Abstract: In this paper, we study the Markowitz dynamic portfolio problem, where individual agents seek to maximize their expected return while minimizing the variance of the return (risk). We model a ...

Abstract: The bio-inspired metaheuristics have evolved as effective alternatives to handle portfolio optimization problems, which remain a key instrument in investment analysis. This study proposes ...

CEO Jon Erik Fyrwald stated that "IFF's fourth quarter and full year 2025 results reflect a continued focus on disciplined execution and improvements across the business to further strengthen our ...

Smurfit said for 2026, the company expects first quarter adjusted EBITDA of between $1.1 billion and $1.2 billion and a full year 2026 adjusted EBITDA between $5 billion and $5.3 billion. He described ...

Abstract: We study Markowitz's mean-variance portfolio optimization problem. When practically using this model, the mean vector and the covariance matrix of the assets returns often need to be ...

Pitz outlined 2026 enterprise financial targets: "9% to 12% growth in earnings per share, 75% to 85% free capital flow conversion and 15% to 17% return on equity. The ROE target has increased, ...

Abstract: Portfolio optimization remains a critical challenge in modern investment management, particularly as traditional methods like Modern Portfolio Theory (MPT) and Value at Risk (VaR) show ...

Abstract: In the realm of portfolio optimization, the Markowitz and Black-Litterman models play a significant role. This study closely examines their performance in three broad market indices; the ...

Abstract: Portfolio optimization is one of the most studied optimization problems at the intersection of quantum computing and finance. In this work, we develop the first quantum formulation for a ...

Abstract: Selecting appropriate research and development (R&D) projects under budget constraints is a critical yet challenging task for enterprises. During development, these projects are inevitably ...