A1 Journal article (refereed), original research

Adaptive market hypothesis: An empirical analysis of time-varying market efficiency of cryptocurrencies

Open Access publication

Publication Details

Authors: Khursheed Ambreen, Naeem Muhammad, Ahmed Sheraz, Mustafa Faisal

Publisher: Cogent OA / Taylor & Francis Group

Publication year: 2020

Language: English

Related journal or series: Cogent Economics and Finance

Volume number: 8

ISSN: 2332-2039

JUFO level of this publication: 1

Digital Object Identifier (DOI): http://dx.doi.org/10.1080/23322039.2020.1719574

Permanent website address: https://www.cogentoa.com/article/10.1080/23322039.2020.1719574

Open Access: Open Access publication


This study examines the adaptive market hypothesis (AMH) in relation to time-varying market efficiency by using three tests, namely Generalized Spectral (GS), Dominguez-Lobato (DL) and the automatic portmanteau test (AP) test on four-digital currencies; Bitcoin, Monaro, Litecoin, and Steller over the sample period of 2014–2018. The study applies Jarque-Bera test, ADF test, Ljung-Box statistics and ARCH-LM test for testing normality of returns, stationarity of series, serial correlation and volatility clustering in returns and squared returns of selected cryptocurrencies. Further, the study adopts an extremely important category of martingale difference hypothesis (MDH), which uses non-linear methods of dependencies for identifying changing linear and non-linear dependence in the price movement of currencies. The results indicate that price movements with linear and nonlinear dependences varies over time. Our tests also reveal that Bitcoin, Monaro and Litecoin have the longest efficiency periods. While Steller shows the longest inefficient market period. In view of varying market conditions, the results indicate that different market periods have significant impact on prices fluctuations of cryptocurrencies. Therefore, our findings suggest implementing the adaptive market hypothesis (AMH) as predicting changes in cryptocurrency prices over time must consider the time-varying market conditions for efficient forecasting.

Research Areas

Last updated on 2021-16-03 at 12:47