| Titre : | Synthesis of the portfolio optimization algorithms in finance | | Type de document : | projet fin études | | Auteurs : | Abderraouf HARAKAT, Auteur | | Langues : | Français (fre) | | Catégories : | Ingénierie Finance et la Gestion des Risques (IFGR)
| | Index. dĂ©cimale : | mast 146/18 | | RĂ©sumĂ© : | In finance, portfolio management is a very important activity. It is a fundamental tool for investors and a good dashboard for decision makers. However, we cannot conceive success in this management without managing risk. Indeed, the goal of any portfolio management is to ensure a best distribution of the investor’s assets thereby, an optimized risk/return ratio can be achieved.
Several works and scientific research have successfully led to a set of optimization algorithms. In this work, we will focus on some of them for study and comparison.
Our goal is to contribute in this field of research by reviewing, via a literature review, recent and old research studies and articles that have been conducted about these algorithms. Eventual coming researches in this subject can refer to this work, and develop the new results.
Three algorithms from the most useful new techniques in this field were analysed. Genetic algorithm, particle swarm optimization and simulated annealing. They all lead to important results and good portfolio optimization. Otherwise, another type of algorithm improves these results, it is the hybrid algorithms.
Finally, a best portfolio optimization can be achieved by introducing Machine Learning algorithms in this hybridization. Recent work has studied some examples and illustrated the results. |
Synthesis of the portfolio optimization algorithms in finance [projet fin études] / Abderraouf HARAKAT, Auteur . - [s.d.]. Langues : Français ( fre) | Catégories : | Ingénierie Finance et la Gestion des Risques (IFGR)
| | Index. dĂ©cimale : | mast 146/18 | | RĂ©sumĂ© : | In finance, portfolio management is a very important activity. It is a fundamental tool for investors and a good dashboard for decision makers. However, we cannot conceive success in this management without managing risk. Indeed, the goal of any portfolio management is to ensure a best distribution of the investor’s assets thereby, an optimized risk/return ratio can be achieved.
Several works and scientific research have successfully led to a set of optimization algorithms. In this work, we will focus on some of them for study and comparison.
Our goal is to contribute in this field of research by reviewing, via a literature review, recent and old research studies and articles that have been conducted about these algorithms. Eventual coming researches in this subject can refer to this work, and develop the new results.
Three algorithms from the most useful new techniques in this field were analysed. Genetic algorithm, particle swarm optimization and simulated annealing. They all lead to important results and good portfolio optimization. Otherwise, another type of algorithm improves these results, it is the hybrid algorithms.
Finally, a best portfolio optimization can be achieved by introducing Machine Learning algorithms in this hybridization. Recent work has studied some examples and illustrated the results. |
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Synthesis of the portfolio optimization algorithms in finance / Abderraouf HARAKAT
