Does blockchain patent-development influence Bitcoin risk?

Hu, Yang; Hou, Yang; Oxley, Les; Corbet, Shaen

doi:10.1016/j.intfin.2020.101263

Cited by 21 publications

(5 citation statements)

References 58 publications

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“…The "decentralization" of cryptocurrencies also plays a role in circumventing capital controls. The fact that cryptocurrencies are borderless and largely technologically independent of existing financial institutions makes them suitable for capital flight in a largely unregulated manner (Hu et al, 2021).…”

Section: Theoretical Hypothesismentioning

confidence: 99%

RETRACTED: The Impact of FOMC Announcements on Cryptocurrency Risk Spillover in Different Market Conditions

2024

Preprint

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This paper investigates the impact of FOMC announcements on cryptocurrency risk spillovers under different market conditions and their mechanisms of action. We calculate the high-frequency RGARCH volatilities of four major dirty cryptocurrencies and six major clean currencies, and apply the quantile-expanded joint-network approach to test their risk spillovers under different market conditions, and then investigate their impact and mechanism of action by monetary shocks. The results show that: (i) The total spillover in the extreme volatility market is larger than the total spillover in the normal market, and there is a tail asymmetry. (ii) The total cryptocurrency risk spillover in the highly volatile market, the normal market, and the smooth volatility market are all positively affected by monetary shocks. (iii) Mechanism analysis shows that the FOMC announcement will have an impact on the total cryptocurrency market risk spillover through two channels, which are changing the market expectations and hedging demand. Heterogeneity analysis shows that clean cryptocurrencies have positive net spillovers to dirty cryptocurrencies, and the mutual spillovers between the two are significantly affected by monetary shocks in extremely volatile markets.

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Section: Theoretical Hypothesismentioning

confidence: 99%

RETRACTED: The Impact of FOMC Announcements on Cryptocurrency Risk Spillover in Different Market Conditions

2024

Preprint

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“…Giudici and Polinesi (2019) primarily identified that Bitcoin exchange prices are positively related to each other and large exchanges Bitstamp, drive the prices. Such destabilising effects of fraud and regulatory events had also been identified by , , Katsiampa et al (2019a), Katsiampa et al (2019b) and Hu et al (2020). Evidence supporting the predictability of Bitcoin futures prices through the use of machine learning would not explicitly be a unique characteristic to cryptocurrency markets, as it has been previously identified across several assets such as foreign exchange markets (Plakandaras et al 2015) and several other asset markets , it is essential to note that it is contrary to the efficient markets hypotheses, where prices should follow a martingale process.…”

Section: Previous Literaturementioning

confidence: 81%

Forecasting mid-price movement of Bitcoin futures using machine learning

et al. 2021

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In the aftermath of the global financial crisis and ongoing COVID-19 pandemic, investors face challenges in understanding price dynamics across assets. This paper explores the performance of the various type of machine learning algorithms (MLAs) to predict mid-price movement for Bitcoin futures prices. We use high-frequency intraday data to evaluate the relative forecasting performances across various time frequencies, ranging between 5 and 60-min. Our findings show that the average classification accuracy for five out of the six MLAs is consistently above the 50% threshold, indicating that MLAs outperform benchmark models such as ARIMA and random walk in forecasting Bitcoin futures prices. This highlights the importance and relevance of MLAs to produce accurate forecasts for bitcoin futures prices during the COVID-19 turmoil.

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“… 2 Such research builds upon work that investigates contagion and spillover effects due to a variety of behavioural effects relating to cryptocurrency dynamics. Important work here includes, ( Cioroianu et al, 2020a , b ; Meegan et al, 2018 ; Akhtaruzzaman et al, 2020 ; Akyildirim, Corbet, Cumming, Lucey, and Sensoy, 2020 ; Hu et al, 2020 ; Katsiampa et al, 2019a , b ) and ( Akyildirim, Corbet, Sensoy, and Yarovaya, 2020 ). A concise review of cryptocurrency market behaviour is provided by Corbet et al (2019) .…”

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confidence: 99%

The influence of the COVID-19 pandemic on the hedging functionality of Chinese financial markets

Corbet

Hou

et al. 2022

Research in International Business and Finance

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In this paper, we investigate both constant and time-varying hedge ratios in terms of the effectiveness of CSI300 index futures during the COVID-19 crisis. Using naïve, OLS and EC/ROLS strategies to estimate constant hedge ratios, results indicate that the CSI300 spot index presents decreased effectiveness using the naïve hedging strategy; however, increased effectiveness of OLS and EC hedge ratios are identified. Differential behaviour is identified when considering five newly introduced COVID-19 concept-based stock indices. Time-varying hedge ratios indicate the weakened effectiveness, ranging between 20% and 40% variance reduction. Evidence suggests that the capability of the CSI300 index futures to hedge against the risks of the COVID-19 is impaired, regardless of whether constant or time-varying hedge ratios are used. Such results provide important implications to both local and foreign investors in the Chinese stock market.

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Does blockchain patent-development influence Bitcoin risk?

Cited by 21 publications

References 58 publications

RETRACTED: The Impact of FOMC Announcements on Cryptocurrency Risk Spillover in Different Market Conditions

RETRACTED: The Impact of FOMC Announcements on Cryptocurrency Risk Spillover in Different Market Conditions

Forecasting mid-price movement of Bitcoin futures using machine learning

The influence of the COVID-19 pandemic on the hedging functionality of Chinese financial markets

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