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Cryptocurrency volatility, volatility spillovers and the effect of global investor sentiment.

dc.contributor.advisorMuguto, Hilary Tinotenda.
dc.contributor.advisorNhlapo, Rethabile.
dc.contributor.authorRathilal, Sahil.
dc.date.accessioned2022-04-13T07:00:23Z
dc.date.available2022-04-13T07:00:23Z
dc.date.created2021
dc.date.issued2021
dc.descriptionMasters Degree. University of KwaZulu-Natal, Durban.en_US
dc.description.abstractCryptocurrencies continue to enjoy attention from investors and policymakers and their growing usage has fortified this attention. However, it is their volatility and the volatility spillovers among the cryptocurrencies have been most intriguing. Various factors such as susceptibility to speculative pressures, uncertainty regarding their valuation, and the lack of regulation have been forwarded as possible explanations. However, these factors have not fully explained cryptocurrency volatility and volatility spillovers, suggesting that there could be other salient factors. In this study, investor sentiment, described as the noise-driven investors' perception of the risk and cash flows of an asset, was forwarded as one of those salient factors. Specifically, this study sought to examine the nature of volatility and volatility spillovers among currencies and their subjectivity to global investor sentiment. Bitcoin, Ethereum and Ripple and an investor sentiment index constructed from a set of five proxies over a period spanning February 2018 to August 2021 were employed. For the analysis, the study employed GARCH models to examine the nature of cryptocurrency volatility, the ADCC-GARCH framework and the Diebold-Yilmaz spillover index to examine the nature of cryptocurrency volatility spillovers, and the Toda-Yamamoto model to examine the causality between cryptocurrencies and investor sentiment. The study found evidence of significant sentiment effects in both mean and variance equations of the cryptocurrencies. Similarly, the analysis of comovements and spillovers showed that there were significant sentiment effects on the phenomena. Failure to account for investor sentiment could, therefore, lead to poor estimation of volatility and volatility spillovers. The results have implications for investors, speculators, and policymakers alike. The results obtained provided an insight on the effect of investor sentiment on cryptocurrency volatility and showed how the market reacts to the investors' behaviour where their actions influence volatility. The investors and speculators may then use the insight on sentiment to determine the market volatility to earn returns accordingly. Further, policymakers can use this to determine the optimal regulations to prevent excessive volatility in this market. The study, therefore contributes to the debate on the drivers of cryptocurrency volatility. It also contributes to literature by introducing a measure of investor sentiment.en_US
dc.identifier.urihttps://researchspace.ukzn.ac.za/handle/10413/20320
dc.language.isoenen_US
dc.subject.otherVolatility of markets.en_US
dc.subject.otherSpillovers.en_US
dc.subject.otherGeneralised Autoregressive Conditional Heteroskedasticity (GARCH)en_US
dc.subject.otherAsymmetric Dynamic Conditional Correlation (ADCC)en_US
dc.titleCryptocurrency volatility, volatility spillovers and the effect of global investor sentiment.en_US
dc.typeThesisen_US

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