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A general framework for spatial GARCH models
In time-series analysis, particularly in finance, generalized autoregressive conditional heteroscedasticity (GARCH) models are widely applied...
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Volatility forecasting using deep recurrent neural networks as GARCH models
Estimating and predicting volatility in time series is of great importance in different areas where it is required to quantify risk based on...
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Bayesian inference of multivariate-GARCH-BEKK models
The main aim of this paper is to present a Bayesian analysis of Multivariate GARCH( l , m ) (M-GARCH) models including estimation of the coefficient...
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ARCH and GARCH Models
In finance data one often observes so-called volatility clustering, i.e. periods with relatively high volatility and periods with low volatility...
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M-Estimation in GARCH Models in the Absence of Higher-Order Moments
We consider a class of M-estimators of the parameters of a GARCH(p, q) model. These estimators are asymptotically normal, depending on score...
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A covariate-driven beta-binomial integer-valued GARCH model for bounded counts with an application
This paper considers the modeling problem of the weekly number of districts with new cases of cryptosporidiosis infection, and proposes a...
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Multiple Measures Realized GARCH Models
Realized volatility has become the most popular empirical measure in fitting and forecasting volatility. However, as the properties of this class of...
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Test for conditional quantile change in GARCH models
In this study, we consider the problem of detecting a change point in the conditional quantile of GARCH models. The task is essential in risk...
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Capturing Measurement Error Bias in Volatility Forecasting by Realized GARCH Models
This paper proposes generalisations of the Realized GARCH model, in three different directions. First, heteroskedasticity of the noise term in the...
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Bayesian GARCH modeling of functional sports data
The use of statistical methods in sport analytics has gained a rapidly growing interest over the last decade, and nowadays is common practice. In...
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M-Estimate for the stationary hyperbolic GARCH models
In this manuscrit, we propose two classes of M-estimates for the hyperbolic GARCH models. The first class called M-estimate is defined by minimizing...
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Portmanteau test for the asymmetric power GARCH model when the power is unknown
It is now widely accepted that, to model the dynamics of daily financial returns, volatility models have to incorporate the so-called leverage...
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A new class of integer-valued GARCH models for time series of bounded counts with extra-binomial variation
This article considers a modeling problem of integer-valued time series of bounded counts in which the binomial index of dispersion of the...
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Bayesian inference of multiple structural change models with asymmetric GARCH errors
Structural change in any time series is practically unavoidable, and thus correctly detecting breakpoints plays a pivotal role in statistical...
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Bayesian log-linear beta-negative binomial integer-valued Garch model
When dealing with time series with outlying and atypical data, a commonly used approach is to develop models based on heavy-tailed distributions. The...
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Bayesian inference of nonlinear hysteretic integer-valued GARCH models for disease counts
This study proposes a class of nonlinear hysteretic integer-valued GARCH models in order to describe the occurrence of weekly dengue hemorrhagic...
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Statistical inference for mixture GARCH models with financial application
In this paper we consider mixture generalized autoregressive conditional heteroskedastic models, and propose a new iteration algorithm of type EM for...
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Data driven value-at-risk forecasting using a SVR-GARCH-KDE hybrid
Appropriate risk management is crucial to ensure the competitiveness of financial institutions and the stability of the economy. One widely used...
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Specification procedures for multivariate stable-Paretian laws for independent and for conditionally heteroskedastic data
We consider goodness-of-fit methods for multivariate symmetric and asymmetric stable Paretian random vectors in arbitrary dimension. The methods are...
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A Semi-Markov Approach to Financial Modelling During the COVID-19 Pandemic
We assess the capabilities of the weighted-indexed semi-Markov chain (WISMC) model applied to high-frequency financial data during the COVID-19...