This paper estimates switching autoregressive conditional heteroskedasticity (SWARCH) time series models for weekly returns of nine Asian forward exchange rates. We find two regimes with different volatility levels, whereby each regime displays considerable persistence. Our analysis provides evidence that the knock-on effects from China’s currency forwards markets upon other Asian countries hav...

Most high-frequency asset returns exhibit seasonal volatility patterns. This article proposes a new class of models featuring periodicity in conditional heteroscedasticity explicitly designed to capture the repetitive seasonal time variation in the second-order moments. This new class of periodic autoregressive conditional heteroscedasticity, or P-ARCH, models is directly related to the class o...

This paper examines the price volatility in the silver spot (cash) market. A host of Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models are used to analyze and gain a better understanding of the volatility of silver prices. We find the TGARCH (1,1) model indicates that both positive and negative shocks do not have a significant effect on volatility in the silver spot marke...

It is meaningful and of certain theoretical value for the development economy through analyzing fluctuation rules international oil prices forecasting future trend prices. By composing autoregressive integrated moving average (ARIMA) model combination model-generalized conditional heteroskedasticity (ARIMA-GARCH) prices, study shows that ARIMA (1,1,0)-GARCH (1,1) more suitable short-term with h...

Although market interdependence would seem to be conceptually straightforward, being based on international fundamentals, there are no generally accepted testing strategies. This paper tests for the sensitivity of the empirical results reported in Veiga and McAleer (2004), who use the vector autoregressive moving average asymmetric generalised autoregressive conditional heteroskedasticity (VARM...

Following the unconventional gas revolution, the forecasting of natural gas prices has become increasingly important because the association of these prices with those of crude oil has weakened. With this as motivation, we propose some modified hybrid models in which various combinations of the wavelet approximation, detail components, autoregressive integrated moving average, generalized autor...

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This paper proposes a new parametric model adequacy test for possibly nonlinear time series models such as generalized autoregressive conditional heteroskedasticity (GARCH) and autoregressive conditional duration (ACD). We consider the correct specification of parametric conditional distributions, not only some particular conditional characteristics. Using the true parametric conditional distri...

The main purpose of this paper is to estimate the volatility in global fertilizer prices. The endogenous structural breakpoint unit root test and alternative volatility models, including the generalized autoregressive conditional heteroskedasticity (GARCH) model, Exponential GARCH (EGARCH) model, and GJR model are estimated for six global fertilizer prices and the crude oil price. Weekly data f...

This paper proposes a constrained nonlinear programming view of generalized autoregressive conditional heteroskedasticity (GARCH) volatility estimation models in financial econometrics. These models are usually presented to the reader as unconstrained optimization models with recursive terms in the literature, whereas they actually fall into the domain of nonconvex nonlinear programming. Our re...