Abstract
We investigated the effects of news valence, the direction of trends in graphically presented price series, and the culture and personality of traders in a financial trading task. Participants were given 12 virtual shares of financial assets and asked to use price graphs and news items to maximize their returns by buying, selling, or holding each one. In making their decisions, they were influenced by properties of both news items and price series but they relied more on the former. Western participants had lower trading latencies and lower return dispersions than Eastern participants. Those with greater openness to experience had lower trading latencies. Participants bought more shares when they forecast that prices would rise but failed to sell more when they forecast that they would fall. These findings are all consistent with the view that people trading assets try to make sense of information by incorporating it within a coherent narrative.
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Public Interest Statement
We investigated the effects of news valence, the direction of trends in graphically presented price series, and the culture and personality of traders in a financial trading task. Participants were given 12 virtual shares of financial assets and asked to use price graphs and news items to maximize their returns by buying, selling, or holding each one. In making their decisions, they were influenced by properties of both news items and price series but they relied more on the former. Western participants had lower trading latencies and lower return dispersions than Eastern participants. Those with greater openness to experience had lower trading latencies. Participants bought more shares when they forecast that prices would rise but failed to sell more when they forecast that they would fall. These findings are all consistent with the view that people trading assets try to make sense of information by incorporating it within a coherent narrative.
Notes
1. The graphs that participants saw showed asset price as a function of time. Hence, trading latency represented the date on which participants made their financial decision in the virtual trading task rather than the actual duration of each trial.
2. This interval ensured that successive price changes were independent, thereby making series consistent with the random walk behavior expected from the EMH. This allows our results to be compared with predictions derived from that approach.
3. Our inclusion of filler series with U-shaped and inverted U-shaped trends may have acted to reduce the weight that participants put on price trend data when making their trading decisions. However, inclusion of filler series ensured high external validity of the experiments: clearly, in real life, not all trends are easy to identify.
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Notes on contributors
Daphne Sobolev
Daphne Sobolev is a teaching fellow and a research associate at the School of Management at University London College. Her research focuses on judgment and decision-making. In particular, she is interested in behavioral finance, business ethics, consumer ethics, and forecasting.
Bryan Chan
Bryan Chan completed his BSc in Psychology in the Department of Experimental Psychology at University College London. He currently works in the aviation industry, where he is interested in how people deal with conflicts in information that they receive from different sources.
Nigel Harvey
Nigel Harvey is a professor of Judgment and Decision Research at University College London and a visiting fellow in the Department of Statistics, London School of Economics and Political Science. His research focuses on the cognitive processes that people use to respond to time series data: forecasting, controlling, or otherwise reacting to them.