Stock picking with machine learning
This study focuses on the integration of both Fundamental and Technical Analysis in stock picking with the machine learning model, Multilayer Perceptron (MLP). We will analyze time-series stock data to identify optimal features for training the MLP model and assess the predictability of the machine...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2023
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| Online Access: | https://hdl.handle.net/10356/172691 |
| _version_ | 1811681439056396288 |
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| author | Ong, Glenna Xianyu |
| author2 | Wang Lipo |
| author_facet | Wang Lipo Ong, Glenna Xianyu |
| author_sort | Ong, Glenna Xianyu |
| collection | NTU |
| description | This study focuses on the integration of both Fundamental and Technical Analysis in stock picking with the machine learning model, Multilayer Perceptron (MLP).
We will analyze time-series stock data to identify optimal features for training the MLP model and assess the predictability of the machine learning model. The historical stock prices and financial metrics from Nasdaq will be used for analysis. The financial metrics used include Market Capitalization, Earnings Per Share (EPS), Price-to-Earnings (PE) ratio, Price-to-book (PB) ratio, Price-to-Sales (PS) ratio, Market Capitalization and Dividend Yield of stocks from Nasdaq.
In this paper, we determine whether MLP can accurately forecast market movements with historical financial data and stock market indicators. |
| first_indexed | 2024-10-01T03:40:57Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/172691 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T03:40:57Z |
| publishDate | 2023 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1726912023-12-22T15:42:29Z Stock picking with machine learning Ong, Glenna Xianyu Wang Lipo School of Electrical and Electronic Engineering ELPWang@ntu.edu.sg Engineering::Electrical and electronic engineering This study focuses on the integration of both Fundamental and Technical Analysis in stock picking with the machine learning model, Multilayer Perceptron (MLP). We will analyze time-series stock data to identify optimal features for training the MLP model and assess the predictability of the machine learning model. The historical stock prices and financial metrics from Nasdaq will be used for analysis. The financial metrics used include Market Capitalization, Earnings Per Share (EPS), Price-to-Earnings (PE) ratio, Price-to-book (PB) ratio, Price-to-Sales (PS) ratio, Market Capitalization and Dividend Yield of stocks from Nasdaq. In this paper, we determine whether MLP can accurately forecast market movements with historical financial data and stock market indicators. Bachelor of Engineering (Information Engineering and Media) 2023-12-18T06:11:42Z 2023-12-18T06:11:42Z 2023 Final Year Project (FYP) Ong, G. X. (2023). Stock picking with machine learning. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/172691 https://hdl.handle.net/10356/172691 en A3316-222 application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Electrical and electronic engineering Ong, Glenna Xianyu Stock picking with machine learning |
| title | Stock picking with machine learning |
| title_full | Stock picking with machine learning |
| title_fullStr | Stock picking with machine learning |
| title_full_unstemmed | Stock picking with machine learning |
| title_short | Stock picking with machine learning |
| title_sort | stock picking with machine learning |
| topic | Engineering::Electrical and electronic engineering |
| url | https://hdl.handle.net/10356/172691 |
| work_keys_str_mv | AT ongglennaxianyu stockpickingwithmachinelearning |