In this paper we test for (Generalized) AutoRegressive Conditional Heteroskedasticity [(G)ARCH] in daily data on 22 exchange rates and 13 stock market indices using the standard Lagrange Multiplier [LM] test for GARCH and a LM test that is resistant to patches of additive outliers. The data span two samples of 5 years ranging from 1986 to 1995. Using asymptotic arguments and Monte Carlo simulat...

It is shown empirically that mixed autoregressive moving average regression models with generalized autoregressive conditional heteroskedasticity (Reg-ARMA-GARCH models) can have multimodality in the likelihood that is caused by a dummy variable in the conditional mean. Maximum likelihood estimates at the local and global modes are investigated and turn out to be qualitatively different, leadin...

The Composite Stock Price Index (IHSG) is a value that describes the combined performance of all shares listed on Indonesia Exchange. JCI serves as benchmark for investors in investing. method used to predict future conditions based past data forecasting . Autoregressive Integrated Moving Average with Exogenous Variables (ARIMAX) amodel time series can be forecasting. Financial has high volatil...

We present a volatility forecasting comparative study within the autoregressive conditional heteroskedasticity (ARCH) class of models. Our goal is to identify successful predictive models over multiple horizons and to investigate how predictive ability is influenced by choices for estimation window length, innovation distribution, and frequency of parameter reestimation. Test assets include a r...

Abstract For large multivariate models of generalized autoregressive conditional heteroskedasticity (GARCH), it is important to reduce the number parameters cope with ‘curse dimensionality’. Recently, Laurent, Rombouts and Violante (2014 “Multivariate Rotated ARCH Models” Journal Econometrics 179 : 16–30) developed rotated GARCH model, which focuses on for standardized variables. This paper ext...

in this paper various arch models and relevant news impact curves including a partially nonparametric (pnp) one are compared and estimated with daily iran stock return data. diagnostic tests imply the asymmetry of the volatility response to news. the egarch model, which passes all the tests and appears relatively matching with the asymmetry in the data, seems to be the most adequate characteriz...

We consider a time series model with autoregressive conditional heteroskedasticity that is subject to changes in regime. The regimes evolve according to a multistate latent Markov switching process with unknown transition probabilities, and it is the constant in the variance process of the innovations that is subject to regime shifts. The joint estimation of the latent process and all model par...