ID 4110
FullText File
Title Alternative
Visualization of the Market Sentiment in Stock Markets based on Neural Network
Authors
Self DOI
Journal Title
The Wakayama economic review
Publisher
和歌山大学経済学会
ISSN
04516222
NCID
AN00071425
Volume
400
Start Page
17
End Page
33
Order
02
Published Date
2020-03-01
Language
jpn
Docuemnt Type
論文
Keywords
株価指数時系列分析
市場心理
ニューラルネットワーク
Keywords Alternative
Stock Index Time Series Analysis
market sentiment
neural network
Abstract Alternative
In this study, we tried to visualize the market sentiment that affects the judgment and behavior of stock market participants. Its purpose is to clarify the periodicity contained in the time series data of TOPIX and S&P500. The trend and volatility for a given period of time were calculated for price fluctuations from 2005 to 2014 and we used as training data for the neural network. We prepared three types of learning data: short, medium, and long term, according to the length of the period over which we calculate the trend and volatility. An agent with a neural network learns using one of these three types of training data, and each predicted a near-future price after the training was completed. Therefore, we used three agents in this study. By comparing the predictive results of these three agents, we attempted to visualize market sentiment.
Content Type
Departmental Bulletin Paper
Text Version
publisher