Investor's information processing and expectation formation is biased by circumstances, e.g. in terms of current investment position (gain or loss) and favorability of the news (Grosshans, Langnickel and Zeisberger, 2021; Khunen and Knutson, 2011; Khunen, 2015; Trutmann, Heinke and Rieskamp, 2022). These distortions in the beliefs also affect trading behavior and have a detrimental impact on investor's profits.
OBJECTIVE. This study aims to explore a different angle of the phenomenon and to provide an intervention within the scope of regular investment advice.
MECHANISM. The potential point of attack we aim for in this study is a reduction of the perceived engagement with the results of a decision. We argue, that it is partially the involvement with the decision making over the course of a price path that leads to distortions in belief updating. It has been shown that distancing oneself from previous decisions can improve the success of subsequent ones (e.g. Chang, Solomon & Westerfield, 2016; Heinke, Trutmann and Rudin, 2021; Rotaru, Kalev, Yadav and Bossaerts, 2021) and we argue that the same holds for the updating of beliefs. The role of involvement is also supported by findings showing that whether an asset is owned or not influences how beliefs are updated (Hartzmark, Hirshman & Imas, 2021) and studies showing that sometimes even less information can lead to more favorable investment outcomes (Mosenhauer, 2020). Such mental distance can help avoid the influence of mechanisms such as regret aversion and cognitive dissonance, which may underlie the belief effects found in Trutmann et al. (2022). Thus, we aim to mitigate belief effects through lowering participants' engagement with the development of their investments once those investments have been made. We expect such a reduction of the involvement to improve the quality of the belief updates and decisions. The reduction of involvement will be achieved by either blocking participants from trading decisions for several rounds or providing the information bundled once a number of rounds have passed. Note, such interventions would not improve but most likely worsen the success of a rational Bayesian decision maker. For such a decision maker receiving more information about future changes in value as early as possible, and being able to act on that information, should lead to more profitable outcomes.
EXPERIMENT. In an investment task participants can learn from observing prices whether an asset has an upward or downward drift (.65 or .35 probability of a price increase respectively, with the price changing in each round). This drift will be fixed in each block consisting of nine rounds. Participants will be endowed with a random portfolio and observe the the price movement in the first three rounds without any decisions to take. In the baseline condition for rounds four to nine participants make trading decisions and we ask for their belief on a price increase in the next round. We expect belief updates to be more in line with a Bayesian- or unbiased update when engagement with the price development is lowered. This will be done by two manipulations: in the "blocked trading" condition participants will make an initial investment, which will then remain unchangeable for five of rounds. As they do observe the price chances for each round we also elicit their expectations about a price increase in the upcoming round. In a second intervention condition, the "blocked information" condition, participants will not only be blocked from changing their investments for a period of five rounds but in addition will only receive information about the price changes at the end of the five rounds in a list format. We expect this "bundling" of the information to provide an additional emotional distance to investors. Bundling the information in such a way further gives participants a dedicated time to update their beliefs which may be similarly beneficial as providing time to deliberate in general (Imas, Kuhn & Mironova, 2016).
To reduce the effect of individual differences this will be run as a within-subject study. Each participants plays eight blocks of each of the three conditions, thus 24 blocks in total. The allocation of conditions across all of the 24 blocks is a random draw and participants are informed about the procedure of the current condition at the beginning of each block. To reduce the noise induced by a random price draw, eight price paths are generated for each participant, each of which is presented once in every condition. These combinations of price-path and condition are then presented in randomized order.
Chang, T. Y., Solomon, D. H., & Westerfield, M. M. (2016). Looking for someone to blame: Delegation, cognitive dissonance, and the disposition effect. The Journal of Finance, 71(1), 267-302.
Grosshans, D., Langnickel, F., & Zeisberger, S. (2020). Is Buying more Forward-Looking than Selling? The Role of Beliefs in Investment Decisions. The Role of Beliefs in Investment Decisions (July 8, 2020).
Hartzmark, S. M., Hirshman, S. D., & Imas, A. (2021). Ownership, learning, and beliefs. The Quarterly Journal of Economics, 136(3), 1665-1717.
Heinke, S., Trutmann, K., & Rudin, C. (2021). Hire Someone to Blame: Degree of Involvement in Decisions and the Likelihood that Professionals Will Stop Investing after Experiencing Losses. Available at SSRN: https://ssrn.com/abstract=3892106 or http://dx.doi.org/10.2139/ssrn.3892106
Imas, A., Kuhn, M., & Mironova, V. (2016). Waiting to choose: The role of deliberation in intertemporal choice.
Kuhnen, C. M., & Knutson, B. (2011). The influence of affect on beliefs, preferences, and financial decisions. Journal of Financial and Quantitative Analysis, 46(3), 605-626.
Kuhnen, C. M. (2015). Asymmetric learning from financial information. The Journal of Finance, 70(5), 2029-2062. Mosenhauer, M. (2020). Information Management against Excessive Stock Trading: More or Less? Or Both?.
Rotaru, K., Kalev, P. S., Yadav, N., & Bossaerts, P. (2021). Transferring Cognitive Talent Across Domains: The Case of Finance.
Trutmann, K., Heinke, S., & Rieskamp, J., (2022) Belief Updating and Investment Decisions: The Impact of Good or Bad News Varies With Prior Returns. Available at SSRN: https://ssrn.com/abstract=3935798 or http://dx.doi.org/10.2139/ssrn.3935798