Browsing by Author "Ali, Fahad"

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    Green cryptocurrencies and portfolio diversification in the era of greener paths
    (Elsevier Ltd, 2024-03) Ali, Fahad; Khurram, M. U.; Sensoy, Ahmet; Vo, X. V.
    The shift towards cleaner fuels from hydrocarbons has influenced nearly all market types and asset classes, and cryptocurrencies are no exception. The complex mechanism of blockchain and mining consumes high levels of electricity and surges environmental footprints in electronic waste generation. Existing studies that examine green and sustainable investments are limited to sustainable equities or green bonds; therefore, this study opens up a new research direction by considering green (energy-efficient) cryptocurrencies. First, this study develops a four-step screening process to systematically select cryptocurrencies that are greener than others. A comprehensive set of green and non-green assets and a battery of empirical tests are then employed to examine the diversification benefits of selected green cryptocurrencies against several well-diversified equity portfolios at the global, regional, and country levels. The diversification benefits of green cryptocurrencies are compared with non-green cryptocurrencies using (i) the four-moment modified value at risk and conditional value at risk, (ii) four different portfolio optimization strategies, and (iii) dynamic correlation-based hedge and safe-haven regression analyses. The results show that green cryptocurrencies provide diversification benefits that are at least comparable to, and in some cases, superior to, non-green (energy-intensive) cryptocurrencies. Cardano and Tezos are identified as green cryptocurrencies offering the most diversification benefits to investors, followed by EOS, Steller, and IOTA. This study provides valuable insights to investors and policymakers, specifically those concerned with achieving sustainability and ESG-compliance (environmental-social-governance) goals and seeking green assets to hedge and diversify various traditional investments.
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    Safe havens for Bitcoin and Ethereum: evidence from high-frequency data
    (SpringerOpen, 2025-01-15) Ali, Fahad; Khurram, Muhammad Usman; Şensoy, Ahmet
    Investing in cryptocurrencies is progressively becoming a norm; however, these assets are excessively volatile and often decrease or increase in value instantly. Thus, rational investors holding cryptocurrencies for extended periods firmly search for assets that can diversify their risk, preferably with assets other than cryptocurrencies. In this study, we consider the two most studied cryptocurrencies with the highest capitalization and trading volume/value, namely Bitcoin and Ethereum. Specifically, we examine whether high-performing leading US tech stocks (Facebook, Amazon, Apple, Netflix, Google [FAANG]) can provide any diversification benefits to cryptocurrency investors. To do so, we employ dynamic conditional correlation (DCC), asymmetric DCC, time-varying parameter vector autoregression-based connectedness measures, dynamic correlation-based hedge and safe-haven regression analyses, portfolio optimization and hedging strategies, time- and frequency-based wavelet coherence, and high-frequency 10-min intraday data from January 1, 2018 to January 31, 2023. We find that FAANG stocks can be considered (at least weak) safe havens for Bitcoin and Ethereum during the sample period. Our subperiod analyses reveal that the safe-haven role of FAANG stocks, specifically for Bitcoin, has noticeably increased. While the safe-haven property of Facebook is the most promising, for Netflix it is blurred between a weak-safe-haven and a hedge. Our findings may help investors, policymakers, and academicians to invest in cryptocurrencies, formulate relevant investment guidelines, and extend the literature on cryptocurrencies, respectively.