GARCH models with Markov-switching regimes are often used for volatility analysis of …nancial time series. Such models imply less persistence in the conditional variance than the standard GARCH model, and potentially provide a signi…cant improvement in volatility forecast. Nevertheless, conditions for asymptotic wide-sense stationarity have been derived only for some degenerated models. In this...

This paper contains a survey of univariate models of conditional heteroskedasticity. The classical ARCH model is mentioned, and various extensions of the standard Generalized ARCH model are highlighted. This includes the Exponential GARCH model. Stochastic volatility models remain outside this review.

ARCH and GARCH models are widely used to model financial market volatilities in risk management applications. Considering a GARCH model with heavy-tailed innovations, we characterize the limiting distribution of an estimator of the conditional Value-at-Risk (VaR), which corresponds to the extremal quantile of the conditional distribution of the GARCH process. We propose two methods, the normal ...

We study the sample autocovariance and autocorrelation function of the stationary AR(1) process with ARCH(1) errors. In contrast to ARCH and GARCH processes, AR(1) processes with ARCH(1) errors can not be transformed into solutions of linear stochastic recurrence equations. However, we show that they still belong to the class of stationary sequences with regular varying nite-dimensional distrib...

Data finansial yang mengikuti deret waktu memiliki keragaman atau volatilitas setiap waktunya tidak konstan. Keadaan ini disebut sebagai heteroskedastisitas. Metode dapat menyelesaikan masalah tersebut adalah Autoregressive Conditional Heteroscedasticity (ARCH)/Generalized (GARCH). Namun, ARCH/GARCH mengatasi beberapa kasus seperti perbedaan dalam nilai leverage effect. Sehingga dilakukan pemod...

This paper contains a survey of univariate models of conditional heteroskedasticity. The classical ARCH model is mentioned, and various extensions of the standard Generalized ARCH model are highlighted. This includes the Exponential GARCH model. Stochastic volatility models remain outside this review.

We develop a misspecification test for the multiplicative two-component GARCHMIDAS model suggested in Engle et al. (2013). In the GARCH-MIDAS model a short-term unit variance GARCH component fluctuates around a smoothly timevarying long-term component which is driven by the dynamics of a macroeconomic explanatory variable. We suggest a Lagrange Multiplier statistic for testing the null hypothes...

Inflasi telah menjadi bagian penting masalah perekonomian pada setiap negara, termasuk Indonesia. Kestabilan inflasi merupakan suatu hal yang karena rendah dan stabil prasyarat bagi pertumbuhan ekonomi sehingga memberikan manfaat peningkatan kesejahteraan masyarakat. Penelitian ini menggunakan metode ARCH/GARCH dalam memodelkan laju periode bulanan di Indonesia selama Januari 1979 sampai April ...

The purpose of this research was to examine the dynamics volatility spillover between energy and environmental, social, sustainable indices. COVID19 prompted select April 2019 March 2022 as a sample period, respective data (Daily Prices) Nifty Energy ESG indices were obtained from National Stock Exchange India Limited. outcomes study confirmed that daily returns 100 not normally distributed rea...

GARCH-type models have been highly developed since Engle [1982] presented ARCH process 30 years ago. Different kinds of GARCH-type models are applicable to different kinds of research purposes. As documented by many literatures that short-memory processes with level shifts will exhibit properties that make standard tools conclude long-memory is present. Therefore, in this paper, we want to fore...