Abstract
Technical analysis is a widely used tool in making investment decisions. Nowadays it becomes very popular in the context of big data analysis and artificial intelligence framework. Although the analysis of the results of indicators in certain markets often becomes the axis of technical analysis research, it is difficult to find articles aimed at applying and comparing this analysis in different markets. This paper attempts to answer the question of whether technical analysis indicators work in the same or different ways in the US, European, and Asian stock markets. For this purpose, 8 indicators are calculated, and their results are compared in three selected markets. The correlation between the indicators themselves in individual markets is also determined. It has been observed that the performance of technical analysis is similar in different markets so this type of analysis can be used in artificial intelligence framework.
Highlights
Technical analysis becomes especially relevant topic in big data and artificial intelligence field because this type of analysis is integrated in decision making framework
The main question raised in this work was to examine whether the image of technical analysis is the same in different markets or whether it works differently
This topic is very relevant in the context in big data analytics and artificial intelligence framework so it is very important to check the capabilities of technical analysis methods
Summary
Technical analysis becomes especially relevant topic in big data and artificial intelligence field because this type of analysis is integrated in decision making framework. The importance of big data and artificial intelligence increases day by day and financial institutions and investors seek to be involved in this technological process. Increasing interest in big data and artificial intelligence force market players to take decisions how to apply technologies in order to improve their daily activities. The term artificial intelligence first appeared at Dartmouth College in 1956. It is not a new concept but nowadays because of high technological development artificial intelligence can help to improve daily processes much more than could do many years ago. FCA indicates that the company should have a formal process to identify material changes to algorithmic trading activity – either in terms of a shift in strategy or the introduction of new algorithms. The company should have very detailed algorithmic inventory which should include:
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