Analysis of effect by technical analysis using machine learning

Abstract

In recent years, stock prices have been predicted in various forms such as technical analysis and fundamental analysis using time series data and financial indicators, and text analysis using news information. In particular, some use text mining to predict whether stock prices will rise or fall from text information, but useful text information does not appear frequently on all stocks. Considering the increase in algorithmic trading using technical analysis, analysis that relies solely on textual information is not appropriate because it does not take into account the impact of such trading. Therefore, in this study, first, stocks that are easily affected by technical analysis were ranked by using machine learning to raise and lower stock prices using indicators that are often used in technical analysis techniques. Moreover, when the analysis did not go well, we analyzed what kind of events occurred and investigated how technical analysis affects the stock price.