Bitcoin and investor sentiment: Statistical characteristics and predictability

Eom, Cheoljun; Kaizoji, Taisei; Kang, Sang Hoon; Pichl, Lukáš

doi:10.1016/j.physa.2018.09.063

Cited by 87 publications

(43 citation statements)

References 20 publications

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“…However, our paper has limitations that could be addressed by those who would like to expand this field, such as the omission of the United States of America and Europe stock markets as well as the other methodologies for testing including vine-copulas, Extreme Value Theory, etc. In particular, we omitted studies using more advanced quantitative techniques such as copula causality as in Dastgir et al (2019a, b) or other performance measures such as those of Saito (2019) or Eom et al (2019). More interestingly, the follow-up studies also employ the alternative techniques from Jiang et al (2017) and Kou et al (2012) such as wavelet and VMD-based copula tests and classification algorithms using MCDM and rank correlation for risk model construction.…”

Section: Discussionmentioning

confidence: 99%

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Tail dependence in emerging ASEAN-6 equity markets: empirical evidence from quantitative approaches

Duong

Huynh

2020

Financ Innov

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This study contributes a rich set of quantitative methodologies including a nonparametric approach (Chi-plots and K-plots) as well as copulas (traditional and timevarying with Student's t-copulas) to the existing literature in terms of determining the dependence structure in ASEAN stock markets. Drawing on the emerging ASEAN equity returns of six countries from January 2001 to December 2017, we found that Student's t-copulas under time-varying approach is the most appropriate approach to explain these co-movements. Among all research return pairs, the dependence between Vietnam and other ASEAN equity indices has the lowest value. Meanwhile, all couples show left-and right-tail dependence by each pair for pre-and postfinancial shocks. Hence, diversification across these pairs of equity markets from ASEAN is still adequate for international investors, though it might trigger contagion risks.

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Section: Discussionmentioning

confidence: 99%

“…This is the main approach of the K-plot (or Kendall-plot). Furthermore, we also refer to the studies by Dastgir et al (2019a, b) and other performance measures from Saito (2019) and Eom et al (2019) for recent literature incorporating new research methodologies of copula Causality.…”

Section: Non-parametric Approachmentioning

confidence: 99%

Tail dependence in emerging ASEAN-6 equity markets: empirical evidence from quantitative approaches

Duong

Huynh

2020

Financ Innov

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“…In consideration of future cash flow, financial stock values in different markets may produce different results. Eom et al (2019) indicated that volatilities in virtual currency returns are affected by investors' sentiment and monetary assets, but did not explain whether virtual currency volatilities reversely affect assets in the financial market. An explanation to the second issue can supplement the study gaps of Eom et al (2019).…”

Section: Introductionmentioning

confidence: 93%

“…Guesmi, Saadi, Abid, and Ftiti (2019) indicated that bitcoin not only has significant hedging effects, but also spills over the connotation of virtual currency value changes into the commodities and corporate financial variables in the financial industry through transmission mechanisms. After investigating the statistical properties of bitcoin, Eom, Kaizoji, Kang, and Pichl (2019) found that investors' sentiment and monetary assets have significant impacts on bitcoin volatilities.…”

Section: Introductionmentioning

confidence: 99%

Does virtual currency development harm financial stocks’ value? Comparing Taiwan and China markets

2020

Economic Research-Ekonomska Istraživanja

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This research incorporated virtual currency development factors into the capital asset pricing model (CAPM) and interpreted the effects of bitcoin and fin-tech on the capital market through a deduction of the portfolio theory and innovation diffusion theory (IDT) on changes to financial stocks' value. This paper examined a total of 67,166 panel data of financial stocks in the two emerging markets of Taiwan and China between July 2016 and April 2019, presenting the following significant findings. (1) Financial stocks in Taiwan's market are more greatly shocked by the bitcoin and interaction effect between bitcoin and fin-tech than those in China's market. (2) Even after changing proxy variable or autocorrelation and heteroskedasticity are considered, the asymmetric shocks on financial stocks in Taiwan's market are still great. (3) The effects of the two variables of bitcoin and interaction with fin-tech on financial stocks are consistently important as the three-factor CAPM model. (4) Transmitted by the changes in currency supply and demand as well as exchange rate volatilities, the spillover effects of virtual currencies and financial innovation indirectly change the currency multiplier of the home country, investors' sensibility to interest rates, and balance of import and export trades and may eventually impact the gross outputs and inflation of individual economies.

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“…Another factor that determines the popularity of cryptocurrencies, according to Eom, Kaizoji, Kang, and Pichl (2019), is the high volatility. No one knows what the future holds for cryptocurrencies, although Dibrova (2016) sees great potential for the development of the cryptocurrency market.…”

Section: Introductionmentioning

confidence: 99%

Analysis of cryptocurrencies market: current situation, tendencies of household investment and future forecasting

Pieczulis

Taujanskaitė

2019

Proceedings of 6th International Scientific Conference Contemporary Issues in Business, Management and Economics Engineering ‘2

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Purpose – the purpose of this study is to analyse the cryptocurrency market and to forecast household investments in it from a theoretical and practical point of view. Research methodology – in order to achieve the aim of the article, scientific literature and statistical data analysis, comparative analysis and SWOT analysis were done. Also, ARIMA forecasting model was adapted to forecast Household investment in cryptocurrencies. Findings – the first part of the study presents the theoretical aspects of cryptocurrencies. An overview of the cryptocurrencies and their market is provided, focusing on the concept of Bitcoins, its’ mining and technical principles of operation. The second part of this study is intended to analyse the cryptocurrencies market and its dynamics. In the last part of the research tendencies of household investments in cryptocurrencies are examined for the period of 2016–2019 according to the data from cryptocurrency exchange. Also, household investments in cryptocurrencies are analysed and major future investment trends and seasonality are identified as well. Household future investment in cryptocurrencies is also predicted. Research limitations – data used in the research only includes currency exchange information, that may be inaccurate when concluding the main trends of the market. Practical implications – the practical results of the study may be useful for households interested in investing, especially in risky investment alternatives. Results of the research justify the dynamics of the currency market and the fluctuation of cryptocurrencies’ prices that shows that investment in cryptocurrencies is very variable, unstable and risky. Originality/Value – cryptocurrencies market is particularly dynamic and fast-changing, so the newest scientific investigations are urgent. In this research, an attempt was made to forecast household investment in main cryptocurrencies

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Bitcoin and investor sentiment: Statistical characteristics and predictability

Cited by 87 publications

References 20 publications

Tail dependence in emerging ASEAN-6 equity markets: empirical evidence from quantitative approaches

Tail dependence in emerging ASEAN-6 equity markets: empirical evidence from quantitative approaches

Does virtual currency development harm financial stocks’ value? Comparing Taiwan and China markets

Analysis of cryptocurrencies market: current situation, tendencies of household investment and future forecasting

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