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Energy Economics ; 117, 2023.
Article in English | Scopus | ID: covidwho-2238803


This paper investigates the relationship between oil and airline stock returns under different time frequencies. First, we propose an Autoregressive moving average model with mixed frequency exogenous variable to analyse the different impacts of oil on airline stock returns on daily, weekly, and monthly basis. We consistently find a negative oil-airline stock return nexus on a daily basis, but a positive relationship on a weekly basis. While the former supports the economic-based channel, the latter is in line with the market inertia channel. Our findings help explain mixed results reported in the literature. Further, our time frequency connectedness analysis shows that the economic-based channel dominates the market inertia channel since the connectedness is more pronounced in the short-run compared to the medium- and long-run. Our block connectedness results highlight that business models of airline firms can play a significant role in affecting the connectedness, in which the low-cost airlines are more sensitive to the oil price changes. It is worth noting that there are distinguished drivers of the oil-airline stock return nexus in different time frequencies. The drivers also vary between the Global Financial Crisis and the COVID-19 pandemic. Our results are consistent under a battery of robustness checks and deliver important implications to investors, portfolio managers, and executives of airline firms. © 2022 Elsevier B.V.

International Review of Economics & Finance ; 2023.
Article in English | ScienceDirect | ID: covidwho-2179775


This paper explores the connectedness of dynamic time-frequency between cryptocurrencies and traditional financial assets in China using a weekly dataset from September 4, 2015 to March 4, 2022. We found that cryptocurrencies were the primary contributors to the connectedness system and the primary risk sources for traditional financial assets in China. We also found that cryptocurrencies were the main net transmitters of dynamic spillovers, while China's traditional financial assets are the primary net receivers. In addition, conventional financial assets were more sharply influenced by cryptocurrencies in the short term because the level of spillovers was more significant than in the long term, and spillover fluctuations were intense during the COVID-19 pandemic. These findings provide empirical support for the Chinese State Council's current policy regarding crackdowns on cryptocurrencies.

Journal of International Financial Markets, Institutions and Money ; 77, 2022.
Article in English | Scopus | ID: covidwho-1683199


The cryptocurrency markets are perceived as being dominated by Bitcoin leading the overall system dynamics. Although the previous empirical evidence points towards strong connections among selected cryptocurrencies or, from the other side, weak dependence between Bitcoin and traditional financial assets, a focused study on the dynamics of return and volatility connectedness among a wider range of cryptocurrencies is lacking, and more so, one directed towards the very first actual critical period of the global economy coinciding with relevant crypto-markets. Using data for the 10 most capitalized cryptocurrencies between 1st October 2017 and 5th January 2021, we examine how cryptocurrencies interact and whether they have a clear leader, with a special focus on differences with respect to investment horizons and how the relationship structure evolves in time. We uncover a structural change in the connectedness evolving in 2020 as the market restructures in reaction to the unprecedented monetary injections as a counter to the COVID-19-induced economic standstill. The structural change is shown not only for cryptocurrencies considered separately but also when we jointly examine them with traditional assets. © 2022 Elsevier B.V.