Candlestick—The Main Mistake of Economy Research in High Frequency Markets

Abstract

One of the key problems of researching the high-frequency financial markets is the proper data format. Application of the candlestick representation (or its derivatives such as daily prices, etc.), which is vastly used in economic research, can lead to faulty research results. Yet, this fact is consistently ignored in most economic studies. The following article gives examples of possible consequences of using candlestick representation in modelling and statistical analysis of the financial markets. Emphasis should be placed on the problem of research results being detached from the investing practice, which makes most of the results inapplicable from the investor’s point of view. The article also presents the concept of a binary-temporal representation, which is an alternative to the candlestick representation. Using binary-temporal representation allows for more precise and credible research and for the results to be applied in investment practice.

Empirical mode decomposition using deep learning model for financial market forecasting

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Support Vector Machine for Predicting Candlestick Chart Movement on Foreign Exchange

“…The candlestick chart has many functional visual patterns and can interpret prices during the session simply so that it is easy to explain in decision-making. As a result, the candlestick chart is one of the most widely used charts [3,4].…”