|
|
|
|
|
Kyle Erwin and Andries Engelbrecht
Portfolio optimization is a multi-objective optimization problem (MOOP) with risk and profit, or some form of the two, as competing objectives. Single-objective portfolio optimization requires a trade-off coefficient to be specified in order to balance t...
ver más
|
|
|
|
|
|
|
|
|
|
|
Wendy Wijaya and Kuntjoro Adji Sidarto
Portfolio optimization is a mathematical formulation whose objective is to maximize returns while minimizing risks. A great deal of improvement in portfolio optimization models has been made, including the addition of practical constraints. As the number...
ver más
|
|
|
|
|
|
|
|
|
|
|
Werry Febrianti, Kuntjoro Adji Sidarto and Novriana Sumarti
Portfolio optimization is an activity for balancing return and risk. In this paper, we used mean-variance (M-V) portfolio models with buy-in threshold and cardinality constraints. This model can be formulated as a mixed integer nonlinear programming (MIN...
ver más
|
|
|
|
|
|
|
|
|
|
|
Younes Berouaga, Cherif El Msiyah and Jaouad Madkour
Portfolio optimization is a pertinent topic of significant importance in the financial literature. During the portfolio construction, an investor confronts two important steps: portfolio selection and portfolio allocation. This article seeks to investiga...
ver más
|
|
|
|
|
|
|
|
|
|
|
Adrian Millea and Abbas Edalat
|
|
|
|
|
|
|
|
|
|
|
Branimir Mocic
Pág. 65 - 78
Research Question: This paper investigates the performances of six portfolios constructed using robust optimization methods in the Serbian stock market. Motivation: Motivated by the lack of research that analyses the allocation strategies based on robust...
ver más
|
|
|
|
|
|
|
|
|
|
|
Mirza Sikalo, Almira Arnaut-Berilo and Adela Delalic
Comparing portfolio performance is complex due to the fact that each model is dominant in its own risk space. Since there is no single dominant performance measure, the research problem is how to incorporate several different measures into a performance ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Hyunsun Song and Hyunjun Choi
Various deep learning techniques have recently been developed in many fields due to the rapid advancement of technology and computing power. These techniques have been widely applied in finance for stock market prediction, portfolio optimization, risk ma...
ver más
|
|
|
|
|
|
|
|
|
|
|
Gaurang Sonkavde, Deepak Sudhakar Dharrao, Anupkumar M. Bongale, Sarika T. Deokate, Deepak Doreswamy and Subraya Krishna Bhat
The financial sector has greatly impacted the monetary well-being of consumers, traders, and financial institutions. In the current era, artificial intelligence is redefining the limits of the financial markets based on state-of-the-art machine learning ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Serena Crisci, Valentina De Simone and Marco Viola
Many data analysis problems can be modeled as a constrained optimization problem characterized by nonsmooth functionals, often because of the presence of ℓ1" role="presentation">l1l1
l
1
-regularization terms. One of the most effective ways to...
ver más
|
|
|
|
|
|