We estimate a model of common and commodity-specific, highand low-frequency factors, built on the spline-GARCH model of Engle and Rangel (2008) to explain the period of exceptionally high price volatility in commodity markets during 2006-2008. We find that decomposing realized volatility into highand low-frequency components reveals the impact of slowly-evolving macroeconomic variables on the p...

In the present study, it was explored how volatility of carbon neutrality concept index (CNCI) affected by China economic policy uncertainty (CEPU) index, climate (CPU) and geopolitical risk (GPR) index. According to research Amendola et al. GARCH-MIDAS model improved introducing realized kernel stock market into short-term component. On this basis, GARCH-RKV-MIDAS constructed. Meanwhile, both ...

This paper proposes a model for realized variance that exploits information in quarticity. The and quarticity measures are both highly persistent correlated with each other. proposed incorporates from the observed process via autoregressive conditional dynamics. It dependence higher order (fourth) moments analogy to class of GARCH models exploit second moments.

This paper focuses on modeling foreign exchange return behavior that would result in more accurate currency options pricing. These alternative approaches namely, implied volatility model (IVM), realized volatility model (RVM) and GARCH (1,1) volatility model (GVM) are used in this study. The results, in general suggest that RVM outperforms both IVM and GVM in pricing currency options. In-sample...

Free AccessImportant Keywordshttps://doi.org/10.14220/9783737013444.259SectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinkedInRedditEmail About Previous chapter Next FiguresReferencesRelatedDetails Download book coverOsnabrücker Studien zur Jüdischen und Christlichen Bibel.Volume 8 1st editionISBN: 978-3-8471-1344-7 eISBN: 978-3-7370-1344-4Hi...

We propose a simple class of semiparametric multivariate GARCH models, allowing for asymmetric volatilities and time-varying conditional correlations. Estimates for time-varying conditional correlations are constructed by means of a convex combination of estimates for averaged correlations (across all assets) and dynamic realized (historical) correlations. Our model is very parsimonious. Estima...

We propose a simple class of multivariate GARCH models, allowing for time-varying conditional correlations. Estimates for time-varying conditional correlations are constructed by means of a convex combination of averaged correlations (across all series) and dynamic realized (historical) correlations. Our model is very parsimonious. Estimation is computationally feasible in very large dimensions...

Smooth Transition Exponential Smoothing (STES) is a popular exponential smoothing method for volatility forecasting; whereby the success of STES model lies in choice transition variable. In this paper, three realized variance (RV), daily, weekly and monthly RV were used as variables methods to evaluate performance intraday data. While daily squared return noisy series, residual employed proxy a...

The augmented GARCH model is a unification of numerous extensions of the popular and widely used ARCH process. It was introduced by Duan and besides ordinary (linear) GARCH processes, it contains exponential GARCH, power GARCH, threshold GARCH, asymmetric GARCH, etc. In this paper, we study the probabilistic structure of augmented GARCH(1,1) sequences and the asymptotic distribution of various ...