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A fast, accurate method for value-at-risk and expected shortfall

Krause, Jochen; Paolella, Marc S. - In: Econometrics : open access journal 2 (2014) 2, pp. 98-122

exhibiting leptokurtosis, asymmetry and conditional heteroskedasticity. It is based on a GARCH-type process driven by noncentral …

Persistent link: https://www.econbiz.de/10010429763

Forecasting the volatility of S&P depositary receipts using GARCH-type models under intraday range-based and return-based proxy measures

Liu, Hung-Chun; Chiang, Shu-mei; Cheng, Nick Ying-pin - In: International review of economics & finance : IREF 22 (2012) 1, pp. 78-91

Persistent link: https://www.econbiz.de/10009618705

Selection criteria in regime switching conditional volatility models

Chuffart, Thomas - In: Econometrics : open access journal 3 (2015) 2, pp. 289-316

Smooth Transition GARCH and the Markov-Switching GARCH models. Simulation experiments reveal that information criteria and …

Persistent link: https://www.econbiz.de/10011297653

Alright : asymmetric LaRge-scale (I)GARCH with Hetero-Tails

Paolella, Marc S.; Polak, Pawel - In: International review of economics & finance : IREF 40 (2015), pp. 282-297

Persistent link: https://www.econbiz.de/10011573592

Generalized fractional processes with long memory and time dependent volatility revisited

Peiris, M. Shelton; Asai, Manabu - In: Econometrics : open access journal 4 (2016) 3, pp. 1-21

follow GARCH and stochastic volatility (SV). Under certain regularity conditions, we give asymptotic results for the … approximate maximum likelihood estimator for the GARMA-GARCH model. We discuss a Monte Carlo likelihood method for the GARMA …

Persistent link: https://www.econbiz.de/10011568296

Copula-based vMEM specifications versus alternatives : the case of trading activity

Cipollini, Fabrizio; Engle, Robert F.; Gallo, Giampiero M. - In: Econometrics : open access journal 5 (2017) 2, pp. 1-24

We discuss several multivariate extensions of the Multiplicative Error Model to take into account dynamic interdependence and contemporaneously correlated innovations (vector MEM or vMEM). We suggest copula functions to link Gamma marginals of the innovations, in a specification where past...

Persistent link: https://www.econbiz.de/10011654447

Measuring risk spillovers from multiple developed stock markets to China : a vine-copula-GARCH-MIDAS model

Jiang, Cuixia; Li, Yuqian; Xu, Qifa; Liu, Yezheng - In: International review of economics & finance : IREF 75 (2021), pp. 386-398

Persistent link: https://www.econbiz.de/10012692552

The economic sources of China's CSI 300 spot and futures volatilities before and after the 2015 stock market crisis

Chen, Qiang; Gong, Yuting - In: International review of economics & finance : IREF 64 (2019), pp. 102-121

Persistent link: https://www.econbiz.de/10012322288

Volatility forecasting of crude oil market : can the regime switching GARCH model beat the single-regime GARCH models?

Zhang, Yue-jun; Yao, Ting; He, Ling-yun; Ripple, Ronald D. - In: International review of economics & finance : IREF 59 (2019), pp. 302-317

Persistent link: https://www.econbiz.de/10012202881

Co-movements among major European exchange rates : a multivariate time-varying asymmetric approach

Tamakoshi, Go; Hamori, Shigeyuki - In: International review of economics & finance : IREF 31 (2014), pp. 105-113

Persistent link: https://www.econbiz.de/10010490436