Multivariate dynamic intensity peaks‐over‐threshold models
نویسندگان
چکیده
منابع مشابه
Aggregation analysis in empirical multivariate dynamic models*
The paper analyses the aggregation problem when the micro relations consist of multivariate specifications. We focus on a generalization of the model selection criterion proposed in the previous literature for discriminating between aggregate and disaggregate models. In addition, we extend the model selection problem in forecasting aggregate variables out of sample. Both the stationary and coin...
متن کاملDynamic Correlations in Symmetric Multivariate SV Models
This paper proposes two types of stochastic correlation structures for Multivariate Stochastic Volatility (MSV) models, namely the constant correlation (CC) MSV and dynamic correlation (DC) MSV models, from which the stochastic covariance structures could be obtained easily. Both structures can be used for purposes of optimal portfolio and risk management, and for calculating Value-at-Risk (VaR...
متن کاملVariance estimation for multivariate normal dynamic linear models
In multivariate normal dynamic and state-space linear models the observational variance matrix is usually assumed known. Apart from a handful of special cases, estimation procedures that allow for the variance of the observational errors to be left unspecified are not widely available. The foundation of this paper is the general multivariate normal dynamic linear model with unknown but fixed ob...
متن کاملBayes Linear Covariance Matrix Adjustment for Multivariate Dynamic Linear Models
A methodology is developed for the Bayes linear adjustment of the covariance matrices underlying a multivariate constant time series dynamic linear model. The covariance matrices are embedded in a distribution-free inner-product space of matrix objects which facilitates such adjustment. This approach helps to make the analysis simple, tractable and robust. To illustrate the methods, a simple mo...
متن کاملMultivariate Stochastic Volatility with Bayesian Dynamic Linear Models
This paper develops a Bayesian procedure for estimation and forecasting of the volatility of multivariate time series. The foundation of this work is the matrix-variate dynamic linear model, for the volatility of which we adopt a multiplicative stochastic evolution, using Wishart and singular multivariate beta distributions. A diagonal matrix of discount factors is employed in order to discount...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Applied Econometrics
سال: 2019
ISSN: 0883-7252,1099-1255
DOI: 10.1002/jae.2741