Diversification is one of the major components of investment decision-making under risk or
uncertainty. However, paradoxically, as the 2007–2009 financial crisis revealed, the concept …

Stochastic linear programming is a suitable numerical approach for solving practical asset-
liability management problems. In this paper, we consider a multi-stage setting under time …

We investigate the use of machine learning (ML) to forecast stock returns in the Brazilian
market using a rich proprietary dataset. While ML portfolios can easily outperform the local …

We construct portfolios with an alternative selection criterion, the Omega function, which can
be expressed as the ratio of two partial moments of a portfolio's return distribution. The main …

Purpose: The challenge of managing a portfolio effectively is allocating capital among
numerous stock holdings to achieve maximum profit. Therefore, the purpose of this study is …

The book is a monograph in the cross disciplinary area of Computational Intelligence in
Finance and elucidates a collection of practical and strategic Portfolio Optimization models …

This paper used artificial neural networks (ANNs) time series predictor for approximating
returns of Pakistan Stock Exchange (PSX) listed 100 companies. These projected returns …

The information coefficient (IC), the correlation between forecasted and realized return, is a
popular measure of signal quality. As shown in this article, variation in IC is an important …

This paper explores the scholarship and intellectual contribution of the second series of
World Order magazine, which published from 1966 until 2008 over 38 volumes. In so doing …

We construct portfolios with an alternative selection criterion, the Omega function, which can
be expressed as the ratio of two partial moments of the returns distribution. Finding Omega …