We study the realized variance of sample minimum variance portfolios of arbitrarily high
dimension. We consider the use of covariance matrix estimators based on shrinkage and …

To comprehensively reflect the heteroscedasticity, nonlinear dependence and heavy-tailed
distributions of stock returns while reducing the huge cost of parameter estimation, we use …

Abstract Based on a General Dynamic Factor Model with infinite-dimensional factor space
and MGARCH volatility models, we develop new estimation and forecasting procedures for …

We develop portfolio optimization problems for a nonlife insurance company seeking to find
the minimum capital required that simultaneously satisfies solvency and portfolio …

Many financial decisions, such as portfolio allocation, risk management, option pricing and
hedge strategies, are based on forecasts of the conditional variances, covariances and …

The modern portfolio theory has been trying to determine how an investor might allocate
assets among the possible investments options. Since the seminal contribution provided by …

The main aim of this article is to investigate the accuracy of the Multivariate Generalized
Autoregressive Conditional Heteroskedasticity Model (M-GARCH) for the selection of the …

It is well known that every investment carries a risk associated, and depending on the type of
investment, it can be very risky; for instance, securities. However, Markowitz proposed a …

Many financial decisions such as portfolio allocation, risk management, option pricing and
hedge strategies are based on the forecast of the conditional variances, covariances and …

The main purpose of this paper is to consider the multivariate GARCH (MGARCH)
framework to model the volatility of a multivariate process exhibiting long-term dependence …