Volume 23, Issue 3 (Autumn 2021)                   Advances in Cognitive Sciences 2021, 23(3): 135-148 | Back to browse issues page


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Naghikhani M, Hatami J, Jahanitabesh A, Kiani K. Effect of description-experience learning on cognitive shifting process and decision-making outcome in stock market. Advances in Cognitive Sciences 2021; 23 (3) :135-148
URL: http://icssjournal.ir/article-1-1303-en.html
1- PhD Student of Cognitive Psychology-Social Cognition, Institute for Cognitive Science Studies (ICSS) and Researcher Fellow, Statistical Research and Training Center (SRTC), Tehran, Iran
2- Associate Professor of Psychology, Department of Psychology, Tehran University, Tehran, Iran and Institute for Cognitive Science Studies (ICSS), Tehran, Iran
3- Lecturer and Postdoctoral Researcher, University of California, Davis, USA
4- Lecturer in Data Science, School of Science, Engineering & Environment, the University of Salford, Manchester, United Kingdom
Abstract:   (896 Views)
Introduction
William James (1890) defines the relationship between thinking and habit as follows: thinking is an interruption between habits, and humans are constantly shifting cognitively between thinking and habit (7). The cognitive shifting process between thinking and habit has received various supports from numerous studies. Sutton & Louis supposed a cognitive switching gear to shift cognition between conscious and automatic modes (13). Time to stabilization and time to flexibilization are two characteristics of this shifting. Time to stabilization and flexibilization is defined as the time to sense the right conditions for shifting the conscious mode to automatic mode and automatic mode to conscious mode, respectively.
In the stock market, the environmental conditions are constantly shifting between low volatile (stationary conditions) and high volatile (nonstationary conditions), and it is supposed that this shifting is in progress. In this constantly changing environment, decision-makers’ cognitive abilities can be developed so that they become more flexible to high volatility and more stable to the low volatility in the stock market. These cognitive abilities of this process can be developed through learning approaches such as experience and description learning. In experience learning, experience is a vector of learning information that results from interaction with the environment and human characteristics. In contrast, in description learning, learning displays a problem’s status as a number, sentence, or image.
Accordingly, the present study aimed to investigate the cognitive shifting process in stock market decision making and determine the effect of description-experience learning on the two characteristics of the cognitive shifting process (time to stabilization and time to flexibilization) and decision-making outcome. In addition, the effect of statistical literacy and risk tolerance on the two characteristics and decision-making outcome were analyzed as a second goal in this regard.
Methods
In a time-series study, 54 participants randomly allotted to experience learning group (n=30, M=32.3, SD=7.2) and description learning group (n=24, M=30.3, SD=11.2). Participants were instructed to buy and sell shares of 5 virtual companies for 60 days, based on their bank account balance, the value, and the number of shares offered to each company. Almost all participants completed every investment simulation in less than 30 minutes, excluding the possibility of seeking background information. Decisions could be based only on share price trends. The experiment was performed consecutively in two 30-day periods. Within the first thirty days, a calm and low volatility stock market was designed for investment. During the second 30-day period, the market was simulated in unstable and high volatility. The random walking method was used to simulate the stock price. This configuration allowed participants to find and follow optimal investment strategies for maximizing their investment returns (36).
The stock market simulated system was designed in an Excel environment for two learning groups and was provided to participants via email on a daily basis. The system was designed in two ways to fit the two learning groups. In the first group, a simulated stock market environment was designed for the experience learning group, which included five companies, information on the number of shares presented, and the price per share was provided to participants. In the second group, for the descriptive learning group, in addition to the information provided in the experimental learning group, a representation of the information in the form of risk for each company was provided to the participants on a daily basis.
Participants’ statistical literacy was assessed using a researcher-made questionnaire, and the FinaMetric questionnaire was used to measure participants’ risk tolerance. In addition, multiple change-point detection methods and stationery tests were used to study the cognitive shifting process, and multivariate analysis of covariance was used to analyze the data in SPSS-26 and R software.
Results
In the present study, time to stabilization and flexibilization were considered as dependent variables based on changing the distribution behavior or changing the data trend over the 60 days of trading. Time to stabilization refers to the day when the participant's daily decision-making time distribution or trend, changes to stabilization in the coming days, and time to flexibilization refers to the day on which data behavior becomes unstable. Also, the dependent variable of decision-making output was measured using the net worth. The net worth is equal to the sum bank account balance and the totals invested in shares.
A time series of each participant's decision-making time was extracted over the 60 days of trading to identify the presence of the cognitive shifting process in stock market decision-makers. Time to stabilization and flexibilization were obtained for 54 participants by static test and multiple change-point detection methods. The results showed that there were two change points (time to stabilization and time to flexibilization) in the time series of decision-making time for each participant. Therefore, the hypothesis cognitive shift process between habitual decision making (habit) and conscious decision making (thinking) was supported.
In addition, according to the results of the independent t-test and the U-Mann-Whitney test, the experience-description learning had a significant effect on time to stabilization, time to flexibilization, and net worth. The time to stabilization in the experience learning group was significantly shorter than the description learning group but, the time to flexibilization in the description learning group was less compared to the experience learning group. Also, the mean net worth of participants from description learning was significantly higher than experience learning. In addition, the data showed that the level of risk tolerance had a significant positive effect on the time to flexibilization and net worth, while statistical literacy did not affect the time to stabilization, the time of flexibilization, and net worth. The results showed that investment decision-making could improve by using description learning and high-level risk tolerance. This way, decision-makers also become more flexible in high volatility the stock market.
Conclusion
These findings provided cognitive scientific support for improving stock decision-making. It is to strike a balance between the two seemingly contradictory behavioral dimensions of stability and flexibility. In other words, under risk and uncertainty conditions, effective decision-making requires a continuous cognitive oscillation between the two modes of habitual decision-making (habit) and conscious decision-making (thinking). Because most improvements are associated with learning, this is of particular importance to the field of investment decision-making. There are several ways to improve the characteristics of the cognitive shifting process. One of these methods is description learning. In this type of learning, the problem is represented in different ways. However, the representation of information without considering its analytical power in decision-makers is not effective. In addition, stock market investors could focus on increasing analytical skills of description information, risk perception, and risk tolerance. Also, brokers and stock exchange organizations could publish description information with the least mental effort and cognitive bias for their users. Stock exchange organizations can also prescribe description information analysis and increase the level of risk tolerance as part of users' decision-making strategy. If replicated by future studies, these results will open a new avenue for research and have practical implications for limitation cognitive bias in educational settings.
Ethical Considerations
Compliance with ethical guidelines
The conditions of this study were designed in such a way that there was no physical or mental harm to the study participants. Participants joined in the experiments with satisfaction and knowledge of the test conditions.
Author’s contribution
Mehdi Naghikhani was involved in the study design, data collection, analysis, review and correction, and article writing. Javad Hatami, Azra Jahanitabesh, and Kaveh Kiani were involved in the study design, analysis, and article writing. All authors read and approved the final manuscript.
Funding
No financial support has been received for this research.
Acknowledgments
This article is an excerpt from the dissertation of the Department of Psychology of the Institute of Cognitive Science Study (ICSS) with the same title, and we thank all the participants in this study. Also, we appreciate the efforts of Prof. Warren Thorngate (retired professor at Carleton University, Canada), who contributed to the development of the theoretical foundations of this research. We would also like to thank Dr. Zahra Eskandari (expert in risk), Ms. Maryam Zanganeh and Mr. Farshad Roshan Sangachin for designing the stock market simulation.
Conflict of interest
This study has no conflict of interest with any organization.
Full-Text [PDF 997 kb]   (260 Downloads)    
Type of Study: Research |
Received: 2021/07/10 | Accepted: 2021/09/12 | Published: 2021/11/16

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