Genetic algorithms for portfolio optimization
In the modern age financial markets have grown dramatically and become vastly more complicated. Subsequently, this makes investing to gain from assets in these markets far more complicated as well. The aim of this study is twofold, finding ways to create optimal portfolios using Markowitz’s model...
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sg-ntu-dr.10356-1581402023-07-07T19:33:37Z Genetic algorithms for portfolio optimization Balasubramaniam, Abhinav Narayana Ponnuthurai Nagaratnam Suganthan School of Electrical and Electronic Engineering EPNSugan@ntu.edu.sg Engineering::Electrical and electronic engineering In the modern age financial markets have grown dramatically and become vastly more complicated. Subsequently, this makes investing to gain from assets in these markets far more complicated as well. The aim of this study is twofold, finding ways to create optimal portfolios using Markowitz’s model and providing an interface for users to perform optimizations based on methods in the study. The experimentation tests various factors such as time duration, frequency of data points, algorithm used to solve the problem etc.. The user interface should be easily available, intuitive and seamless, it should enable users to perform optimization on their datasets using methods in the experiment. Bachelor of Engineering (Electrical and Electronic Engineering) 2022-05-30T12:45:03Z 2022-05-30T12:45:03Z 2022 Final Year Project (FYP) Balasubramaniam, A. N. (2022). Genetic algorithms for portfolio optimization. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/158140 https://hdl.handle.net/10356/158140 en A1100-211 application/pdf Nanyang Technological University |
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Engineering::Electrical and electronic engineering Balasubramaniam, Abhinav Narayana Genetic algorithms for portfolio optimization |
description |
In the modern age financial markets have grown dramatically and become vastly
more complicated. Subsequently, this makes investing to gain from assets in these
markets far more complicated as well. The aim of this study is twofold, finding ways
to create optimal portfolios using Markowitz’s model and providing an interface for
users to perform optimizations based on methods in the study. The experimentation
tests various factors such as time duration, frequency of data points, algorithm used
to solve the problem etc.. The user interface should be easily available, intuitive and
seamless, it should enable users to perform optimization on their datasets using
methods in the experiment. |
author2 |
Ponnuthurai Nagaratnam Suganthan |
author_facet |
Ponnuthurai Nagaratnam Suganthan Balasubramaniam, Abhinav Narayana |
format |
Final Year Project |
author |
Balasubramaniam, Abhinav Narayana |
author_sort |
Balasubramaniam, Abhinav Narayana |
title |
Genetic algorithms for portfolio optimization |
title_short |
Genetic algorithms for portfolio optimization |
title_full |
Genetic algorithms for portfolio optimization |
title_fullStr |
Genetic algorithms for portfolio optimization |
title_full_unstemmed |
Genetic algorithms for portfolio optimization |
title_sort |
genetic algorithms for portfolio optimization |
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Nanyang Technological University |
publishDate |
2022 |
url |
https://hdl.handle.net/10356/158140 |
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1772826723407101952 |