Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/158140
Title: Genetic algorithms for portfolio optimization
Authors: Balasubramaniam, Abhinav Narayana
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2022
Publisher: Nanyang Technological University
Source: Balasubramaniam, A. N. (2022). Genetic algorithms for portfolio optimization. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/158140
Project: A1100-211
Abstract: 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.
URI: https://hdl.handle.net/10356/158140
Schools: School of Electrical and Electronic Engineering 
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

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