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Titel
Volatility estimation for Bitcoin : a comparison of ARCH-models including Google Trends & alternative cryptocurrencies / author: Jules Kamps
VerfasserKamps, Jules
Betreuer / BetreuerinnenBank, Matthias
ErschienenInnsbruck, 2018
HochschulschriftUniversity of Innsbruck, Masterarbeit, 2018
Datum der AbgabeJuni 2018
SpracheEnglisch
DokumenttypMasterarbeit
Schlagwörter (DE)Bitcoin / Cryptocurrencies / Klassifizierung von Geld / Bitcoin return / Bitcoin Preisvolatilität / Tauschmittel / Rechnungseinheit / Wertaufbewahrung / lineare Regression / Familie von ARCH-Modellen / asymmetrische ARCH-Modelle / Bitcoin tägliche Suchtrends / Ethereum / Litecoin / Monero / GJR - GARCH model / vorhersagekraft
Schlagwörter (EN)Bitcoin / Cryptocurrencies / classification of money / Bitcoin return / Bitcoin price volatility / medium of exchange / unit of account / store of value / linear regression / family of ARCH models / asymmetric ARCH models / Bitcoin Daily Search Trends / Ethereum / Litecoin / Monero / GJR - GARCH model / predictive power
Schlagwörter (GND)Bitcoin / Virtuelle Währung / Volatilität / ARCH-Prozess / Lineare Regression
URNurn:nbn:at:at-ubi:1-23726 Persistent Identifier (URN)
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Volatility estimation for Bitcoin [2.88 mb]
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Zusammenfassung (Englisch)

This paper aims to investigate different magnitudes of Bitcoin and cryptocurrencies regarding the classification of money, the correlation between Bitcoin return and possible determinants, and the estimation of Bitcoin price volatility. The theoretic framework proposes evidence if Bitcoin and cryptocurrencies can be classified as money. Currently, Bitcoin and other cryptocurrencies do not possess the different characteristics of money. Bitcoin and other cryptocurrencies do not yet function as a desirable medium of exchange, as scalability issues need to be resolved. Bitcoin and other cryptocurrencies also perform poorly as a store of value, as the exchange rate of Bitcoin and cryptocurrencies is widely fluctuating, and therefore unstable. The empirical research provides evidence for possible determinants of Bitcoin return and estimation of Bitcoin price volatility. The correlation of possible determinants with Bitcoin return is captured with linear regression. It shows that the return of Bitcoin Daily Search Trends and the return of other cryptocurrencies ‘Ethereum, ‘Litecoin, and ‘Monero are significant in the determination of Bitcoin return. Bitcoin price volatility is analyzed by examining the family of ARCH models. It shows that the asymmetric ARCH models provide the best fitting results, more precise, the GJR GARCH model. The determinants are also significant in the estimation of Bitcoin price volatility and increase the predictive power of the GJR GARCH model.

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