Stock forecasting using transformers

This paper develops a model for predicting stock investment value using past stock market information based on the transformer deep learning method. To obtain the investment value of stock more accurately, the technical analysis method of predicting the future stock price based on the past sto...

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Bibliographic Details
Main Author: Peng, Xiaoqi
Other Authors: Wang Lipo
Format: Thesis-Master by Coursework
Language:English
Published: Nanyang Technological University 2023
Subjects:
Online Access:https://hdl.handle.net/10356/169344
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author Peng, Xiaoqi
author2 Wang Lipo
author_facet Wang Lipo
Peng, Xiaoqi
author_sort Peng, Xiaoqi
collection NTU
description This paper develops a model for predicting stock investment value using past stock market information based on the transformer deep learning method. To obtain the investment value of stock more accurately, the technical analysis method of predicting the future stock price based on the past stock price and the fundamental analysis method based on the past intrinsic value of stocks (Composite Index, earnings per share, Market capitalisation in circulation) are adopted. To predict stock investment value as accurately as possible, transformer as a new deep learning method is tried to solve this problem. The main research work and contributions of this paper are as follows: (1) Build a model of stock prediction method in a Python environment based on technical analysis and fundamental analysis of the actual stock market; (2) Based on the PyTorch platform and Python language, a stock prediction method based on the transformer algorithm is developed. By debugging parameters and comparing the predicted value with the actual value, the effectiveness of this method in stock investment value prediction is demonstrated. Based on the above facts, this paper successfully realises the use of the transformer method to predict the future investment value of stocks.
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spelling ntu-10356/1693442023-07-14T15:43:24Z Stock forecasting using transformers Peng, Xiaoqi Wang Lipo School of Electrical and Electronic Engineering ELPWang@ntu.edu.sg Engineering::Electrical and electronic engineering This paper develops a model for predicting stock investment value using past stock market information based on the transformer deep learning method. To obtain the investment value of stock more accurately, the technical analysis method of predicting the future stock price based on the past stock price and the fundamental analysis method based on the past intrinsic value of stocks (Composite Index, earnings per share, Market capitalisation in circulation) are adopted. To predict stock investment value as accurately as possible, transformer as a new deep learning method is tried to solve this problem. The main research work and contributions of this paper are as follows: (1) Build a model of stock prediction method in a Python environment based on technical analysis and fundamental analysis of the actual stock market; (2) Based on the PyTorch platform and Python language, a stock prediction method based on the transformer algorithm is developed. By debugging parameters and comparing the predicted value with the actual value, the effectiveness of this method in stock investment value prediction is demonstrated. Based on the above facts, this paper successfully realises the use of the transformer method to predict the future investment value of stocks. Master of Science (Communications Engineering) 2023-07-13T08:55:51Z 2023-07-13T08:55:51Z 2023 Thesis-Master by Coursework Peng, X. (2023). Stock forecasting using transformers. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/169344 https://hdl.handle.net/10356/169344 en ISM-DISS-03481 application/pdf Nanyang Technological University
spellingShingle Engineering::Electrical and electronic engineering
Peng, Xiaoqi
Stock forecasting using transformers
title Stock forecasting using transformers
title_full Stock forecasting using transformers
title_fullStr Stock forecasting using transformers
title_full_unstemmed Stock forecasting using transformers
title_short Stock forecasting using transformers
title_sort stock forecasting using transformers
topic Engineering::Electrical and electronic engineering
url https://hdl.handle.net/10356/169344
work_keys_str_mv AT pengxiaoqi stockforecastingusingtransformers