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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Main Author: Balasubramaniam, Abhinav Narayana
Other Authors: Ponnuthurai Nagaratnam Suganthan
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2022
Subjects:
Online Access:https://hdl.handle.net/10356/158140
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Institution: Nanyang Technological University
Language: English
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spelling 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
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering
spellingShingle 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
publisher Nanyang Technological University
publishDate 2022
url https://hdl.handle.net/10356/158140
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