PARTICLE SWARM OPTIMIZATION IMPLEMENTATIONON PORTFOLIO OPTIMIZATION PROBLEMS
The Markowitz portfolio model has become the cornerstone of modern portfolio theory because it is able to provide an overview of how to build an optimal portfolio. Over time, this model was then expanded with a variety of additional constraints to get closer to real-world investment problems, suc...
محفوظ في:
| المؤلف الرئيسي: | |
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| التنسيق: | Final Project |
| اللغة: | Indonesia |
| الوصول للمادة أونلاين: | https://digilib.itb.ac.id/gdl/view/72988 |
| الوسوم: |
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| المؤسسة: | Institut Teknologi Bandung |
| اللغة: | Indonesia |
| الملخص: | The Markowitz portfolio model has become the cornerstone of modern portfolio
theory because it is able to provide an overview of how to build an optimal portfolio.
Over time, this model was then expanded with a variety of additional constraints
to get closer to real-world investment problems, such as buy-in threshold and
roundlot constraints. The buy-in threshold constraint provides a minimum limit for
the proportion of asset purchases and the roundlot constraint provides a portfolio
arrangement in accordance with the lot unit. There are additional constraints
and variations of assets that may be included in the portfolio, presenting its own
complexity in calculating the Markowitz portfolio model analytically. These more
complex problems can be solved numerically more effectively and efficiently. One
method that can be used is the Particle Swarm Optimization algorithm which is a
metaheurestic method. In this final project, an optimal portfolio will be developed
based on the Markowitz portfolio model buy-in threshold and roundlot constraints
metaheurestically using Particle Swarm Optimization. |
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