Abstract
The aim of the current research is to provide a model to explain unfavorable risk and favorable risk with regard to psychological variables in predicting market fluctuations in the Iranian capital market. According to its purpose, the research method is applicable-developmental; and in terms of the research method, it is in the category of qualitative research of thematic analysis type. The statistical population of this research includes 18 Iranian capital market experts who have at least 10 years of teaching, research and management experience in the stock market. Purposeful sampling method was used in this research. The method of data collection is referring to documents and semi-structured interviews. For data analysis, Atlas ti software was used to code the interviews. The findings of the research showed that the model for explaining unfavorable risk and favorable risk according to psychological variables includes the model of one overarching theme, five constructive themes, and 23 basic themes. The dimensions of the research include: favorable and unfavorable risk factors, market conditions, psychological conditions, risk control strategies, and success in market forecasting. The research components include: financing, marketing communications, information accuracy, bankruptcy financial indicators, bankruptcy non-financial indicators, political factors, interpretation of fluctuations, economic factors, factors related to the stock market, factors related to the company, brokerages, personality, optimistic behavior, over-trusting behavior, risk-averse behavior, emotional behavior, financial education, monitoring and evaluation, rules and regulations, economic added value, company value, individual satisfaction, and economic growth.
Extended Abstract
Introduction
Individuals may react under the impression of their emotions and personal preferences on economic events, which can have an impact on market volatility. Therefore, the models explaining unfavorable risk and favorable risk according to psychological variables can help to improve the prediction of market fluctuations and understand the influencing factors, which can be very valuable for investors, financial analysts, and economic decision makers (Ajello & Pike, 2022). To manage adverse risk and favorable risk in the stock market, investors must use different tools. These tools include diversifying the portfolio, using the importance of time (proper timing of buying and selling assets), using derivative instruments such as options and futures, as well as using financial and economic analysis to predict market changes. Also, paying attention to global economic conditions and analyzing the impact of current events on the market is very important (Giglio et al, 2016). In general, risk management in the stock market requires a suitable combination of analytical knowledge, financial strategies, and a deep understanding of unfavorable and favorable market factors. Smart decision-making and proper management of risks can help preserve investors' capital and increase their returns (Cortes et al, 2020). According to what has been said, the main question of the present research is: what is the explanation model of unfavorable risk and favorable risk with regard to psychological variables in predicting market fluctuations in the Iranian capital market?
Theoretical framework
Risk
According to the new definitions of risk, which is more compatible with investors' perception of risk, increasing the yield of financial assets is not considered as risk. The conventional definition of risk refers to any fluctuations that include valuable investment opportunities. In the new definitions and the indicators designed based on it, only adverse changes (observations that are less than a certain rate of return) are defined as risk (Yuanfang, 2023).
 
Favorable and unfavorable risk
Optimal risk measures are based on the assumption that upward movements in returns and therefore upward volatility in expected or average returns are also considered risks. On the other hand, favorable risk shows the probability or potential of increasing the yield of an asset or investment, based on a percentage or amount, which can be a measure of the attractiveness or desirability of that asset, and the higher it is, the more attractive the investment (Nikoo et al, 2020). Adverse risk measures the probability that the price of an asset or investment will decline, or the amount of loss that could result from a potential price decline. Adverse risk is an estimate of the potential for an asset to decline in price when market conditions do not go well; or the amount that may be lost on an investment. In other words, it is the part of risk that has a negative effect on investment. Adverse risk is a measure of risk that measures the difference between a risky position and its opposite risk-free position, and considers only unfavorable deviations.
Traut (2023) presented a research entitled: 'What we know about low-risk anomaly: a literature review'. This paper concludes that, despite some criticisms, there are good reasons to believe that the low-risk anomaly can be evaluated as an investment factor. It also indicates that more research is needed to disentangle the proposed causes to fully understand the big picture of the anomaly with certainty.
He et al, (2023) presented a research titled investigating favorable and unfavorable risk jumps in dynamic processes of three rates: domestic interest rate, foreign interest rate, and exchange rate. To bridge the gap between the asymmetric jump in the foreign exchange market and current models, a correlated asymmetric jump model is proposed to show the co-movement of related jump risks for three rates and identify the related jump premium. The results of the likelihood ratio test show that the new model performs best in 1, 3, 6 and 12 months maturities. The in- and out-of-sample test results show that the new model can capture more risk factors with relatively small pricing errors. Finally, the risk factors captured by the new model can explain exchange rate fluctuations for different economic events.
Research methodology
According to its purpose, the research method is applicable-developmental; and in terms of the research method, it is in the category of qualitative research of thematic analysis type. The statistical population of this research includes 18 Iranian capital market experts who have at least 10 years of teaching, research and management experience in the stock market. Purposeful sampling method was used in this research. The method of data collection is referring to documents and semi-structured interviews.
Research findings
For data analysis, Atlas ti software was used to code the interviews. The findings of the research showed that the model for explaining unfavorable risk and favorable risk according to psychological variables includes the model of one overarching theme, five constructive themes, and 23 basic themes. The dimensions of the research include: favorable and unfavorable risk factors, market conditions, psychological conditions, risk control strategies, and success in market forecasting. The research components include: financing, marketing communications, information accuracy, bankruptcy financial indicators, bankruptcy non-financial indicators, political factors, interpretation of fluctuations, economic factors, factors related to the stock market, factors related to the company, brokerages, personality, optimistic behavior, over-trusting behavior, risk-averse behavior, emotional behavior, financial education, monitoring and evaluation, rules and regulations, economic added value, company value, individual satisfaction, and economic growth.
Conclusion
The current research was conducted with the aim of providing a model to explain the unfavorable risk and the favorable risk according to the psychological variables in predicting market fluctuations in the Iranian capital market. The results of this research are in agreement with the results of Lu et al, (2023), Traut (2023), Xiang & Borjigan (2023), He et al, (2023), Shahrzadi & Foroghi (2022), Shah et al, (2022), Racicot & Theoret (2022), Ali et al, (2022), Dasineh et al, (2021), Rad kaftroudi et al, and (2020). Xiang & Borjigan (2023) showed that linear and non-linear risk spillover networks at different risk levels show different topology characteristics; they are unevenly distributed at each risk level. At the system level, there is a significant difference in uniqueness and overlap between linear and non-linear risk spillover networks. At the sector level, financial sectors (such as DF and RE sectors) can generate a certain spillover effect on real economy sectors across the quantile, but the net spillover effects of financial sectors are smaller than that of some real economy sectors. Finally, crisis shocks affect the risk spillover effects between the financial sectors and the real economy. In the downward and upward cases, the spillover effects between sectors are greater in the crisis period than in the pre-crisis period.
According to the results of the research, the following suggestions were presented:
It is suggested that investors always carry a notebook with them when reviewing their investments and record all their reasons and opinions, feelings, and emotions about their investments in that notebook and read it once in a while.
It is suggested to financial advisors that before giving any kind of financial advice to the clients, the personality type of the people and the level of their willingness to perceptual errors should be measured and checked, and adjust the portfolio of the people or attempt counseling based on that.