Chapter 12. New Directions in Sentiment Analysis: Charting Words
The aim of this chapter is to introduce the emerging field of text mining as a new form of sentiment analysis for use in trading markets.
This book has really been about the analysis of the shape of sentiment. We first looked at how traders can apply alternative charting to detect sentiment in the market. We can deduce that a price point in the market, represented by a candlestick, line, bar chart, price break chart, Kagi chart, or Renko chart, is the result of an adversarial contest between buyers and sellers. Each price close represents a unit of sentiment. From this perspective, we can consider technical analysis or chart reading to be a branch of shape science. As a result, a chart type is really a shape that has been revealed from sample data. Accordingly, price break charts, Kagi charts, point and figure charts, and Renko charts represent shapes but use different landmarks. The application of these charts is not very different from any pattern recognition process that cuts across disciplines. We can apply some of the principles of shape analysis, which started with the science of morphometrics (the study of biological form), to chart reading.[11]
Consider the following statement: "Shape is a definite entity, a configuration of points that keep geometric relationships among them."[12] Recognizing the shape of surprise in the market is not really different from recognizing a face in a crowd. Seen in this context, ...
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