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CandleAction

Recognition of Candlestick Patterns

The idea of using the chart with candlesticks (or candles) for predicting market prices is very old. Two centuries ago, Japanese rice trader found that the candlesticks pattern chart could be used as a tool to predict future prices in a free market with a natural demand-supply balance. The method was improved later by others and today it is successfully used by many traders and investors in the forexmarket.

The EA addresses the problem of using Japanese candle-stick methodology to analyze index, metal or forex market data by neural nets. Self-organizing maps are presented as tools for providing maps of known candlestick formations. They may be used to visualize these patterns, and as inputs for more complex trading decision systems. In that case, their role is preprocessing, coding and pre-classification of price data.

In this paper, we focus on only one such activity, the analysis of single candles and small groups of candles on the chart. Particularly, self organizing maps will be used as tools for recognizing patterns in price timeseries and for coding the recognized formations as inputs for further steps of decision making. Their role in the whole decision process may be considered as preprocessing, compression, or initial classification of candle data. Along that task, self organizing nets will provide us with clear and coherent maps of formations for the analyzed instrument, preserving the density, topology and similarity of candle formations on a particular chart.