The determinants of bitcoin returns and volatility: A quantile regression approach
The peak of the global financial crisis gave rise to the popularity and growth of the cryptocurrency market, particularly the bitcoin market. The issue centering on the price predictability of bitcoin is crucial to global investors and policymakers. Therefore, the present research aims to investigat...
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my.uum.etd.111092024-05-27T03:15:07Z https://etd.uum.edu.my/11109/ The determinants of bitcoin returns and volatility: A quantile regression approach Afshan, Sahar HG Finance The peak of the global financial crisis gave rise to the popularity and growth of the cryptocurrency market, particularly the bitcoin market. The issue centering on the price predictability of bitcoin is crucial to global investors and policymakers. Therefore, the present research aims to investigate the causal and predictive factors influencing the two major price dynamics of bitcoin i.e., returns and volatility, from October 9, 2013, to December 31, 2020. In doing so, the study analysed seven market micro-structure and financial variables and applied the advanced quantile-based method. The results observed the overall unidirectional quantile causality from bitcoin returns to market size, equity market, and financial uncertainty. The results found that bitcoin liquidity, information demand, energy, and gold prices cause bitcoin returns and vice versa. As for the bitcoin volatility, the findings confirmed the quantile causal association between equity prices to bitcoin volatility in all market states. Alternatively, bitcoin liquidity, market size, information demand, energy prices, and gold prices have shown feedback causality with the bitcoin volatility. Furthermore, the study found that the predictability of bitcoin returns relies on liquidity, market size, energy prices, gold prices, and financial uncertainty. However, only market liquidity and energy prices are found to partially influence bitcoin returns during normal market conditions. The findings regarding bitcoin volatility found that similar variables of liquidity, market size, energy and gold prices, and financial uncertainty are crucial to predict bitcoin volatility. However, bitcoin volatility is more predictable in a low-to-medium volatile market. The results established that during high volatile bitcoin market, only liquidity and energy prices partially influence bitcoin volatility. The outcomes have implications for managers, investors, and regulators in highlighting the relevance of the studied variables in the bitcoin market while emphasising the eminence of market states to support efficient risk management. 2021 Thesis NonPeerReviewed text en https://etd.uum.edu.my/11109/1/s903052_01.pdf text en https://etd.uum.edu.my/11109/2/s903052_02.pdf Afshan, Sahar (2021) The determinants of bitcoin returns and volatility: A quantile regression approach. Doctoral thesis, Universiti Utara Malaysia. |
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The peak of the global financial crisis gave rise to the popularity and growth of the cryptocurrency market, particularly the bitcoin market. The issue centering on the price predictability of bitcoin is crucial to global investors and policymakers. Therefore, the present research aims to investigate the causal and predictive factors influencing the two major price dynamics of bitcoin i.e., returns and volatility, from October 9, 2013, to December 31, 2020. In doing so, the study analysed seven market micro-structure and financial variables and applied the advanced quantile-based method. The results observed the overall unidirectional quantile causality from bitcoin returns to market size, equity market, and financial uncertainty. The results found that bitcoin liquidity, information demand, energy, and gold prices cause bitcoin returns and vice versa. As for the bitcoin volatility, the findings confirmed the quantile causal association between equity prices to bitcoin volatility in all market states. Alternatively, bitcoin liquidity, market size, information demand, energy prices, and gold prices have shown feedback causality with the bitcoin volatility. Furthermore, the study found that the predictability of bitcoin returns relies on liquidity, market size, energy prices, gold prices, and financial uncertainty. However, only market liquidity and energy prices are found to partially influence bitcoin returns during normal market conditions. The findings regarding bitcoin volatility found that similar variables of liquidity, market size, energy and gold prices, and financial uncertainty are crucial to predict bitcoin volatility. However, bitcoin volatility is more predictable in a low-to-medium volatile market. The results established that during high volatile bitcoin market, only liquidity and energy prices partially influence bitcoin volatility. The outcomes have implications for managers, investors, and regulators in highlighting the relevance of the studied variables in the bitcoin market while emphasising the eminence of market states to support efficient risk management. |
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Afshan, Sahar |
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The determinants of bitcoin returns and volatility: A quantile regression approach |
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The determinants of bitcoin returns and volatility: A quantile regression approach |
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The determinants of bitcoin returns and volatility: A quantile regression approach |
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The determinants of bitcoin returns and volatility: A quantile regression approach |
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The determinants of bitcoin returns and volatility: A quantile regression approach |
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determinants of bitcoin returns and volatility: a quantile regression approach |
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2021 |
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https://etd.uum.edu.my/11109/1/s903052_01.pdf https://etd.uum.edu.my/11109/2/s903052_02.pdf https://etd.uum.edu.my/11109/ |
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