Abstract Machine learning has been widely applied to predict asset returns and can improve
static portfolio selection model performance by handling complex financial information …

This paper solves the robust portfolio decision problem with subjective risk aversion under
dependence uncertainty. We use spectral risk measures to capture investors' subjective risk …

The modeling and identification of time series data with a long memory are important in
various fields. The streamflow discharge is one such example that can be reasonably …

The online portfolio selection (OLPS) problem differs from classical portfolio model
problems, as it involves making sequential investment decisions. Many OLPS strategies …

This paper solves the robust portfolio selection problem with spectral risk measures under
mixture R-vine copula uncertainty. Spectral risk measures are used to capture investors' …

Multistage stochastic programming (MSP) problems belong to a class of problems that
involve a sequence of decisions made over multiple time stages under uncertainty. Many …

RESUMO MARTINS, Patricia Reis. A maximização da assimetria na seleção de carteiras
eficientes. 2023. 11 f. Tese (Doutorado em Ciências Computacionais)–Instituto de …

Considering transaction costs, borrowing constraints, upper and lower bounds, carnality
constraints and bankruptcy control, a novel multi-period predicted mean variance portfolio …

The convertible bond has become an important tool in financial market and enjoyed
significant growth in China's capital markets since the Chinese government decided to …