scholarly journals Think Again: Volatility Asymmetry and Volatility Persistence

Author(s):  
Dirk G. Baur ◽  
Thomas Dimpfl
Author(s):  
Dirk G. Baur ◽  
Thomas Dimpfl

Abstract We use a leveraged quantile heterogeneous autoregressive model of realized volatility to illustrate that volatility persistence and the asymmetric “leverage” effect are high volatility phenomena. More specifically, we find that (i) low volatility is not persistent, but high volatility all the more, even featuring properties of explosive processes; and (ii) asymmetry of volatility is only a high volatility phenomenon and there is no asymmetry in low volatility regimes. Our results turn out to be robust to the choice of the realized variance estimator, in particular with respect to jumps. The analysis illustrates that quantile regression can provide information that is hidden in commonly used GARCH or realized volatility models. The quantile regression results can also be linked to the weak empirical evidence of the leverage effect and the volatility feedback effect.


2020 ◽  
Author(s):  
Christina Sklibosios Nikitopoulos ◽  
Alice Thomas ◽  
Jian-Xin Wang

2009 ◽  
Vol 12 (01) ◽  
pp. 63-85 ◽  
Author(s):  
Weihua Shi ◽  
Larry Eisenberg ◽  
Cheng-few Lee

Following Bollerslev et al. (2000), this study characterizes the high-frequency volatility of the Japanese Government Bond (JGB) futures on the Tokyo Stock Exchange (TSE) in terms of intraday calendar effects, announcement effects and volatility persistence effects. The results indicate that, unlike the case for the US Treasury bond futures, only four out of 21 scheduled macroeconomic announcements are found to have a significant impact on volatilities, and their instantaneous and daily influences are rather small. At both instantaneous and daily frequencies, volatility persistence effects have the largest influence on volatility, while macroeconomic announcements have only a negligible impact.


2013 ◽  
Vol 8 (1) ◽  
pp. 49-68 ◽  
Author(s):  
Elie I. Bouri

AbstractThis study applies a multivariate model to examine the dynamics of mean and volatility transmission between fine wine and crude oil prices using daily observations from January 2004 to December 2011. The results suggest that the crude oil mean determines the wine market. In each series, volatility persistence is high and significant; innovations in each market seem to include figures that are valuable to risk managers seeking to predict volatility in other markets. During the financial crisis of 2008, wine and oil conditional volatilities climbed but then returned to their overall pre-crisis levels. (JEL Classifications: G11, G15, Q14, Q40)


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