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A Systematic and Bibliometric Analysis of Risk and Return Management in Cryptocurrency Portfolio

Authors: Muzzamil Rehman; Babli Dhiman; Gagandeep Singh Cheema; Ubaid Ahmad Peer; Syed Mohd Khalid;

A Systematic and Bibliometric Analysis of Risk and Return Management in Cryptocurrency Portfolio

Abstract

Abstract: This paper aims to map the existing literature on risk and return management, in the crypto-currency portfolio to understand various strategies and methods investors use. This paper conducts a systematic review of the research done between 2012 and 2022 in the area of risk and return management in cryptocurrencies. In this paper PRISMA framework for the systematic literature review was used; 257 research articles specific to crypto-currency and risk and return were identified through a structured keyword search on the Scopus Database. It was observed that most of the authors had preferred the Markov-switching regime and support vector machines (SVM) for better risk management in crypto-currency. It was observed that the risk associated with one crypto is not the same as other currencies, and the magnitude of return also varies. So, most of the authors have favoured the mixed model of cryptocurrency to mitigate the risk and multiply the profits. Volatility in the cryptocurrency market is very high as compared to other financial markets but has improved due to leverage effects and volatility persistence. The additional impression of this article is that it has made a collective and comparative analysis of risk and return in cryptocurrency. However, the research was limited to only a few factors, databases, and timeframe, and many other factors may be the avenues for the upcoming studies. Keywords: Cryptocurrency, Portfolio, VOSviewer, Bitcoin, Risk and Return

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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