Results 101 to 110 of about 51,403 (193)

Modeling Nonstationary Financial Volatility with the R Package tvgarch

Journal of Statistical Software
Certain events can make the structure of volatility of financial returns to change, making it nonstationary. Models of time-varying conditional variance such as generalized autoregressive conditional heteroscedasticity (GARCH) models usually assume ...
Susana Campos-Martins, Genaro Sucarrat
doaj   +1 more source

Some Exact Formulae for the Constant Correlation and Diagonal M - Garch Models [PDF]

The purpose of this paper is to examine the covariance structure of multivariate GARCH (M-GARCH) models that have been introduced in the literature the last fifteen years, and have been greatly favoured by time series analysts and econometricians.
Menelaos Karanasos
core  

Volatility models with innovations from new maximum entropy densities at work [PDF]

Generalized autoregressive conditional heteroskedasticity (GARCH) processes have become very popular as models for financial return data because they are able to capture volatility clustering as well as leptokurtic unconditional distributions which ...
Fischer, Matthias J., Gao, Yang, Herrmann, Klaus   +2 more
core  

Contemporaneous Aggregation of GARCH Processes [PDF]

We study the impact of large cross-sections of contemporaneous aggregation of GARCH processes and of dynamic GARCH factor models. The results crucially depend on the shape of the cross-sectional distribution of the GARCH coefficients and on the cross ...
Paolo Zaffaroni
core  

Hilbertian GARCH MODELS

, 2012
Strongly second order Generalized Autoregressive Conditional Heteroscedastic models with values in separable Hilbert spaces (HGARCH, in brief) are introduced. Necessary and sufficient conditions for the existence of these models are given. Tensor analysis for Hilbert-Schmidt operators, and conditional expectation operatorial calculus for Hilbert space ...
Reza Soltani, Ahmad, Shishebor, Zohreh, Sajjadnia, Zahra   +2 more
openaire   +1 more source

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

Modelling Asymmetric Sovereign Bond Yield Volatility with Univariate GARCH Models: Evidence from India

, 2023
M LB, Chakraborty S, Iyer V, N NM, Ledwani S.   +4 more
europepmc   +1 more source

Estimating the volatility of cryptocurrencies during bearish markets by employing GARCH models. [PDF]

Heliyon, 2019
Kyriazis ΝA, Daskalou K, Arampatzis M, Prassa P, Papaioannou E.   +4 more
europepmc   +1 more source

A Multivariate Perspective for Modeling and Forecasting Inflation's Conditional Mean and Variance [PDF]

We test the importance of multivariate information for modelling and forecasting in- flation's conditional mean and variance. In the literature, the existence of inflation's conditional heteroskedasticity has been debated for years, as it seemed to ...
Marco Capasso, Matteo Barigozzi
core  

Asymmetries and Volatility Regimes in the European Equity Markets [PDF]

This paper provides and empirical examination of four European equity indices between 1991 and 2005. We investigate the ability of fifteen different GARCH models to capture the characteristics of historical daily returns effectively and generate ...
Carol Alexandra, Emese Lazar
core