Threshold autoregression analysis for finite-range time series of counts with an application on measles data

2017 ◽  
Vol 88 (3) ◽  
pp. 597-614 ◽  
Author(s):  
Kai Yang ◽  
Dehui Wang ◽  
Han Li
Keyword(s):  
Time Series ◽  
Finite Range ◽  
Time Series Of Counts ◽  
Threshold Autoregression

Extreme Overdispersion and Persistence in Time-Series of Counts

2020 ◽  
Author(s):  
Leopoldo Catania ◽  
Eduardo Rossi ◽  
Paolo Santucci de Magistris
Keyword(s):  
Time Series ◽  
Time Series Of Counts

scholarly journals Dissecting Tether’s Nonlinear Dynamics during Covid-19

2020 ◽  
Vol 6 (4) ◽  
pp. 161
Author(s):  
Moinak Maiti ◽  
Zoran Grubisic ◽  
Darko B. Vukovic
Keyword(s):  
Time Series ◽  
Regime Switching ◽  
Return Time ◽  
The Other ◽  
Smooth Transition ◽  
Daily Average ◽  
Star Models ◽  
Average Return ◽  
Threshold Autoregression ◽  
Highly Nonlinear

The present study is on the five cryptocurrency daily mean return time series linearity dynamics during the Covid-19 period. These cryptocurrencies were chosen based on their influence on the market, primarily driven by its market capitalisation. Tether is included as the most important stable coin on the market, nominally pegged to the U.S. dollar (USD). The reason to investigate it is that there are some inconsistencies in its behaviour as opposed to the other four cryptocurrencies. This study found that the behaviour of Tether cryptocurrency daily average return time series pattern is highly nonlinear and chaotic in nature, whereas the other four cryptocurrencies (namely Bitcoin, Ethereum, XRP and Bitcoin Cash) daily average return time series were found to be linear in nature. To further study Tether’s nonlinear time series rich dynamics, this study deployed one category of the regime switching models popularly known as the threshold regressions. The study estimates fairly suggest that both the threshold autoregression (TAR) and smooth transition autoregressive (STAR) models with lag 1 are adequate to capture the rich nonlinear and chaotic dynamics of Tether’s daily average return time series.

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