Impact of chart image characteristics on stock price prediction with a convolutional neural network.

ABSTRACT: Stock price prediction has long been the subject of research because of the importance of accuracy of prediction and the difficulty in forecasting. Traditionally, forecasting has involved linear models such as AR and MR or nonlinear models such as ANNs using standardized numerical data such as corporate financial data and stock price data. Due to the difficulty of securing a sufficient variety of data, researchers have recently begun using convolutional neural networks (CNNs) with stock price graph images only. However, we know little about which characteristics of stock charts affect the accuracy of predictions and to what extent. The purpose of this study is to analyze the effects of stock chart characteristics on stock price prediction via CNNs. To this end, we define the image characte

SUBMITTER: Jin G 

PROVIDER: S-EPMC8221485 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature