A gentle reminder: Should returns be interpreted as log differences? DOI Creative Commons
David Iheke Okorie

International Review of Financial Analysis, Journal Year: 2024, Volume and Issue: 97, P. 103864 - 103864

Published: Dec. 10, 2024

Language: Английский

Interconnections and contagion among cryptocurrencies, DeFi, NFT and traditional financial assets: Some new evidence from tail risk driven network DOI
Xin Liao, Q. Li, Stephen Chan

et al.

Physica A Statistical Mechanics and its Applications, Journal Year: 2024, Volume and Issue: 647, P. 129892 - 129892

Published: June 24, 2024

Language: Английский

Citations

8
The Predictability of High-Frequency Returns in the Cryptocurrency Markets and the Adaptive Market Hypothesis DOI
Jacek Karasiński

Central European Economic Journal, Journal Year: 2025, Volume and Issue: 12(59), P. 34 - 48

Published: Jan. 1, 2025

Abstract The objective of this study was to examine the level and behaviour weak-form efficiency 16 most capitalised cryptocurrencies using intraday data. employed martingale difference hypothesis tests utilising rolling window method. predictability high frequency returns varied over time. For time, were unpredictable. Nevertheless, their appeared decrease along with an increase in frequency. In general, marked by levels unpredictability. However, there some significant differences between least efficient ones. To exploit market inefficiencies, investors should focus on higher frequencies. Higher frequencies also be a concern regulators when it comes ensuring efficiency.

Language: Английский

Citations

0
Interest rate sensitivity of traditional, green, and stable cryptocurrencies: A comparative study across market conditions DOI Creative Commons
Francisco Jareño, María de la O González,

José M. Almansa

et al.

Quantitative Finance and Economics, Journal Year: 2025, Volume and Issue: 9(1), P. 100 - 130

Published: Jan. 1, 2025

Language: Английский

Citations

0
How Bitcoin market trends affect major cryptocurrencies? DOI
Elie Bouri,

Soufiane Benbachir,

Marwane El Alaoui

et al.

Physica A Statistical Mechanics and its Applications, Journal Year: 2025, Volume and Issue: unknown, P. 130587 - 130587

Published: April 1, 2025

Language: Английский

Citations

0
Price Anomalies in Non-Fungible Token Coins DOI
Alex Plastun, Elie Bouri, Ramzi Nekhili

et al.

International Journal of the Economics of Business, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 21

Published: May 7, 2025

Citations

0
Information spillover among cryptocurrency and traditional financial assets: Evidence from complex networks DOI Creative Commons
Xiaoling Yu, Javier Cifuentes‐Faura

Physica A Statistical Mechanics and its Applications, Journal Year: 2024, Volume and Issue: 646, P. 129903 - 129903

Published: June 15, 2024

This study aims to investigate the information spillover among four traditional financial assets (i.e., crude oil, gold, stock, and U.S. dollar) nine main cryptocurrencies Bitcoin, Cardano, Dai, Ripple, Dogecoin, Ethereum, Ethereum Classic, Monero, Tether), by constructing entropy-based network integration from both static dynamic perspectives. The empirical results show that these is time-varying, experiencing an obvious increase trend after COVID-19. As a whole, mainly play role of net transmitter while recipient. Tether Dai are two visual coins can transmit flow assets, gold stock cryptocurrencies. dollar central nodes link together.

Language: Английский

Citations

1
A gentle reminder: Should returns be interpreted as log differences? DOI Creative Commons
David Iheke Okorie

International Review of Financial Analysis, Journal Year: 2024, Volume and Issue: 97, P. 103864 - 103864

Published: Dec. 10, 2024

Language: Английский

Citations

0