Applying Machine Learning, Asset Allocation, and Risk Management in Selecting Stocks and Building Profitable Portfolio
| dc.contributor.advisor | Nguyen, Hien Van | |
| dc.contributor.committeeMember | Chen, Jiefu | |
| dc.contributor.committeeMember | Pan, Miao | |
| dc.creator | Duong, Binh | |
| dc.creator.orcid | 0000-0002-1089-5480 | |
| dc.date.accessioned | 2023-05-28T18:55:36Z | |
| dc.date.created | December 2022 | |
| dc.date.issued | 2022-12-14 | |
| dc.date.updated | 2023-05-28T18:55:37Z | |
| dc.description.abstract | Many years ago, the stock market became one of the considerable investment channels for many individuals. When the Covid-19 pandemic occurred in the world, many people are placed under full or partial lockdown, and the “stock” keyword became trendy on Google Search. People started discussing investing or trading in the stock market. Approximately, 95% traders lose money due to many factors such as lack of experience, financial knowledge, or fortune. The comparison between investors and traders, which includes all types of traders such as day traders and swing traders, gradually became popular. There are many strategies to invest or trade in the stock market. One of the efficient methods is to select good stocks to build a profitable portfolio. It sounds easy, but it requires many steps and effort including collecting and cleaning data, filtering stocks, gathering potential stocks, predicting stock returns, creating portfolios, filtering portfolios by using risk management, finding weights of each stock by asset allocation, and testing with a custom environment. | |
| dc.description.department | Electrical and Computer Engineering, Department of | |
| dc.format.digitalOrigin | born digital | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.uri | https://hdl.handle.net/10657/14349 | |
| dc.language.iso | eng | |
| dc.rights | The author of this work is the copyright owner. UH Libraries and the Texas Digital Library have their permission to store and provide access to this work. Further transmission, reproduction, or presentation of this work is prohibited except with permission of the author(s). | |
| dc.subject | Stock | |
| dc.subject | KNN | |
| dc.subject | PCA | |
| dc.subject | HMM | |
| dc.subject | CNN | |
| dc.subject | PPO | |
| dc.subject | Allocation | |
| dc.subject | Risk | |
| dc.title | Applying Machine Learning, Asset Allocation, and Risk Management in Selecting Stocks and Building Profitable Portfolio | |
| dc.type.dcmi | Text | |
| dc.type.genre | Thesis | |
| dcterms.accessRights | The full text of this item is not available at this time because the student has placed this item under an embargo for a period of time. The Libraries are not authorized to provide a copy of this work during the embargo period. | |
| local.embargo.lift | 2024-12-01 | |
| local.embargo.terms | 2024-12-01 | |
| thesis.degree.college | Cullen College of Engineering | |
| thesis.degree.department | Electrical and Computer Engineering, Department of | |
| thesis.degree.discipline | Electrical Engineering | |
| thesis.degree.grantor | University of Houston | |
| thesis.degree.level | Masters | |
| thesis.degree.name | Master of Science in Electrical Engineering |