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What Drives Bitcoin Volatility?

Hans Bystrom, Dominika Krygier
2018 Social Science Research Network  
A stronger positive link is found between Bitcoin volatility and search pressures on Bitcoin-related words on Google, particularly for the word "bitcoin".  ...  To further assess what drives Bitcoin volatility we turn to a VAR-analysis and impulse response functions which point at Google searches for the word "bitcoin", and to some extent the USD currency index  ...  The following nine variables starting with G are Google search strings collected from Google Trends. Summary statistics for variables.  ... 
doi:10.2139/ssrn.3223368 fatcat:c7duuozytnbaxbm7yfx64gq5wm

Bitcoin Analysis and Forecasting through Fuzzy Transform

Maria Letizia Guerra, Laerte Sorini, Luciano Stefanini
2020 Axioms  
Finally, we examine the dependence of Bitcoin prices on Google Trend scores and we estimate short-term forecasting models; the Diebold–Mariano (DM) test statistics, applied for their significance, shows  ...  Sentiment analysis to characterize the properties of Bitcoin prices and their forecasting is here developed thanks to the capability of the Fuzzy Transform (F-transform for short) to capture stylized facts  ...  Acknowledgments: The authors would like to thank the editors and the anonymous reviewers for their meaningful and constructive suggestions that have led to the present improved version of the paper.  ... 
doi:10.3390/axioms9040139 fatcat:cvauo2sodbhtvcsxpsiw7kohu4

Social signals and algorithmic trading of Bitcoin

David Garcia, Frank Schweitzer
2015 Royal Society Open Science  
In our analysis, we include economic signals of volume and price of exchange for USD, adoption of the Bitcoin technology, and transaction volume of Bitcoin.  ...  We verify this high profitability with robust statistical methods that take into account risk and trading costs, confirming the long-standing hypothesis that trading based social media sentiment has the  ...  Social signals We record the overall interest towards Bitcoin through information search, as quantified by the Google trends volume for the term 'bitcoin', S(t), as recorded in early 2015 and shown in  ... 
doi:10.1098/rsos.150288 pmid:26473051 pmcid:PMC4593685 fatcat:n7tqnhz7a5ftphi4riy6juwisy

Real-time Prediction of Bitcoin Bubble Crashes [article]

Min Shu, Wei Zhu
2019 arXiv   pre-print
on the LPPLS model and finer (than daily) timescale for the Bitcoin price data.  ...  The adaptive multilevel time series detection methodology can provide real-time detection of bubbles and advanced forecast of crashes to warn of the imminent risk.  ...  Acknowledgment The authors would like to thank the Stony Brook Research Computing and Cyberinfrastructure, and the Institute for Advanced Computational Science at Stony Brook University for access to the  ... 
arXiv:1905.09647v2 fatcat:lfsyifjkgbbdhdnxrr5mlxrksq

What Drives Bitcoin? An Approach from Continuous Local Transfer Entropy and Deep Learning Classification Models

Andrés García-Medina, Toan Luu Duc Luu Duc Huynh
2021 Entropy  
The proposed variable selection do not find significative the explanatory power of NASDAQ and Tesla.  ...  In other words, our results indicate that in times of high volatility, Bitcoin seems to self-regulate and does not need additional drivers to improve the accuracy of the price direction.  ...  Thus, the diverse stylized facts of Bitcoin, including heteroskedasticity and long memory, require uncertainty to be controlled in the model.  ... 
doi:10.3390/e23121582 pmid:34945888 pmcid:PMC8700167 fatcat:z2vxksscpjgrnpoclemns2gbom

Bitcoin: an alternative currency to pay for goods and services or a useful investment tool?

Zuzana Rowland, Petr Suler, Bohdana Cajkovicova, T. Kliestik
2021 SHS Web of Conferences  
Methods: Analysing bitcoin statistical features, we found no connection with traditional asset categories such as stock, bonds and commodities either in intermediate time, or periods of financial crises  ...  Research background: Bitcoin is defined as digital money in a peer-to-peer decentralized payment network, an amalgam hybrid between fiat and commodity currency without a real value.  ...  Regarding the fact that the grey system theory enables low-data and incomplete-information predictions, we adopted this convenient method to forecast bitcoin prices for the following day.  ... 
doi:10.1051/shsconf/202112903026 fatcat:7ntfroqz7bd7jnwlnnb2ik3h5u

Expectations of Macroeconomic News Announcements: Bitcoin vs. Traditional Assets

Ivan Mužić, Ivan Gržeta
2022 Risks  
It is also evident that the trading volume of Bitcoin does not change, unlike other assets, suggesting that the price of Bitcoin is always moved by the same players, indicating the closed and, therefore  ...  Finally, we found evidence that the impact of macroeconomic announcements on Bitcoin returns is stronger when the announcements are negative but, interestingly, the returns of Bitcoin, unlike those of  ...  From the commonly used Google Trends (Urquhart 2018; Aalborg et al. 2019; Dastgir et al. 2019 )-which essentially proves that Google searches do not influence price, but price influences Google searches-to  ... 
doi:10.3390/risks10060123 doaj:7c575be04b714975959ca67f54f31689 fatcat:ga4ijfikh5hsldfcv52vrnzf7i

Satoshi Nakamoto and the Origins of Bitcoin – The Profile of a 1-in-a-Billion Genius [article]

Jens Ducrée
2022 arXiv   pre-print
In a purposely agnostic, and meticulous "lea-ving no stone unturned" approach, this study presents new hard facts, which evidently slipped through Satoshi Nakamoto's elaborate privacy shield, and derives  ...  Evidence compounds towards a substantial role of the Benelux cryptography ecosystem, with strong transatlantic links, in the creation of Bitcoin.  ...  Acknowledgements Many thanks to some of the grands of cryptography and blockchain the author got the opportunity to have quite revealing and inspiring communication with.  ... 
arXiv:2206.10257v14 fatcat:epytmeimqfcypi5vbnt3kvdh2q

Where do we stand in cryptocurrencies economic research? A survey based on hybrid analysis [article]

Aurelio F. Bariviera, Ignasi Merediz-Solà
2020 arXiv   pre-print
In this way, we offer a classification and analysis of the mounting research produced in a relative short time span.  ...  Firstly, by means of the distant reading provided by machine learning bibliometric techniques, we are able to identify main topics, journals, key authors, and other macro aggregates.  ...  Bitcoin attention (measured by the Google Trends search queries) and Bitcoin re- turns Bidirectional causality mainly exists in both tails Panagiotidis et al  ... 
arXiv:2003.09723v1 fatcat:yea2ckjc3nb2zaixy7i4fl6nly

Multivariate Analysis of Cryptocurrencies

Vincenzo Candila
2021 Econometrics  
In this work, the interdependencies among a panel of the most traded digital currencies are explored and evaluated from statistical and economic points of view.  ...  For this reason, investigating the daily volatility and co-volatility of cryptocurrencies is crucial for investors and portfolio managers.  ...  Paolella, the guest editor Fredj Jawadi, and three anonymous referees for their very helpful and constructive comments. Conflicts of Interest: The author declares no conflict of interest.  ... 
doi:10.3390/econometrics9030028 doaj:96e25620ab2549dca5578383533bfb1e fatcat:swsfkuvq7nckxf3angllrvyigq

Reddit as a prediction tool for crypto-assets

Luis Antonio Loredo Camou
2022 Revista Brasileira de Finanças  
Cryptocurrencies, such as Bitcoin and Ethereum, have recently become a conversation topic among the general population.  ...  We also offer evidence that the Reddit variables gain importance in market-wide and asset-specific events.  ...  Among them, Kristoufek (2013) studies the effect of search trends for Bitcoin in Wikipedia and Google.  ... 
doi:10.12660/rbfin.v20n1.2022.83888 fatcat:fpcw6otqrbh4hnoz5zxnnpfcia

A Comprehensive Statistical Analysis of the Six Major Crypto-Currencies from August 2015 through June 2020

Beatriz Vaz de Melo Mendes, André Fluminense Carneiro
2020 Journal of Risk and Financial Management  
Using daily data we (1) showed that the returns present many of the stylized facts often observed for stock assets, (2) modeled the returns underlying distribution using a semi-parametric mixture model  ...  approach to compute risk measures, such as the value-at-risk, the expected shortfall, and drawups, (5) found that the crypto-coins' price trajectories do not contain speculative bubbles and that they  ...  In Dro żd ż et al. ( 2018 ) the well known stylized facts were investigated.  ... 
doi:10.3390/jrfm13090192 fatcat:dd2xeh43wzebdhqtwguyz25whi

Blockchain and Cryptocurrencies [chapter]

Neha Mason, Malka N. Halgamuge, Kamalani Aiyar
2021 Exploring the Convergence of Big Data and the Internet of Things  
In financial trading, cryptocurrencies like bitcoin use decentralization, traceability, and anonymity features to perform transactional activities.  ...  This chapter analyzes various legal and ethical implications, their effects, and various solutions to overcome the inherent issues that are currently faced by the policymakers and regulators.  ...  Acknowledgments: We are grateful for the anonymous referees and guest editors for their remarks. Any remaining errors are my own responsibilities.  ... 
doi:10.4018/978-1-7998-6650-3.ch007 fatcat:ubsh5ikff5hpzk52l65hai7lgy

Contrasting Cryptocurrencies with Other Assets: Full Distributions and the COVID Impact

Esfandiar Maasoumi, Xi Wu
2021 Journal of Risk and Financial Management  
is statistically closely dependent on, and indifferent from Bitcoin daily return.  ...  We also find that the highest similarity before the COVID-19 outbreak is between Bitcoin and Coal, Steel and Mining industries, and after the COVID-19 outbreak is between Bitcoin and Business Supplies,  ...  Our objective in this paper is to revisit some stylized facts of cryptocurrency markets and employ econometrics models for accurate volatility forecasts.  ... 
doi:10.3390/jrfm14090440 fatcat:6odqf3snujemphrapxe5pjo6iq

To keep faith with homoskedasticity or to go back to heteroskedasticity? The case of FATANG stocks

José Dias Curto
2021 Nonlinear dynamics  
of nine returns series that include individual FATANG stocks (FAANG: Facebook, Amazon, Apple, Netflix and Google; plus Tesla) and US indices (S&P 500, DJIA and NASDAQ).  ...  In this paper, we provide evidence in favor of a "quietness" in the stock markets, interrupted by COVID-19, by analyzing dispersion, skewness and kurtosis characteristics of the empirical distribution  ...  Availability of data and material The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.  ... 
doi:10.1007/s11071-021-06535-8 pmid:34075278 pmcid:PMC8162171 fatcat:jmuibitugvcknolpjkdeobkvee
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