scholarly journals Modeling Psychology in Islamic Wealth Management

2017 ◽  
Vol 9 (10) ◽  
pp. 64
Author(s):  
Ahmed Hamed Al-Abbadi ◽  
Adam Abdullah

This paper proposes a conceptual framework for modeling psychology in Islamic wealth management. Incorporating psychology into finance would significantly contribute to our understanding of the behavior of individual investors as well as market behavior. Utilizing the findings of behavioral finance and financial therapy, along with industry megatrends, Islamic wealth management could step further in fulfilling its ultimate objective of promoting social welfare. This is can be achieved by exploring and identifying the psychological factors that affect the clients’ decision-making and then behaviorally and cognitively helping them to engage in socially-responsible investments, projects and initiatives. In operationalizing this model, financial advisors/wealth managers should adopt a comprehensive client discovery and profiling method and apply Fintech innovations in producing complex analytics and thereby enriching the client experience.

Behavioral finance explains that cognitive biases influences investor decision making. Due to the influence of different behavioral biases investors do tend to make irrational decisions. Behavioral finance has highlighted the failure of traditional finance theories to account for human emotions when making investment decisions. While traditional finance theories disregard human element in decision-making, behavioral finance theories take into account the human phycology while explaining theories. Many studies have found and explained many biases that are exhibited by investors which lead to irrational investment decision making on their part. One among the many the biases herding can be considered among the most important behavior which leads to low quality investment decisions by investors. While compared to studies about herd behavior of institutional investors, the studies about individual retail investors in less. The motive behind this study is to clarify the role of demographic factors and psychological factors that influence herd behavior among individual investors. In this study the impact of demographics and psychological factors on herd behavior was studied. For this survey, primary data was collected using Judgment sampling technique and the results analyzed. Retail investors in Chennai exhibited herd behavior with regard to investment decisions. Eight factors were found to influence herd behavior.


2021 ◽  
pp. 231971452110582
Author(s):  
Pragati Hemrajani ◽  
Rajni ◽  
Rahul Dhiman

The aim of this article is to look at how two psychological factors affect financial risk tolerance (FRT) and financial risk-taking behaviour (FRB) of individual investors. The study also investigates the role of FRT in mediating the relationship between psychological factors and FRB. A standardized questionnaire was used to collect the information. For the study, a total of 303 completed questionnaires were used. The proposed research model was validated and assessed using partial least squares structural equation modelling. The findings revealed some important experiences. Emotional intelligence and impulsiveness have a significant relationship with both FRT and FRB, according to the results. The findings also support FRT’s position as a mediating factor in the proposed research model. The results emphasize the importance of psychological factors in determining an individual’s FRT and FRB. FRT is a complex mechanism that entails more than just psychological considerations. As a result, further research is needed to decide which additional factors financial advisors can use to increase the explained variance in FRT inequalities.


2014 ◽  
Vol 14 (1) ◽  
pp. 59-64
Author(s):  
Jose Fernandes ◽  
Alberto Matsumoto ◽  
Paulo Chagas ◽  
Israel Ferreira

Author(s):  
Marcelo Henriques de Brito ◽  
Paula Esteban do Valle Jardim

This work presents a new approach to behavioral finance with a theoretical contribution by suggesting and discussing with examples a list of group behavioral biases along with established individual behavioral biases, bringing, hence, an additional outlook on how behavioral biases affect financial decisions. While individual behavioral biases are detected in individuals acting alone, group behavioral biases require the scrutiny of group behavior. This awareness may be particularly important to institutional investors, whose decisions basically stem from a committee or a group that will exhibit behavioral biases depending on how the group members interact between themselves when making a decision, which may include negotiation activities and not necessarily be related to personality or hierarchy. The focus on individual investors deciding on personal investments explain the need of work already developed in behavioral finance, which focus on individual behavioral biases, which may be a consequence from either cognitive errors or emotional biases. However, decisions from institutional investors basically stem from a committee or a group that will exhibit behavioral biases depending on how the group members interact between themselves when making a decision. To address the challenge of identifying causes and consequences for unexpected or unsuitable financial decision-making within a group, this work initially retrieves previous work on individual behavioral biases, linking emotional biases and cognitive errors to the “system 1” and “system 2” decision-making framework. Then, a conceptual contribution of this paper, which may be particularly relevant for institutional investors, is to explain with examples - after research and experience - which are the group behavioral biases and their impact upon financial decisions. Individual behavioral biases already acknowledged in other works on behavioral finance are contrasted in this work to the suggested group behavioral biases. Furthermore, this work suggests that there are two broad types of group behavioral biases: group dynamics biases and information-acceptance biases. Each broad type is subdivided into biases related to the structure of the group and biases related to how the group decision-making procedure occurs. Group dynamics biases related to the manner the group is structured are the following: kin bias (belonging bias), harmony bias, and competition bias. On the other hand, group dynamics biases may be sorted according to five different decision-making procedures, namely: herding, fad bias, Plato bias (denial bias), scarcity bias, and home bias.


Author(s):  
Alberto S. Matsumoto ◽  
Jose L. B. Fernandes ◽  
Israel Karlos Ferreira ◽  
Paulo CCsar Chagas

Market Forces ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. 22
Author(s):  
Muhammad Rehan ◽  
Jahanzaib Alvi ◽  
Lubna Javed ◽  
Baber Saleem

Market irregularities and irrational behavior triggered investor’s changes in the stock market, and this has led to an investigation into the impact of various behavioral biases and factors affecting decision-making for individual investors. The quality of individual investor behavior in making stock investment decisions is very important to be understood as a reference of the movement of the capital market. This study investigated the role of behavioral finance and investor psychology in investment decision-making at the Pakistan Stock Exchange (PSE). Using a sample of 147 individual investors, the study established that behavioral factors such as Herding, Heuristic, Market and Prospect that affected the decisions of the investors operating at the Pakistan Stock Exchange (PSE). As there are a few studies in Pakistan related to behavioral finance, so this study mainly contributes to the field of behavioral finance in Pakistan. This study focusses on existing theories of behavioral finance which led to develop the hypothesis. The result of the analysis is that the four variables have greatly influenced the investment decision and return on investment. All behavioral variables have a significant impact on the decision-making process of investors, which led to the acceptance of all assumptions regarding the level of influence of behavioral factors in decision making for individual investors


2021 ◽  
Vol 11 (2) ◽  
pp. 237-248
Author(s):  
Elkunny Dovir Siratan ◽  
Temy Setiawan

The investment decision-making process is influenced by various factors, including financial literacy and demographic factors. This research examines the impact of demographic factors and financial literacy with behavioral finance as a mediation on investment decision making.  This research using structural equation model (SEM) analysis. The result shows that demographic factors through gender, age, education, income, occupation and experience have an influence and cause a specific behavior in investment decision making. Then the financial literacy factor has an influence in reducing negative behavior. Likewise, demographic factors and financial literacy with behavioral finance as a mediation on investment decisions have a positive influence. The existence of behavior that is manages with planning, financial literacy support, and demographic factors owned by individual investors will create an opportunity for market momentum. Which help maximize profit, better investment and portfolio performance, avoid risks, better investment decision, and forming trading strategies.


2014 ◽  
Vol 8 (5) ◽  
pp. 677-687
Author(s):  
Nariaki Nishino ◽  
◽  
Kaoru Kihara ◽  
Kenju Akai ◽  
Tomonori Honda ◽  
...  

Environmental problems must be solved urgently, and sustainable production activities are desired. This study focuses on environmental finance, which is a method of promoting sustainable corporation activities. Environmental finance allows socially responsible investment to directly contribute to corporate activities and sustainable production activities. To clarify the mechanism of eco-friendly investment decision making, 4,843 respondents took a questionnaire survey on investment decision making, based on the framework of prospect theory. The results showed that prospect theory did not always work for environment issues and that people’s attitudes when they decide on eco-friendly investments could be classified to four clusters.


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