how Visual Cues Increase the Disposition Effect

  how Visual Cues Increase the Disposition Effect

The article looks at how Visual Cues Increase the Disposition Effect. The disposition effect is whereby investors tend to sell assets that have gained value and keep assets that have reduced in value. It is one of the behavioral biases that can decrease the performance of the traders’ leading to financial losses. There are two main research questions the authors of this article address which are; (1) Is the knowledge about the existence of the disposition effect suited to lower an individuals’ disposition effect? (2) Does a trend indicator arrow positively affect the disposition effect? The authors are arguing that disposition is not considered common knowledge despite being widely known in several research communities. It is such a behavioral bias, which often leads to missed gains and individual losses. It is, therefore, necessary for online trading platforms providers to have a particular interest to not only inform their customers about that bias but also provide tools to avoid it.  The individuals’ awareness influences the strength of the bias, their internal decision making processes, and their knowledge about the specific prejudice and also the individuals’ environment (e.g., information presentation) might impact the effect strength.

The author’s focused shedding some light on the question whether it is expedient to inform about the Disposition effect. Either by using short information text directly on an online trade screen or if a ‘deeper understanding’ of the DE is needed. It could be an active training or interactive learning unit on how to avoid the disposition effect. They expected that reading an information text will lead to a lower disposition effect, only by creating awareness of this particular deviation from rationality and thus increasing self-control. Therefore, they defined an interface change ‘DE Info Text’ consisting of an information text about the disposition effect on the trading screen. In line with current research, they expected this information text to reduce the disposition effect. They tested four hypotheses in the study. H1: The mean disposition effect is lower if ‘DE Info Text’ is offered.  H₂: Mean disposition effect is higher if ‘Trend Indicator’ is present. H_3(a): Trend Indicator’ increases the mean disposition effect, even if ‘DE Info Text’ is present, and H_3(b):  Info Text’ is suited to reduce the mean disposition effect, also if ‘Trend Indicator’ is current. (TREND_INFO \ TREND):   H₄: Trend Indicator’ leads to an increase in the traders’ activity.

The author used primary data in the study from a field experiment, taken in 2011, from a prediction market known as “Kurspiloten,” which is a web-based prediction market designed to forecast the stock exchange value of selected stock indices and commodities weekly. The author explained that for data collection, participants registered for free and traded with play money to avoid incurring losses random sample. The Kurspiloten market was in operation from 9^th February to 25^th November 2011.  During the 84 days, 1912 active users submitted a total of 215,234 orders, which led to 131, 561 transactions. The authors’ filtered invalid data and only valid data left for data analysis. A total of 144 payouts was executed, which represents 12 per product. Calculation on disposition effect was only done for traders who submitted at least 12 orders. Traders who had no chance to realize a gain or loss or those who did not know one benefit or one loss were also left out. Therefore, the disposition effect of only 514 traders was determined.

The author uses several methods of statistical analysis, including mean, Correlation, OLS regression, and ANOVA. Mean is used to derive central tendency of data in question. Correlation is a statistical measure that indicates the extent to which two or more variables fluctuate each other. The method is appropriate because it establishes if there are possible connections between variables. The authors used Correlation in the study to determine the disposition effect influence on the trader’s performance. They looked at the Correlation between the trader profits and the disposition effect as well as their relative rank. The result of Correlation shows that there is no significant relationship between benefits and disposition effect. Also, there is no meaningful relationship between rank and disposition effect.  Correlation between profits and disposition effect was 0.011, and the Correlation between rank and disposition effect was 0.028. Ordinary least squares (OLS) regression is a statistical method of analysis that estimates the relationship between one or more independent variables and a dependent variable. The technique determines the relationship by minimizing the sum of the squares in the difference between the observed and predicted values of the dependent variable configured as a straight line. This method is appropriate because it is a good estimator that is unbiased. The independent variables in the OLS regression in the study are trend indicators, and the dependent variable is the disposition effect. Thus, the author is trying to establish a relationship between trend indicators and disposition effect. The results of the regression show there was no interaction effect between disposition effect and showing visual cues, thus confirming hypothesis 3a and invalidating hypothesis 3b. ANOVA is used to determine whether there are any statistically significant differences between the means of two or more independent groups. This method is appropriate because it evaluates a range of issues. The ANOVA in the study was used to establish the relationship between interaction and the treatment conditions ‘DE Info Text’ and ‘Trend Indicator.’ The result of ANOVA was qualitatively similar to the regression result and showed that there were no interaction effects between the disposition effect and showing visual cues.

Overall results from the study show that the disposition effect can be aggravated by a minute modification of the user interface. The change consists of a simple percentage value and a trend direction arrow showing the trader’s portfolio value, as used by online trading sites throughout the web as a trend indicator for stock prices or similar applications. Surprisingly, even such a small change significantly increases the strength of the disposition effect. As mentioned earlier, this interface change provides traders with a transparent overview of their portfolio positions. The key conclusions from the study done from 514 online traders show that even tiny visual cues can significantly increase the strength of disposition effect. No verification creating awareness for the disposition effect employing textual information could decrease its power. This paper analyzed the disposition effect on an aggregated and individual level in an online prediction market with nearly 2000 active traders and more than 200,000 orders. In line with research, we found a disposition effect at both levels.

Furthermore, we conducted a field study with over 500 traders for which we could measure the individual disposition effect. Although authors could not verify that creating awareness for the disposition effect through textual information could decrease its strength, they could show that even tiny visual cues can significantly increase the strength of the disposition effect. Previous studies show that the disposition effect can have a negative impact on decision performance in trading environments. A future study could examine whether the disposition effect is also affected if trend indicators are used to represent price changes of tradable stocks. The study is generally well done, but there are several threats to validity that are apparent in the study. For instance, the surveys were semi-structured interviews, and the interviewees may have given the responses that they thought that the researcher wanted, which can result in a threat to construct validity from Experimenter Expectancies bias.