SUBGEOMETRICALLY ERGODIC AUTOREGRESSIONS WITH AUTOREGRESSIVE CONDITIONAL HETEROSKEDASTICITY [PDF]
Econometric Theory, 2023 In this paper, we consider subgeometric (specifically, polynomial) ergodicity of univariate nonlinear autoregressions with autoregressive conditional heteroskedasticity (ARCH). The notion of subgeometric ergodicity was introduced in the Markov chain literature in the 1980s, and it means that the transition probability measures converge to the ...
Mika Meitz, Pentti Saikkonen
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Chaos, Fractionality, Nonlinear Contagion, and Causality Dynamics of the Metaverse, Energy Consumption, and Environmental Pollution: Markov-Switching Generalized Autoregressive Conditional Heteroskedasticity Copula and Causality Methods [PDF]
Fractal and FractionalMetaverse (MV) technology introduces new tools for users each day. MV companies have a significant share in the total stock markets today, and their size is increasing.
Melike Bildirici +2 more
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Neural Generalised AutoRegressive Conditional Heteroskedasticity [PDF]
, 2022 We propose Neural GARCH, a class of methods to model conditional heteroskedasticity in financial time series. Neural GARCH is a neural network adaptation of the GARCH 1,1 model in the univariate case, and the diagonal BEKK 1,1 model in the multivariate case.
Zexuan Yin, Paolo Barucca
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Spatial Autoregressive Conditional Heteroskedasticity Models
JOURNAL OF THE JAPAN STATISTICAL SOCIETY, 2017 Summary: This study proposes a spatial extension of time series autoregressive conditional heteroskedasticity (ARCH) models to those for areal data. We call the spatially extended ARCH models as spatial ARCH (S-ARCH) models. S-ARCH models specify conditional variances given surrounding observations, which constitutes a good contrast with time series ...
Takaki Sato, Yasumasa Matsuda
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Modelling time-varying volatility using GARCH models: evidence from the Indian stock market [version 2; peer review: 2 approved] [PDF]
F1000Research, 2022 Background: In this study, we examined the volatility of the Indian stock market from 2008 to 2021. Owing to the financial crisis, volatility forecasting of the Indian stock market has become crucial for economic and financial analysts.
Tarunpreet Kaur +3 more
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Testing and modelling autoregressive conditional heteroskedasticity of streamflow processes [PDF]
Nonlinear Processes in Geophysics, 2005 Conventional streamflow models operate under the assumption of constant variance or season-dependent variances (e.g. ARMA (AutoRegressive Moving Average) models for deseasonalized streamflow series and PARMA (Periodic AutoRegressive Moving Average ...
W. Wang +4 more
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Chaos in Fractionally Integrated Generalized Autoregressive Conditional\n Heteroskedastic Processes [PDF]
, 2016 Fractionally integrated generalized autoregressive conditional heteroskedasticity (FIGARCH) arises in modeling of financial time series. FIGARCH is essentially governed by a system of nonlinear stochastic difference equations ${u_t}$ = ${z_t}$ $(1-\sum\limits_{j=1}^q _j L^j) _{t}^2 = +(1-\sum\limits_{j=1}^q _j L^j - (\sum\limits_{k=1}^p _k L^k)
Adil Yilmaz, Gazanfer Ünal
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Indonesian Journal on Computing (Indo-JC), 2018 Gold is a one of high selling value items in the market, and it can be used as an investment item. The price of gold in the market tends to be stable and not undergoing too significant changes which makes gold be a very valuable item. The aim of this research is to predict gold price using AR (1) and ARCH (1) model which are the part of time series ...
Ni Luh Ketut Dwi Murniati +2 more
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Detecting Autoregressive Conditional Heteroskedasticity in Non-Gaussian Time Series
SSRN Electronic Journal, 2004 In economic time series conditional heteroskedasticity and conditional non-normality may occur simultaneously. Well known examples include time series of financial returns. The present paper examines a new test for (generalized) autoregressive conditional heteroskedasticity in Monte Carlo experiments with normal, fat-tailed and/or skewed conditional ...
Burkhard Raunig
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Investigating the Impact of International Sanctions on Performance Indicators of Tehran Stock Exchange with Industries Divided From 2010 to 2020 [PDF]
مدلسازی اقتصادسنجی, 2023 In this research, the impact of the impact of the international sanctions index on the performance indices of the Tehran Stock Exchange by industries, including mass production indices, banks, insurance, automobiles, investments, basic metals, rubber ...
Hamid Reza Vaezian +3 more
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