Estimation of large financial volatility models is plagued by the curse of dimensionality: As the dimension grows, joint estimation of the parameters becomes infeasible in practice. This problem is compounded if covariates or conditioning variables (``X") are added to each volatility equation. In particular, the problem is especially acute for non-exponential volatility models (e.g. GARCH models), since there the variables and parameters are restricted to be positive. Here, we propose an estimator for a multivariate log-GARCH-X model that avoids these problems. The model allows for feedback among the equations, admits several stationary regressors as conditioning variables in the X-part (including leverage terms), and allows for time-varyin...
This paper provides a probabilistic and statistical comparison of the log-GARCH and EGARCH models, w...
Generalized autoregressive conditional heteroscedasticity (GARCH) models are widely used in financia...
Exponential models of Autoregressive Conditional Heteroscedasticity (ARCH) enable richer dynamics (e...
Estimation of large financial volatility models is plagued by the curse of dimensionality: As the di...
A new approach is proposed to estimate a large class of multivariate volatility models. The method ...
Exponential models of Autoregressive Conditional Heteroscedasticity (ARCH) enable richer dynamics (e...
This paper studies the probabilistic properties and the estimation of the asymmetric log-GARCH($p,q...
The asymptotic distribution of the Gaussian quasi-maximum likelihood estimator (QMLE) is obtained fo...
Many economic and financial time series exhibit time-varying volatility. GARCH models are tools for ...
Recently, volatility modeling has been a very active and extensive research area in empirical financ...
The importance of modelling comovements of financial returns is well established in the literature. ...
<div><p>This article investigates the asymptotic properties of the Gaussian quasi-maximum-likelihood...
It is now widely accepted that volatility models have to incorporate the so-called leverage effect i...
A general framework for the estimation and inference in univariate and multivariate Generalised log-...
Exponential models of Autoregressive Conditional Heteroscedasticity (ARCH) enable richer dynamics (e...
This paper provides a probabilistic and statistical comparison of the log-GARCH and EGARCH models, w...
Generalized autoregressive conditional heteroscedasticity (GARCH) models are widely used in financia...
Exponential models of Autoregressive Conditional Heteroscedasticity (ARCH) enable richer dynamics (e...
Estimation of large financial volatility models is plagued by the curse of dimensionality: As the di...
A new approach is proposed to estimate a large class of multivariate volatility models. The method ...
Exponential models of Autoregressive Conditional Heteroscedasticity (ARCH) enable richer dynamics (e...
This paper studies the probabilistic properties and the estimation of the asymmetric log-GARCH($p,q...
The asymptotic distribution of the Gaussian quasi-maximum likelihood estimator (QMLE) is obtained fo...
Many economic and financial time series exhibit time-varying volatility. GARCH models are tools for ...
Recently, volatility modeling has been a very active and extensive research area in empirical financ...
The importance of modelling comovements of financial returns is well established in the literature. ...
<div><p>This article investigates the asymptotic properties of the Gaussian quasi-maximum-likelihood...
It is now widely accepted that volatility models have to incorporate the so-called leverage effect i...
A general framework for the estimation and inference in univariate and multivariate Generalised log-...
Exponential models of Autoregressive Conditional Heteroscedasticity (ARCH) enable richer dynamics (e...
This paper provides a probabilistic and statistical comparison of the log-GARCH and EGARCH models, w...
Generalized autoregressive conditional heteroscedasticity (GARCH) models are widely used in financia...
Exponential models of Autoregressive Conditional Heteroscedasticity (ARCH) enable richer dynamics (e...