The aim of this study is to examine the daily return spillover among 18 cryptocurrencies under low and high volatility regimes,while considering three pricing factors and the effect of the COVID-19 outbreak.To do so,w...The aim of this study is to examine the daily return spillover among 18 cryptocurrencies under low and high volatility regimes,while considering three pricing factors and the effect of the COVID-19 outbreak.To do so,we apply a Markov regime-switching(MS)vector autoregressive with exogenous variables(VARX)model to a daily dataset from 25-July-2016 to 1-April-2020.The results indicate various patterns of spillover in high and low volatility regimes,especially during the COVID-19 outbreak.The total spillover index varies with time and abruptly intensifies following the outbreak of COVID-19,especially in the high volatility regime.Notably,the network analysis reveals further evidence of much higher spillovers in the high volatility regime during the COVID-19 outbreak,which is consistent with the notion of contagion during stress periods.展开更多
This paper primarily analyzes the evolution path of China＇s pork price by employing the threshold autoregression model（TAR）. Considering the unit root test with a threshold effect and heteroskedasticity of the TAR ...This paper primarily analyzes the evolution path of China＇s pork price by employing the threshold autoregression model（TAR）. Considering the unit root test with a threshold effect and heteroskedasticity of the TAR model, we show that the pork price series is a unit root process in each regime, and the heteroskedasticity in the TAR model greatly affects the results of linearity test. We find that the changing process of pork price has two regimes： mild regime and expansion regime. In particular, a change belongs to an expansion regime if it is larger than 0.5881; otherwise, it falls in the mild regime.展开更多
基金The fourth author acknowledges that the Deanship of Scientific Research(DSR)at King Abdulaziz University,Jeddah,Saudi Arabia funded this project,under Grant No.(FP-71-42)The third author acknowledges the support of the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea(NRF-2020S1A5B8103268).
文摘The aim of this study is to examine the daily return spillover among 18 cryptocurrencies under low and high volatility regimes,while considering three pricing factors and the effect of the COVID-19 outbreak.To do so,we apply a Markov regime-switching(MS)vector autoregressive with exogenous variables(VARX)model to a daily dataset from 25-July-2016 to 1-April-2020.The results indicate various patterns of spillover in high and low volatility regimes,especially during the COVID-19 outbreak.The total spillover index varies with time and abruptly intensifies following the outbreak of COVID-19,especially in the high volatility regime.Notably,the network analysis reveals further evidence of much higher spillovers in the high volatility regime during the COVID-19 outbreak,which is consistent with the notion of contagion during stress periods.
基金supported by the Fundamental Research Funds for the Central Universities and the Research Funds of Renmin University,China(12XNK015)
文摘This paper primarily analyzes the evolution path of China＇s pork price by employing the threshold autoregression model（TAR）. Considering the unit root test with a threshold effect and heteroskedasticity of the TAR model, we show that the pork price series is a unit root process in each regime, and the heteroskedasticity in the TAR model greatly affects the results of linearity test. We find that the changing process of pork price has two regimes： mild regime and expansion regime. In particular, a change belongs to an expansion regime if it is larger than 0.5881; otherwise, it falls in the mild regime.
