Many econometric and data-science applications require a reliable estimate of the
covariance matrix, such as Markowitz's portfolio selection. When the number of variables is …

Statistical and computational methods are being increasingly integrated into Decision
Support Systems to aid management and help with strategic decisions. Researchers need to …

The Hierarchical risk parity (HRP) approach of portfolio allocation, introduced by Lopez de
Prado (2016), applies graph theory and machine learning to build a diversified portfolio. Like …

Support vector regression is a promising method for time-series prediction, as it has good
generalisability and an overall stable behaviour. Recent studies have shown that it can …

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 …

Portfolio allocation is an important tool for portfolio managers and investors interested in
diversification as well as improvements in out-of-sample portfolio performance. Recently …

Markowitz optimization plays an important role in modern portfolio theory. However, it is well-
known that Markowitz optimization is highly affected by the estimation error of the mean …

When validating variance-covariance (VCV) estimators based on the ex-post volatility of the
global minimum variance (GMV) portfolio, we confirm the academic backing for considering …

Markowitz optimization plays a crucial role in modern portfolio theory. However, it is well
known that Markowitz optimization is highly affected by estimation errors in the mean vector …

Abstract Systems for decision-making assistance are gradually using analytical and
computational methods to aid in management as well as decisions regarding strategy. In …