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 ...

We perform a comprehensive examination of the recursive, comparative predictive performance of a number of linear and non-linear models for UK stock and bond returns. We estimate Markov switching, threshold autoregressive (TAR), and smooth transition autoregressive (STR) regime switching models, and a range of linear specifications in addition to univariate models in which conditional heteroske...

Nowadays many researchers use GARCH models to generate volatility forecasts. However, it is well known that volatility persistence, as indicated by the sum of the two parameters G1 and A1[1], in GARCH models is usually too high. Since volatility forecasts in GARCH models are based on these two parameters, this may lead to poor volatility forecasts. It has long been argued that this high persist...

The onset of the COVID-19 pandemic has increased volatility in financial markets, motivating researchers to investigate its impact. Some use GARCH family models focus on long-memory persistence, while others Markov chain better identify structural breaks and regimes. However, no study addressed occurrence these two phenomena a unified framework. Since both are important features data, ignore on...

Since ARCH and GARCH models are presented, more and more authors are interested in the study of volatilities in financial markets with GARCH models. Method for estimating the coefficients of GARCH models is mainly the maximum likelihood estimation. Now we consider another method—MCMC method to substitute for maximum likelihood estimation method. Then we compare three GARCH models based on it. M...

This paper surveys the persian monetary crises due to economic sanctions and speculative attacks that leads to high inflation. Economic sanctions are associated with various forms of trade barriers and restriction on financial transactions. Among the most influential sanctions on Iran's oil export and central bank sanctions are noted that their Aims to reduce Iran's oil revenues and Devaluation...

Given that there is no consensus on the fact ESG portfolios are characterized by very high returns and low risks compared to conventional portfolios, this study aims empirically verify whether series of an portfolio less volatile than a benchmark market portfolio. To hypothesis, we used Markov-switching GARCH models in order model process daily “MSCI USA Select,” as well those “S&P 500,” during...

In this paper, we introduce a two−dimensional Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model for clutter modeling and anomaly detection. The one−dimensional GARCH model is widely used for modeling financial time series. Extending the one−dimensional GARCH model into two dimensions yields a novel clutter model which is capable of taking into account important characteris...