No / The usefulness of technical analysis, or charting, has been questioned because it flies in the face of the ‘random walk’ and tests present conflicting results. We examine chartists’ decision-making techniques and derive a taxonomy of charting strategies based on investors’ market ontologies and calculative strategies. This distinguishes between trend-seekers and pattern-seekers, and trading as a system or an art. We argue that interpretative activity plays a more important role than previously thought and suggest that charting’s main appeal for users lies in its power as a heuristic device regardless of its effectiveness at generating returns.

Stock market investors are making investment decisions in an information-rich environment. In their attempt to afford investors all the decision-relevant information, standard setters are continually adding to the already weighty load seemingly oblivious to the cognitive limitations of humans. Information overload has long been recognized as a problem to decision-makers. The information overload literature is robust with studies supporting the inverted U hypothesis: Decision accuracy will increase with additional information to the point of maximum processing capability, then decline. The decision style literature has supported the theory that individuals can be classified according to the quantity of information that they are able to process effectively. This study combined the two theories to develop hypotheses about how investors with differing decision styles might behave differently in an information-rich environment. The hypotheses were tested in an internet-based stock market investment experiment. In general, the study did not find significant differences in the decisions of investors with different decision styles. Though the results of the experiment failed to support most of the hypotheses, the study revealed some interesting facts about the investors who participated in this study. There was an unusually high concentration of the analytic decision style in this group. This style, according to the theory, is the one best able to manage high information processing demands. A further analysis of the respondent style dominance reveals that all of the styles had significant analytic influence. This could explain the lack of variation in the decision accuracy of the respondents. It is also possible that the respondents in this study did not reach a point of information overload. Based on prior literature, the study incorporated ten information items. However, the particular items selected may not have created a sense of information overload for the respondents. Future research should increase the information available to respondents and observe whether differences in decisions can be explained by differences in decision styles in an information overload situation. This study provides a baseline for future studies examining how investors make decisions when so much information is available.