Cited by Forecasting crude oil volatility and stock volatility: New evidence from the quantile autoregressive model

Does the Introduction of US Spot Bitcoin ETFs Affect Spot Returns and Volatility of Major Cryptocurrencies? DOI

Babalos Vassilios,

Elie Bouri,

Rangan Gupta

et al.

The Quarterly Review of Economics and Finance, Journal Year: 2025, Volume and Issue: unknown, P. 102006 - 102006

Published: April 1, 2025

Language: Английский

Citations

Co-Bubble transmission across clean and dirty Cryptocurrencies: Network and portfolio analysis DOI

Yan Chen, Lei Zhang, Elie Bouri

et al.

Journal of International Money and Finance, Journal Year: 2024, Volume and Issue: 145, P. 103108 - 103108

Published: May 28, 2024

Language: Английский

Citations

Inner Multifractal Dynamics in the Jumps of Cryptocurrency and Forex Markets DOI

Haider Ali,

Muhammad Aftab, Faheem Aslam

et al.

Fractal and Fractional, Journal Year: 2024, Volume and Issue: 8(10), P. 571 - 571

Published: Sept. 29, 2024

Jump dynamics in financial markets exhibit significant complexity, often resulting increased probabilities of subsequent jumps, akin to earthquake aftershocks. This study aims understand these complexities within a multifractal framework. To do this, we employed the high-frequency intraday data from six major cryptocurrencies (Bitcoin, Ethereum, Litecoin, Dashcoin, EOS, and Ripple) forex (Euro, British pound, Canadian dollar, Australian Swiss franc, Japanese yen) between 4 August 2019 October 2023, at 5 min intervals. We began by extracting daily jumps realized volatility using MinRV-based approach then applying Multifractal Detrended Fluctuation Analysis (MFDFA) those explore their characteristics. The results MFDFA—especially fluctuation function, varying Hurst exponent, Renyi exponent—confirm that all jump series properties. However, range exponent values indicates Dashcoin has highest Litecoin lowest strength. Moreover, show persistent behavior positive autocorrelation, indicating higher probability positive/negative being followed another jump. Additionally, findings rolling-window MFDFA with window length 250 days reveal most time. These are useful for market participants, investors, policymakers developing portfolio diversification strategies making important investment decisions, they could enhance efficiency stability.

Language: Английский

Citations

Understanding Investor Sentiment: Analyzing Its Influence on Stock and Cryptocurrency Markets During the Russia–Ukraine War DOI

Emon Kalyan Chowdhury, Rupam Chowdhury, Bablu Kumar Dhar

et al.

Thunderbird International Business Review, Journal Year: 2024, Volume and Issue: 66(5), P. 473 - 489

Published: June 24, 2024

ABSTRACT This paper examines the shifts in investor sentiment during Russia–Ukraine war and its consequent impact on market volatility. By employing a comprehensive dataset that includes S&P 500 index, historical Bitcoin prices, Investor Sentiment Index, Industrial Production US Consumer Price this study applies several econometric models such as generalized autoregressive conditional heteroskedasticity (GARCH) models, regression analyses, vector error correction (VECM), Granger causality model. The analysis spans from January 2021 to March 2023. findings indicate significantly influences returns both stock cryptocurrency markets, having positive effect. These results underscore importance for investors policymakers monitor periods of conflict understand potential financial markets. research offers valuable insights can guide investment decisions inform policy interventions.

Language: Английский

Citations

Forecasting crude oil volatility and stock volatility: New evidence from the quantile autoregressive model DOI

Yan Chen, Lei Zhang, Feipeng Zhang

et al.

The North American Journal of Economics and Finance, Journal Year: 2024, Volume and Issue: 74, P. 102235 - 102235

Published: July 18, 2024

Language: Английский

Citations