Results 131 to 140 of about 23,897 (230)

Multivariate Regime–Switching GARCH with an Application to International Stock Markets [PDF]

We develop a multivariate generalization of the Markov–switching GARCH model introduced by Haas, Mittnik, and Paolella (2004b) and derive its fourth–moment structure.
Markus Haas, Stefan Mittnik
core  

Variance Persistence in the Greater China Region: A Multivariate GARCH Approach

Lahore Journal of Economics
This paper utilizes three Multivariate General Autoregressive Conditional Heteroscedasticity (MGARCH) models to determine variance persistence in the Greater China region from 2009 to 2014.
John Francis Diaz, Peh Ying Qian, Genevieve Liao Tan   +2 more
doaj  

Estimation of temporally aggregated multivariate GARCH models [PDF]

This paper investigates the performance of quasi maximum likelihood (QML) and nonlinear least squares (NLS) estimation applied to temporally aggregated GARCH models.Since these are known to be only weak GARCH, the conditional variance of the aggregated ...
Hafner, C.M., Rombouts, J.V.K.
core   +1 more source

Dynamic Conditional Correlations for Asymmetric Processes [PDF]

The paper develops two Dynamic Conditional Correlation (DCC) models, namely the Wishart DCC (wDCC) model. The paper applies the wDCC approach to the exponential GARCH (EGARCH) and GJR models to propose asymmetric DCC models.
Manabu Asai, Michael McAleer
core  

Forecasting multivariate volatility in larger dimensions: some practical issues [PDF]

The importance of covariance modelling has long been recognised in the field of portfolio management and large dimensional multivariate problems are increasingly becoming the focus of research.
Adam E Clements, Annastiina Silvennoinen, Ayesha Scott   +2 more
core  

Multivariate Autocontours for Specification Testing in Multivariate GARCH Models* [PDF]

, 2010
Gloria Gonzalez-Rivera, Emre Yoldas
openaire   +1 more source

Forecasting with a Bivariate Hysteretic Time Series Model Incorporating Asymmetric Volatility and Dynamic Correlations. [PDF]

Entropy (Basel)
Than HT.
europepmc   +1 more source

A Neural Stochastic Volatility Model

, 2018
In this paper, we show that the recent integration of statistical models with deep recurrent neural networks provides a new way of formulating volatility (the degree of variation of time series) models that have been widely used in time series analysis ...
Luo, Rui, Wang, Jun, Xu, Xiaojun, Zhang, Weinan   +3 more
core   +1 more source

Cross-market volatility spillovers between China and the United States: A DCC-EGARCH-t-Copula framework with out-of-sample forecasting. [PDF]

PLoS One
Zeng J, Wu J.
europepmc   +1 more source