Cryptocurrency Returns and Cryptocurrency Uncertainty: A Time-Frequency Analysis

Mand, Abdollah Ah

doi:10.2139/ssrn.3950087

Cited by 4 publications

(11 citation statements)

References 0 publications

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“…Considering the marginal hedging role across an 8–16‐week frequency band, earlier research supports the hedging role of sustainable financial assets, such as Naeem and Karim (2021) who documented a positive association between UCRY policy and green assets where green financial assets act as hedges for bitcoin except for clean energy stocks. It also supports the findings of Ah Mand (2021), showing that the UCRY policy index significantly predicts the cryptocurrency return across short, medium and long‐term horizons. Hence, the hedging role of sustainable financial assets is controversial and contradictory.…”

Section: Resultssupporting

confidence: 88%

“…Hasan, Hassan, et al, 2022;Kamal & Hassan, 2022) underline the adverse and negative green assets where green financial assets act as hedges for bitcoin except for clean energy stocks. It also supports the findings of Ah Mand (2021), showing that the UCRY policy index significantly predicts the cryptocurrency return across short, medium and long-term horizons. Hence, the hedging role of sustainable financial assets is controversial and contradictory.…”

Section: Resultssupporting

confidence: 86%

“…Moreover, Rubbaniy et al (2021) explored the comovement between the top three cryptocurrencies, VCRIX and global COVID‐19 fear index, using the wavelet coherence approach. Ah Mand (2021) studied the comovement between cryptocurrency returns and UCRY uncertainties using the wavelet coherence method and discovered that UCRY uncertainties has strong predictive power to predict cryptocurrency returns across short‐term, medium‐term, and long‐term. However, earlier research is lacking in empirical evidence on the dependence structure of cryptocurrency uncertainties (i.e., UCRY policy, UCRY price, CBDCAI, and CBDCUI) and green financial assets (e.g., green bonds, global clean energy, and world sustainability) considering wavelet‐based frameworks.…”

Section: Related Studiesmentioning

confidence: 99%

“…These models are feasible at capturing time‐varying correlation only. Few studies have investigated the linkage between uncertainty measures and cryptocurrencies (Ah Mand, 2021; Balli et al, 2020; Rubbaniy et al, 2021) considering wavelet coherence framework over time and frequency domain. To the best of our knowledge, no study has examined the comovement and dependence between cryptocurrency uncertainties and green financial assets across multiple investment horizons.…”

Section: Introductionmentioning

confidence: 99%

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Time‐frequency comovement among green financial assets and cryptocurrency uncertainties

Haq

2022

Economic Notes

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The high energy consumption and carbon footprints have raised environmental and sustainable concerns of green investors and policymakers. This study explores comovements between three green and socially responsible financial assets, S&P global clean energy index (GCEI), S&P green bonds index (GB), DJ sustainability world index (DJSWI) and four cryptocurrency uncertainty/attention indices cryptocurrency policy uncertainty index, Central Bank Digital Currencies Uncertainty Index, Central Bank Digital Currencies Attentions Index and Index of Cryptocurrency Environmental Attention using the bivariate wavelet coherence approach.

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Section: Resultssupporting

confidence: 88%

Section: Resultssupporting

confidence: 86%

Section: Related Studiesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Time‐frequency comovement among green financial assets and cryptocurrency uncertainties

Haq

2022

Economic Notes

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“…Notably, building on the work of Baker et al (2016), Lucey et al (2022) develop a new cryptocurrency policy uncertainty (UCRY Policy) index that has been found to strongly predict such crypto outcomes as cryptocurrency volatility/returns (e.g. Ah Mand, 2021;Kara€ omer, 2022) and market co-crashes (e.g. Dai et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Do crypto investors wait and see during policy uncertainty? An examination of the dynamic relationships between policy uncertainty and exchange inflows of Bitcoin

Nguyen

2023

RBF

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PurposeIn this paper, the authors examine the short-term and long-term impact of general economic policy uncertainty (EPU) and crypto-specific policy uncertainty on Bitcoin’s (BTC) exchange inflows – a form of crypto investor behaviors that the authors expect to drive the cryptocurrency volatility.Design/methodology/approachThe authors use an autoregressive distributed lag (ARDL), coupled with the bounds testing approach by Pesaran et al. (2001), to analyze a weekly dataset of BTC’s exchange inflows and relevant policy uncertainty indices.FindingsThe authors observe both short-term and long-term impacts of the crypto-specific policy uncertainty on BTC’s exchange inflows, whereas the general EPU only explains these inflows in a short-term manner. In addition, the authors find exchange inflows of BTC “Granger” cause its price volatility. Furthermore, the authors document a significant and relatively persistent response of BTC volatility to shocks to its exchange inflows.Originality/valueThis study’s findings offer significant contributions to research in policy uncertainty and investor behaviors.

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Economic Policy Uncertainty, Energy and Sustainable Cryptocurrencies: Investigating Dynamic Connectedness during the COVID-19 Pandemic

et al. 2023

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The purpose of the research is to explore the dynamic multiscale linkage between economic policy uncertainty, equity market volatility, energy and sustainable cryptocurrencies during the COVID-19 period. We use a multiscale TVP-VAR model considering level (EPUs and IDEMV) and returns series (cryptocurrencies) from 1 December 2019 to 30 September 2022. The data are then decomposed into six wavelet components, based on the wavelet MODWT method. The TVP-VAR connectedness approach is used to uncover the dynamic connectedness among EPUs, energy and sustainable cryptocurrency returns. Our findings reveal that CNEPU (USEPU) is the strongest (weakest) NET volatility transmitter. IDEMV is the most consistent volatility NET transmitter among all uncertainty indices across the original returns and wavelet scales (D1~D6). Energy cryptocurrencies, i.e., GRID, POW and SNC, are more likely to receive volatility spillovers than sustainable cryptocurrencies during a turbulent period (COVID-19). XLM (XNO) is least (most) affected by volatility spillover in system-wide connectedness, and XLM (ADA and MIOTA) showed a consistent (heterogeneous) non-recipient behavior across the six wavelet (D1~D6) scales and original return series. This study uncovers the dynamic connectedness across multiscale, which will support investors considering different investment horizons (D1~D6).

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Cryptocurrency Returns and Cryptocurrency Uncertainty: A Time-Frequency Analysis

Cited by 4 publications

References 0 publications

Time‐frequency comovement among green financial assets and cryptocurrency uncertainties

Time‐frequency comovement among green financial assets and cryptocurrency uncertainties

Do crypto investors wait and see during policy uncertainty? An examination of the dynamic relationships between policy uncertainty and exchange inflows of Bitcoin

Economic Policy Uncertainty, Energy and Sustainable Cryptocurrencies: Investigating Dynamic Connectedness during the COVID-19 Pandemic

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