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Research of Chinese Stock Market Based on Financial Time Series and Deep Machine Learning

Su, Jingyi LU and Xiao, Ying LU (2022) NEKN02 20221
Department of Economics
Abstract
The stock market plays an important role in promoting the development of the national economy. It is of great significance to deeply understand the operation laws of the stock market and predict the future stock price. This paper explores the prediction methods of the Chinese stock market by analyzing the stock trading data and macroeconomics data. This paper compares four methods to predict the rise and fall trend, and two methods to predict the close price of the Chinese stock market. The results show that the multilayer perceptron (MLP) is the most effective model in predicting the rise and fall trend, the long short term model (LSTM) is more effective in predicting the day close price. Finally, based on practical analysis, this paper... (More)
The stock market plays an important role in promoting the development of the national economy. It is of great significance to deeply understand the operation laws of the stock market and predict the future stock price. This paper explores the prediction methods of the Chinese stock market by analyzing the stock trading data and macroeconomics data. This paper compares four methods to predict the rise and fall trend, and two methods to predict the close price of the Chinese stock market. The results show that the multilayer perceptron (MLP) is the most effective model in predicting the rise and fall trend, the long short term model (LSTM) is more effective in predicting the day close price. Finally, based on practical analysis, this paper also gives some suggestions to improve the healthy development of the Chinese stock market. (Less)
Popular Abstract
The stock market is a critical part of the financial market and also a necessary means of capital allocation. It plays an important role in promoting the development of the national economy. It is of great significance to deeply understand the operation laws of the stock market and predict the future stock price, either for investors to reduce investment risk or for the economic management departments to make economic policies. The aim of this paper is to explore the prediction methods of the Chinese stock market by analyzing the stock trading data and macroeconomics data.
Please use this url to cite or link to this publication:
author
Su, Jingyi LU and Xiao, Ying LU
supervisor
organization
course
NEKN02 20221
year
type
H1 - Master's Degree (One Year)
subject
keywords
stock price prediction, financial time series, machine learning, long short term model
language
English
id
9087779
date added to LUP
2022-10-10 09:36:40
date last changed
2022-10-10 09:36:40
@misc{9087779,
  abstract     = {{The stock market plays an important role in promoting the development of the national economy. It is of great significance to deeply understand the operation laws of the stock market and predict the future stock price. This paper explores the prediction methods of the Chinese stock market by analyzing the stock trading data and macroeconomics data. This paper compares four methods to predict the rise and fall trend, and two methods to predict the close price of the Chinese stock market. The results show that the multilayer perceptron (MLP) is the most effective model in predicting the rise and fall trend, the long short term model (LSTM) is more effective in predicting the day close price. Finally, based on practical analysis, this paper also gives some suggestions to improve the healthy development of the Chinese stock market.}},
  author       = {{Su, Jingyi and Xiao, Ying}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{Research of Chinese Stock Market Based on Financial Time Series and Deep Machine Learning}},
  year         = {{2022}},
}