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This study aims to analyze the efficient market hypothesis (EMH) of cryptocurrencies on multiple platforms by observing whether there is a discrepancy in the levels of efficiency between different exchanges. Additionally, EMH is tested in a multivariate way: whether the prices of the same cryptocurrencies traded on different exchanges are temporally related to each other. ADF and KPSS tests, whereas the vector autoregression model of order p – VAR(p) – for multivariate system.

Both Bitcoin and Ethereum show efficiency in the weak form on the main platforms in each market alone. However, when estimating a VAR(p) between prices among exchanges, there was evidence of Granger causality between cryptocurrencies in all exchanges, suggesting that EMH is not adequate due to cross information.

It is essential to assess the cryptocurrency market in a multivariate way, not only to favor its maturation process, but also to promote a broad understanding of its inherent risks. Thus, it will be possible to develop financial products that are actively managed in a more sophisticated cryptocurrency market.

There is a possibility of performing arbitrage on different exchanges and market assets through cross-exchanges. Thus, emphasizing the need for regulation of exchanges in the digital asset market, as an eventual price manipulation on a single platform can impact others, which generates various distortions.

This study is the first to find evidence of cross-information for the same (and other) cryptocurrencies among different exchanges.

To meet the rising global needs, the humanitarian community has signed off on making a strategic change toward more localisation, which commonly refers to the empowerment of national and local actors in humanitarian assistance. However, to this date, actual initiatives for localisation are rare. To enhance understanding of the phenomenon, the authors explore localisation of logistics preparedness capacities and obstacles to its implementation. The authors particularly take the perspective of the international humanitarian organisation (IHO) community as they are expected to implement the localisation strategy.

A phenomenon-driven, exploratory and qualitative study was conducted. Data collection included in-depth interviews with 28 experienced humanitarian professionals.

The findings showed the ambiguity inherent in the localisation strategy with largely different views on four important dimensions. Particularly, the interviewees differ about strengthening external actors or internal national/local offices. The resulting framework visualises the gap between strategy formulation and implementation, which forms major obstacles to the localisation aims.

Further research is required to support the advancement of localisation of logistics preparedness capacities. Important aspects for future research include triangulation of results, other stakeholder perspectives and the influence of context.

The authors add to the important debate surrounding localisation by offering remedies to overcoming obstacles to strategy implementation. Further, the authors’ proposed framework offers a language to precisely describe the ways in which IHOs (should) view localisation of logistics preparedness capacities and its operationalisation.

To the best of authors’ knowledge, this paper is the first academic article on localisation within the humanitarian logistics context.

The study considers time-varying risk premium in investigating the capability of technical analysis (TA) to predict and outperform a buy–hold strategy in Bitcoin exchange rate returns.

The study tests the technical trading rule of fixed moving average (FMA) on daily actual and equilibrium returns of Bitcoin exchange rates. The equilibrium returns are computed using dynamic CAPM in conjunction with a VAR-MGARCH (1, 1) system. The empirical evaluation of the study uses a case study of four Bitcoin exchange rates (BTC/AUD, BTC/EUR, BTC/JPY and BTC/ZAR) for the period 19 June 2010 to 30 October 2020.

The findings are consistent with related studies in conventional foreign exchange markets that find TA to be profitable, especially in emerging markets. Nevertheless, the consideration of risk premium has the effect of reducing the abnormal returns. Also, further robust tests reveal that Bitcoin returns possess a momentum effect which prompts further study in efficient market hypothesis research.

The empirical findings of this study should benefit portfolio managers and active investors on the strength of TA to predict returns in a speculative market like the Bitcoin exchange rate market.

The study takes cognisance that cryptocurrency trading is speculative in nature which renders it a good candidate for TA methods. While there are studies that have explored the value of TA in Bitcoin exchange rates, these studies fail to incorporate the effects of time-varying risk premiums, the strength and focus of the current paper.