavelet Leaders Lahmiri S; Tadj C; Gargour C; 36010830
ENCS
8 Randomness, Informational Entropy, and Volatility Interdependencies among the Major World Markets: The Role of the COVID-19 Pandemic Lahmiri S; Bekiros S; 33286604
JMSB
9 Renyi entropy and mutual information measurement of market expectations and investor fear during the COVID-19 pandemic Lahmiri S; Bekiros S; 32834621
JMSB
10 The impact of COVID-19 pandemic upon stability and sequential irregularity of equity and cryptocurrency markets Lahmiri S; Bekiros S; 32501379
JMSB

 

Title:The effect of COVID-19 pandemic on return-volume and return-volatility relationships in cryptocurrency markets
Authors:Foroutan PLahmiri S
Link:https://pubmed.ncbi.nlm.nih.gov/36068915/
DOI:10.1016/j.chaos.2022.112443
Publication:Chaos, solitons, and fractals
Keywords:COVID-19 pandemicCryptocurrencyEGARCH-MGranger causalityReturn-volatility relationshipReturn-volume relationship
PMID:36068915 Category: Date Added:2022-09-07
Dept Affiliation: CONCORDIA
1 Department of Supply Chain and Business Technology Management, Concordia University, Montreal, Canada.

Description:

Understanding the dynamics of cryptocurrency markets during financial crises such as the recent one caused by the COVID-19 pandemic is crucial for policy makers and investors. In this study, the effect of COVID-19 pandemic on the return-volatility and return-volume relationships for the ten most traded cryptocurrencies, namely Tether, Bitcoin, Ethereum, Ripple, Litecoin, Bitcoin Cash, EOS, Chainlink, Cardano, and Monero is examined. Further, the behavior of cryptocurrencies during COVID-19 pandemic is compared with less volatile markets such as Gold, WTI, and BRENT crude oil markets. To study the effect of volatility on cryptocurrency return, an EGARCH-M model is employed while for the return-volume relationships the VAR model and Granger causality tests are utilized. Results show that the return-volatility relationships for Tether, Ethereum, Ripple, Bitcoin Cash, EOS, and Monero are significant during COVID-19 pandemic, while the same relationship is not significant prior to the pandemic for any of the studied cryptocurrencies. Our findings of the return-volume relationship support the availability of causal relations from return to trading volume changes for Chainlink and Monero in the pre-COVID-19 period and for Ethereum, Ripple, Litecoin, EOS, and Cardano during the COVID-19 period. However, considering the absolute values of returns, we found a significant relationship from cryptocurrencies' absolute returns to trading volume changes for both the prior and during COVID-19 periods. From a managerial perspective, gold can be considered a suitable asset for portfolio hedging during the pandemic period and trading volume can help traders and investors identify the effect of momentum and potential trend in cryptocurrencies on their investments.





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