Contagion Effect in Cryptocurrency Market

The rapid development of cryptocurrencies has drawn attention to this particular market, with investors trying to understand its behaviour and researchers trying to explain it. The evolution of cryptocurrencies’ prices showed a kind of bubble and a crash at the end of 2017. Based on this event, and on the fact that Bitcoin is the most recognized cryptocurrency, we propose to evaluate the contagion effect between Bitcoin and other major cryptocurrencies. Using the Detrended Cross-Correlation Analysis correlation coefficient (ΔρDCCA) and comparing the period after and before the crash, we found evidence of a contagion effect, with this particular market being more integrated now than in the past—something that should be taken into account by current and potential investors.

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Evolution of Cryptocurrency: Changes in the Use and Consumer Demand for Digital Transactions

International Journal for Research in Applied Science and Engineering Technology ◽

10.22214/ijraset.2021.38527 ◽

2021 ◽

Vol 9 (10) ◽

pp. 842-850

Author(s):

Dr. Varsha Agarwal

Keyword(s):

Correlation Analysis ◽

Cross Correlation ◽

Consumer Demand ◽

Private Bank ◽

The Past ◽

Digital Currency ◽

Air Pocket ◽

Cross Correlation Analysis ◽

Connection Coefficient ◽

Digital Transactions

Abstract: The quick advancement of cryptographic forms of money has caused to notice this specific market, with financial backers attempting to comprehend its conduct and analysts attempting to clarify it. The development of digital currencies' costs showed a sort of air pocket and an accident toward the finish of 2017. In view of this occasion, and on the way that Bitcoin is the most perceived digital currency, we propose to assess the infection impact among Bitcoin and other significant cryptographic forms of money. Utilizing the Detrended Cross-Correlation Analysis connection coefficient and looking at the period after and before the accident, we discovered proof of an infection impact, with this specific market being more incorporated now than in the past something that ought to be considered by current and likely financial backers. Cryptocurrency like Bitcoin have developed from being related only with geeks and revolutionaries to being considered by national banks as an innovation to carry out advanced cash. Digital forms of money exist just in computerized shape and can be moved totally between advanced addresses. This is both not normal for traditional electronic cash as perceived by laypersons which goes about as an obligation guarantee on a store with a confided in monetary foundation, for example, a private bank and dissimilar to ordinary bodily cash which might be truly moved by. This implies that any lawful rights related with holding digital forms of money should be diverse in spite of it being staying not entirely clear. In this , we take a gander at the different medicines of cash in the lawful detect and talk about the dangers related with each by drawing on genuine models. We presume that extortion through hacking might actually represent an issue to broad reception of cryptographic forms of money as the shortfall of plan of action against an outsider, for example, a bank amasses hazard in holders of digital currencies. Clients should hence practice alert and comprehend the dangers prior to putting resources into digital currencies. This admonition requires accentuation as many gatherings misunderstand the cryptography inside the innovation as shielding them from such misrepresentation when truth be told it does nothing of the sort. Keywords: Cryptocurrency, Cryptography, Digital Currencies, Bitcoin, Blockchain.

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Application of an Improved Correlation Method in Electrostatic Gait Recognition of Hemiparetic Patients

Sensors ◽

10.3390/s19112529 ◽

2019 ◽

Vol 19 (11) ◽

pp. 2529 ◽

Cited By ~ 1

Author(s):

Shanshan Tian ◽

Mengxuan Li ◽

Yifei Wang ◽

Xi Chen

Keyword(s):

Correlation Analysis ◽

Correlation Coefficient ◽

Cross Correlation ◽

Correlation Method ◽

Disease Diagnosis ◽

Characteristic Analysis ◽

Cross Correlation Analysis ◽

Gait Characteristic ◽

Scaling Index ◽

Coefficient Method

Hemiparesis is one of the common sequelae of neurological diseases such as strokes, which can significantly change the gait behavior of patients and restrict their activities in daily life. The results of gait characteristic analysis can provide a reference for disease diagnosis and rehabilitation; however, gait correlation as a gait characteristic is less utilized currently. In this study, a new non-contact electrostatic field sensing method was used to obtain the electrostatic gait signals of hemiplegic patients and healthy control subjects, and an improved Detrended Cross-Correlation Analysis cross-correlation coefficient method was proposed to analyze the obtained electrostatic gait signals. The results show that the improved method can better obtain the dynamic changes of the scaling index under the multi-scale structure, which makes up for the shortcomings of the traditional Detrended Cross-Correlation Analysis cross-correlation coefficient method when calculating the electrostatic gait signal of the same kind of subjects, such as random and incomplete similarity in the trend of the scaling index spectrum change. At the same time, it can effectively quantify the correlation of electrostatic gait signals in subjects. The proposed method has the potential to be a powerful tool for extracting the gait correlation features and identifying the electrostatic gait of hemiplegic patients.

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Correlações em séries temporais de preços de manga produzida no Vale do São Francisco

Research Society and Development ◽

10.33448/rsd-v10i12.20460 ◽

2021 ◽

Vol 10 (12) ◽

pp. e266101220460

Author(s):

Bruno de Freitas Assunção ◽

Ikaro Daniel de Carvalho Barreto ◽

Tatijana Stosic ◽

Borko Stosic

Keyword(s):

Correlation Analysis ◽

Correlation Coefficient ◽

Detrended Fluctuation Analysis ◽

Cross Correlation ◽

Fluctuation Analysis ◽

Cross Correlation Analysis ◽

Detrended Fluctuation

Nas últimas décadas o comércio de frutas no Brasil cresceu expressivamente atendendo ao mercado interno e externo. Dentre as principais frutas produzidas e comercializadas, destaca-se a manga, a fruta mais exportada pelo Brasil. Neste trabalho foram analisadas as séries temporais de retornos e de volatilidade de preços semanais de duas variedades de manga, Palmer e Tommy Atkins, produzidas no Vale do São Francisco, a região com a maior produção de manga no país. Foram utilizados os métodos Detrended Fluctuation Analysis (DFA) e Detrended Cross-Correlation Analysis (DCCA) para calcular expoentes de escala de autocorrelações e correlações cruzadas entre as séries analisadas. Os resultados mostraram que as séries de volatilidade apresentam persistência mais forte do que as séries de retornos que apresentaram dois regimes de invariância de escala com correlações antipersistentes nas escalas maiores. As correlações cruzadas entre as séries de retornos também apresentaram dois regimes de escala com expoentes semelhantes as séries de retornos da variedade Tommy. Os valores do coeficiente de correlação obtidos pelo método Detrended Cross Correlation Coefficient mostraram que para ambas, retornos e volatilidade, as correlações entre as séries são positivas, aumentam com escala temporal e são mais fortes para as séries de retornos.

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Higher-Order Multifractal Detrended Partial Cross-Correlation Analysis for the Correlation Estimator

Complexity ◽

10.1155/2020/7495058 ◽

2020 ◽

Vol 2020 ◽

pp. 1-10

Author(s):

Keqiang Dong ◽

Xiaojie Gao

Keyword(s):

Time Series ◽

Correlation Analysis ◽

Correlation Coefficient ◽

Nonlinear Interaction ◽

Cross Correlation ◽

Nonstationary Time Series ◽

New Method ◽

Nonlinear Interactions ◽

Cross Correlation Analysis ◽

The Cross

In this paper, we develop a new method to measure the nonlinear interactions between nonstationary time series based on the detrended cross-correlation coefficient analysis. We describe how a nonlinear interaction may be obtained by eliminating the influence of other variables on two simultaneous time series. By applying two artificially generated signals, we show that the new method is working reliably for determining the cross-correlation behavior of two signals. We also illustrate the application of this method in finance and aeroengine systems. These analyses suggest that the proposed measure, derived from the detrended cross-correlation coefficient analysis, may be used to remove the influence of other variables on the cross-correlation between two simultaneous time series.

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Correlações em séries temporais de preços de frango, soja e milho

Research Society and Development ◽

10.33448/rsd-v10i4.14019 ◽

2021 ◽

Vol 10 (4) ◽

pp. e20610414019

Author(s):

Ruben Vivaldi Silva Pessoa ◽

Ikaro Daniel de Carvalho Barreto ◽

Lidiane da Silva Araújo ◽

Guilherme Rocha Moreira ◽

Tatijana Stosic ◽

...

Keyword(s):

Correlation Analysis ◽

Correlation Coefficient ◽

Detrended Fluctuation Analysis ◽

Cross Correlation ◽

Sao Paulo ◽

Fluctuation Analysis ◽

São Paulo ◽

Cross Correlation Analysis ◽

Detrended Fluctuation

A evolução do mercado agrícola brasileiro alterou o processo de produção, exportação e consumo de commodities alimentares. Com isso, novos estudos acerca da relação entre o mercado de alimentos e outros mercados foram desenvolvidos, buscando explicar a ligação entre os preços de commodities agrícolas e não agrícolas. Visando contribuir para esse estudo, foram investigadas as correlações de longo prazo entre os preços de commodities agrícolas brasileiras, utilizando técnicas de Econofísica. Analisaram-se então as séries diárias de preços e retorno de preços da carne de frango, soja e milho, registrados entre 02/08/2004 e 16/06/2017 pelo Centro de Estudos Avançados em Economia Aplicada / Escola Superior de Agricultura Luiz de Queiroz / Universidade de São Paulo - CEPEA/ESALQ/USP. As correlações entre as séries temporais foram investigadas utilizando os métodos Detrended Fluctuation Analysis (DFA) e Detrended Cross Correlation Analysis (DCCA), para calcular o Detrended Cross Correlation Coefficient (DCCA Coefficient), que serve para quantificar correlações de longo prazo entre séries temporais não estacionárias. Os resultados obtidos apontam para a ausência de correlações nas escalas de até 30 dias e, para escalas maiores, acusam correlações mais fortes entre os preços de frango e milho que entre os preços de frango e soja. Após a crise alimentar de 2008, entretanto, as correlações entre as séries diárias de retorno de preços do frango e do milho diminuíram, enquanto que, entre as de frango e soja, aumentaram nas escalas menores e diminuíram nas escalas maiores.

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Multifractal Fluctuation Analysis of Correlations Between the Sector Stock Markets in China and the US

Fluctuation and Noise Letters ◽

10.1142/s0219477521500310 ◽

2020 ◽

pp. 2150031

Author(s):

You-Shuai Feng ◽

Hong-Yong Wang

Keyword(s):

Correlation Analysis ◽

Stock Markets ◽

Cross Correlation ◽

Rapid Development ◽

Fluctuation Analysis ◽

Cross Correlation Analysis ◽

The Us ◽

Cross Correlations ◽

The Cross ◽

Stock Indexes

With the rapid development of economic globalization, the stock markets in China and the US are increasingly linked. The fluctuation features and cross-correlations of the two countries’ markets have attracted extensive attention from market investors and researchers. In this paper, the fractal analysis methods including multifractal asymmetric detrended cross-correlation analysis (MF-ADCCA) and coupled detrended cross-correlation analysis (CDCCA) are applied to explore the volatilities of CSI300 and SP500 sector stock indexes as well as the cross-correlations and coupling cross-correlations between the two corresponding sector stock indexes. The results show that the auto-correlations, cross-correlations and coupling cross-correlations have multifractal fluctuation characteristics, and that the cross-correlations are asymmetric. Additionally, the coupling cross-correlation strengths are distinct due to the different influence of long-range correlations and fat-tailed distribution. Further, the co-movement between China and the US sector stock markets is susceptible to external market factors such as major economic events and national policies.

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