Since the pioneering work of Harry Markowitz, mean–variance portfolio selection model has
been widely used in both theoretical and empirical studies, which maximizes the investment …

Integrating return prediction of traditional time series models in portfolio formation can
improve the performance of original portfolio optimization model. Since machine learning …

Portfolio theory is an important foundation for portfolio management which is a well-studied
subject yet not fully conquered territory. This paper proposes a mixed method consisting of …

The future performance of stock markets is the most crucial factor in portfolio creation. As
machine learning technique is advancing, new possibilities have opened up for …

Portfolio optimization is a hot research topic, which has attracted many researchers in recent
decades. Better portfolio optimization model can help investors earn more stable profits. This …

Energy portfolios have important applications in many aspects of the energy market. This
paper commonly integrates return and volatility prediction to advance portfolio models for …

This research presents a comprehensive, sequential ensemble framework meticulously
crafted for optimizing investment portfolios, focusing on the construction industry. It employs …

In this analysis of the risk and return of stocks in global markets, we build a reasonably large
number of stock selection models and create optimized portfolios to outperform a global …

We extract information on relative shopping interest from Google search volume and provide
a genuine and economically meaningful approach to directly incorporate these data into a …

The purpose of this study is to document the existence, persistence, and effectiveness of
publicly available variables linked to financial anomalies during the 1979–1999 time period …