Nonlinear dynamics analysis of cryptocurrency price fluctuations based on Bitcoin

Tong, Zhongwen; Chen, Zhanbo; Zhu, Chen

doi:10.1016/j.frl.2022.102803

Cited by 24 publications

(8 citation statements)

References 14 publications

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“…Our results are also coloborating with the previous literature on information flow between log returns of cryptocurrencies and other financial time series. For example, recently, Tong et al [ 9 ] also studied Bitcoin price dynamics and showed fractal and chaotic characteristics along with long-memory behavior and a positively correlated nature. Additionally, Assaf et al [ 41 , 42 ] and Keskin and Aste [ 63 ] used information transfer between time series using transfer entropy methods to detect the bi-directional flow between BTC and other cryptocurrency’s prices.…”

Section: Discussionmentioning

confidence: 99%

“…Additionally, Bitcoin has fractal characteristics, and cryptocurrency price fluctuations have a long memory of price volatility. The price fluctuation of cryptocurrency does not follow the random walk model and is a system with chaotic characteristics [ 9 ]. In literature, information-theoretic measures frameworks have been significantly used to detect the nonlinear dynamics of asset prices, volatilities, and construction of risk-neutral densities.…”

Section: Introductionmentioning

confidence: 99%

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Volatility Dynamics of Non-Linear Volatile Time Series and Analysis of Information Flow: Evidence from Cryptocurrency Data

Sheraz

Dedu

Preda

2022

Entropy

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This paper aims to empirically examine long memory and bi-directional information flow between estimated volatilities of highly volatile time series datasets of five cryptocurrencies. We propose the employment of Garman and Klass (GK), Parkinson’s, Rogers and Satchell (RS), and Garman and Klass-Yang and Zhang (GK-YZ), and Open-High-Low-Close (OHLC) volatility estimators to estimate cryptocurrencies’ volatilities. The study applies methods such as mutual information, transfer entropy (TE), effective transfer entropy (ETE), and Rényi transfer entropy (RTE) to quantify the information flow between estimated volatilities. Additionally, Hurst exponent computations examine the existence of long memory in log returns and OHLC volatilities based on simple R/S, corrected R/S, empirical, corrected empirical, and theoretical methods. Our results confirm the long-run dependence and non-linear behavior of all cryptocurrency’s log returns and volatilities. In our analysis, TE and ETE estimates are statistically significant for all OHLC estimates. We report the highest information flow from BTC to LTC volatility (RS). Similarly, BNB and XRP share the most prominent information flow between volatilities estimated by GK, Parkinson’s, and GK-YZ. The study presents the practicable addition of OHLC volatility estimators for quantifying the information flow and provides an additional choice to compare with other volatility estimators, such as stochastic volatility models.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Volatility Dynamics of Non-Linear Volatile Time Series and Analysis of Information Flow: Evidence from Cryptocurrency Data

Sheraz

Dedu

Preda

2022

Entropy

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“…Cryptocurrencies are not in any way insured by the government which implies that money saved in online wallets is not in any way protected like the money kept in banks. The value and price of Cryptocurrency change almost per hour and cannot be accurately forecasted sometimes [16]. There is no assurance of a positive return on investment in Cryptocurrency which is why it is called a volatile market.…”

Section: Relationship Between Fiat Money and Bitcoinmentioning

confidence: 99%

An appraisal of ethical issues and the effect of artificial intelligence on the cryptocurrency market

Ogunyolu¹,

Adebayo²

2022

Global J. Eng. Tech. Adv.

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The world has gradually embraced Cryptocurrency at various levels of capacity and it is not governed or regulated by any Control system. It has over time been used by participants as a means to invest despite the volatility of the market. Though Government does not have the means to outright stop the virtual marketing deals of Cryptocurrency, recently Nigerian government called for deposit money banks to close all corresponding accounts which are perceived to be involved in Cryptocurrency trading. The Crypto market has evolved as the digital and internet world exponentially evolved. Sadly, Cryptocurrency has been misused by illegal participants and exploited wrongly which has caused a lot of worrisome issues around the world like loss of funds, hacking of financial databases, terrorist financing, and identity fraud. This paper aims to identify the methodology surrounding the world of Cryptocurrency and how advancement in technology through artificial intelligence can help solve ethical issues related to cryptocurrency trading. Based on these appraisals, we highlighted procedures to provide a safer, secure, and relatable market for every interested individual.

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“…Among notable studies, many researchers examine the spillover effect of digital currencies in general and of Bitcoin, in particular, on several types of conventional assets, such as stocks, gold, and currencies (Akhtaruzzaman et al, 2022;Elsayed et al, 2022;Guesmi et al, 2019;Klein et al, 2018;Kristjanpoller & Bouri, 2019;Mo et al, 2022;Zeng et al, 2020). Meanwhile, the realm of cryptocurrencies has also been vastly examined from various perspectives, including return and volatility (Bianchi & Babiak, 2022;Chaim & Laurini, 2018;Huang et al, 2022;Malladi & Dheeriya, 2021), fundamental value (Cheah & Fry, 2015;Vidal-Tomás, 2022), and liquidity dynamics (Eross et al, 2019;Li et al, 2022;Scharnowski, 2020;Tong et al, 2022). However, these studies are mainly from the perspective of mainstream finance.…”

Section: Introductionmentioning

confidence: 99%

The Impact of Cryptocurrency Volatility Dynamics on the Islamic Equity Market: The Case of Emerging Asia

Bakar

Foziah

2024

Asian Economics Letters

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This paper investigates the impact of the realized volatility of positive and negative intraday Bitcoin returns on the sensitivity of Shariah-compliant stocks’ orthogonalized returns. We identify the impact in different market states and find that Bitcoin’s upside volatility negatively affects the returns of Islamic equities. The paper contributes to uncovering the properties of a niche Islamic Emerging Asian equity market. The findings offer important implications for investors’ diversification strategies.

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Nonlinear dynamics analysis of cryptocurrency price fluctuations based on Bitcoin

Cited by 24 publications

References 14 publications

Volatility Dynamics of Non-Linear Volatile Time Series and Analysis of Information Flow: Evidence from Cryptocurrency Data

Volatility Dynamics of Non-Linear Volatile Time Series and Analysis of Information Flow: Evidence from Cryptocurrency Data

An appraisal of ethical issues and the effect of artificial intelligence on the cryptocurrency market

The Impact of Cryptocurrency Volatility Dynamics on the Islamic Equity Market: The Case of Emerging Asia

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