Stock trading and prediction using deep learning neural network
Everyday millions of shares trade, with an overall value of a few hundred million. This is due to stockbrokers, traders, stock analysts, portfolio managers or investment bankers trading shares to get monetary gains. However, with the stock market's volatility there is no definite guarantee of p...
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| Other Authors: | |
| Format: | Final Year Project (FYP) |
| Language: | English |
| Published: |
2018
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| Online Access: | http://hdl.handle.net/10356/75389 |
| _version_ | 1826112131154575360 |
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| author | Cheam, Nicholas Yen Kait |
| author2 | Wang Lipo |
| author_facet | Wang Lipo Cheam, Nicholas Yen Kait |
| author_sort | Cheam, Nicholas Yen Kait |
| collection | NTU |
| description | Everyday millions of shares trade, with an overall value of a few hundred million. This is due to stockbrokers, traders, stock analysts, portfolio managers or investment bankers trading shares to get monetary gains. However, with the stock market's volatility there is no definite guarantee of profiting. In some severe cases the market may crash. These crashes resulted in devastating losses for most, if not all, of the players in the stock market. In this paper, we will look at the various models people have used to predict stock prices in order to make gains, investigate if development in deep learning neural network models are an improvement over existing models and to test out various parameters to get more accurate predictions of stock prices. |
| first_indexed | 2024-10-01T03:01:56Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/75389 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T03:01:56Z |
| publishDate | 2018 |
| record_format | dspace |
| spelling | ntu-10356/753892023-07-07T16:29:23Z Stock trading and prediction using deep learning neural network Cheam, Nicholas Yen Kait Wang Lipo School of Electrical and Electronic Engineering DRNTU::Engineering DRNTU::Engineering::Electrical and electronic engineering Everyday millions of shares trade, with an overall value of a few hundred million. This is due to stockbrokers, traders, stock analysts, portfolio managers or investment bankers trading shares to get monetary gains. However, with the stock market's volatility there is no definite guarantee of profiting. In some severe cases the market may crash. These crashes resulted in devastating losses for most, if not all, of the players in the stock market. In this paper, we will look at the various models people have used to predict stock prices in order to make gains, investigate if development in deep learning neural network models are an improvement over existing models and to test out various parameters to get more accurate predictions of stock prices. Bachelor of Engineering 2018-05-31T03:08:50Z 2018-05-31T03:08:50Z 2018 Final Year Project (FYP) http://hdl.handle.net/10356/75389 en Nanyang Technological University 60 p. application/pdf |
| spellingShingle | DRNTU::Engineering DRNTU::Engineering::Electrical and electronic engineering Cheam, Nicholas Yen Kait Stock trading and prediction using deep learning neural network |
| title | Stock trading and prediction using deep learning neural network |
| title_full | Stock trading and prediction using deep learning neural network |
| title_fullStr | Stock trading and prediction using deep learning neural network |
| title_full_unstemmed | Stock trading and prediction using deep learning neural network |
| title_short | Stock trading and prediction using deep learning neural network |
| title_sort | stock trading and prediction using deep learning neural network |
| topic | DRNTU::Engineering DRNTU::Engineering::Electrical and electronic engineering |
| url | http://hdl.handle.net/10356/75389 |
| work_keys_str_mv | AT cheamnicholasyenkait stocktradingandpredictionusingdeeplearningneuralnetwork |