Abstract

This study examined the behavioural finance and investment process to examine various factors that investors think about before deciding on investments. A selection of investment options based on individual needs and objectives is unique for each investor. This article aims to understand the behaviour of individuals and explain how investments are made. According to Tversky and Kahneman (2015) the gender, tolerance of risk, social culture and religion, and the time horizon are factors that influence comfortability financing and investment decision-making. All of the studied objectives of gender, risk tolerance, social culture, and religion have an important relationship to the investment process. Therefore, this paper focuses in general on investors' behavioural financing and investment decisions.

Introduction

Many people find investment attractive because they can see the results of their choice in the decision-making process. Most investors have reasonable expectations and strive to maximize their usefulness. However, the economist Kahneman and Tversky (2019) argue from their research that the market is not effective, and in particular, people make no rational choices to maximize profits in the short term. Not all investments have profited as investors do not always make the right investment decisions over the years; however, a diversified portfolio should yield positive returns. Kahneman and Tversky (2019) also add that an ideal investment decision is an active part of the portfolio design. Like corporate finance, household finance explains how financial decision-making is managed to ensure financial security and household wealth growth.

Behavioural finance, meanwhile, is a subject that focuses on how individuals and groups act on their financial markets and take decisions, as Virlics (2013) asserts. Additionally, Virlics (2013) also argues that when the economic situation is changing, it shows that the average investor makes decisions based on emotions rather than on logic. Conduct finance acknowledges that in investors' decisions, psychological characteristics play a crucial role.  Psychological studies have shown that there is three times more pain in losing money from investments than the joy of earning money, as argued by Ward (2017). Investors' decisions often have emotions such as fear and desire to play an important role. Thus, studying investors' behaviour helps understand why people purchase or sell shares without doing fundamental analysis, according to Ward (2017).

According to Kahneman (2019), the investment phase is a mentality that involves a series of acts that culminate in the purchase of shares or other alternative investments. As investors, investors enjoy handily beating the market and automatically picking "big" investments. The investment process usually specifies portfolio phases and stresses the sequence of investor awareness behaviour as asserted by Kahneman (2019). He also adds that it provides an intelligent way for an investor to create a portfolio or portfolio by highlighting the sequence. Therefore, if investors want to make money, individual investors must learn the tools based on Loewenstein et al. (2018). Besides, Kahneman (2019) states that the investment process offers a structure in which investors can detect the source of different investment strategies and philosophies. Therefore, investors can follow and track the hundreds of procedures outlined in the common press and the investment newsletters.

Furthermore, the investment method illustrates the various components necessary for a successful investment strategy. It explains why so many well-documented ways struggle to succeed for those who employ them, as Jaiyeoba and Haran (2016) argues. As a result, the aim of this study is to learn more about how individual investors use various factors to influence their financial decisions and behaviour.

Problem Statement

Behaviour finance is an investment behaviour in which all decision-making factors are taken into account. However, Kahneman and Tversky (2019) say that investors influence their decisions and emotions, feelings, and intuition, resulting in irrational behaviour. A female investor, for instance, tends to be less risky than all males. All individual behaviour, mainly if they buy or sell their stock in the markets, will potentially affect investor decision-making. However, in recent decades, Merton (2017) research has shown that optimum and rational decisions are subject to financial knowledge; the more a person knows financially, the more reasonable he will decide.  Investors are not always rational due to these variables, and behavioural assumptions influence their decisions, as Jaiyeoba and Haran (2016) stated. Consequently, it is essential to analyze investment decision-making under behavioural finance theories better to understand investors' real-world experiences better.

Literature review

Gender

Countless research has shown that gender can play a significant part in the behaviour of investors. These behavioural differences certainly affect the performance of the portfolio. For example, Barber and Odean (2016, pg. 286) explain that most men are more active portfolio managers, trading 45% more than women, as stated by Barber and Odean (2016). Women's inability to make investment decisions like men is widely confirmed by research, as women are more risk-averse than men, according to research carried out by Anand and Cowton (2019). Furthermore, the gender gap in financial expertise appears to have a direct effect on investor conduct. According to Barber and Odean (2016), men are more likely than women to have financial expertise, so men are more optimistic when making investments. Their research also discovered that the mutual fund industry is dominated by men, with just ten per cent of women working in the industry. In this case, it is shown that women have a better understanding of how to spend their money. Moreover, the previous Anand and Cowton (2019) study showed that risk behaviour among men and women could not be identical due to economic conditions.

Risk Tolerance

Grable (2017) states that Risk tolerance generally refers to the extent of market risk variabilities, such as volatility or market growth, and the investors’ willingness to withstand losses as things go to the south. "Everyone's risk tolerance will be different," Charlie Horonzy says from a certification financial planner Grable (2017, pg. 627). Risk tolerance is positively linked to various personality traits such as age, sex, marital status, income, education, financial awareness, and aspirations, according to Grable (2017). Grable (2017) looked at the two-stage risk response, a cognitive evaluation, and investors' emotional reaction. These two phases of the reaction are related but fundamentally different. According to Schooley and Worden (2019), investors have unknown odds, results, and returns.

Jaiyeoba and Haran (2016) assert that Risk-averse decision-makers predicted utility function is concave, implying that the decision-maker has a smaller margin. They also add that the risk-taking form of decision-maker, on the other hand, has an increasing marginal utility and a convex anticipated utility function. Furthermore, there is a mixed category of decision-maker, implying that the decision-maker does not fit into any previous categories or acts differently in various situations. Grable (2017) looked at the risk-neutral form, which occurs when an individual uses a linear function to optimize expected benefit and expected utility.

Social Culture and Religion

Jamaludin studies (2013) found that culture and convictions influence how individuals make economic choices and investment choices in everyday life, including economic decisions, religion, and culture. In traditional terms, Jamaludin (2016) argues that the financial theory emphasizes risk and returns as important considerations when constructing a portfolio. However, according to Anand and Cowton (2019), a growing number of investors want to consider moral and social issues when making investment decisions.

Jamaludin (2016) explains that in Islam, it is essential to have a thorough understanding of Islamic law sources that the Shariah originates from Qur'an and Sunna (primary sources), and the views of learned lawyers (secondary sources) are interpreted according to them. Moreover, Kahneman (2019) states that legal professionals' opinions should only be used as additional sources of law if there is silence on the two main sources. Indeed, the majority of Muslims in Malaysia are devout Muslims who follow the teachings of Islam. Ward's (2017) research is closely related to the study in that it believes religion has an effect on individual investment decision-making.

Time Horizon

The word "time horizon" typically refers to how long an investor plans to invest and how much risk he or she is willing to take on, as Gunthorpe and Levy (2020) assert. Short- and long­ term time horizons are two words that are used interchangeably. Short-term cycles last less than three years, while long-term periods last more than ten years, as Gunthorpe and Levy (2020) suggest. Gunthorpe and Levy (2020) discovered that the longer the time horizon for an asset to be included in a portfolio, the more important it is. Furthermore, according to Ward (2017), families prefer the long-term horizon for their decision-making preparation because it is normally passed on to the next generation. The Schooley and Worden overview (2019) shows that, compared to short-term investors in the past, long-term investors spend a large percentage on risky investments. Gaspar et al. (2019, p. 151) posit that the time horizon  effect on optimal risk-taking depends on the statistical relationship between current returns and future returns. A long-term horizon could generate more risk-taking, especially in the case of a mean reversal. Lubatkin et al. (2017) have identified the short-term investment not investing in an equally risky project, but with lower returns and equivalent returns, but the increased investment risk continues to decrease over time.

According to Gaspar, Massa, and Matos (2019), investors with a shorter history have less incentives to spend on resource monitoring because they are less likely to stay shareholders long enough to profit. You also have less time to get to know the company. According to Veld­ Merkulova (2019), the proportion of risky financial assets has risen over time despite investors' years. Based on a Jaiyeoba and Haran (2016) study, being a long-lasting investor is essential to avoid investment losses. This is important rather than short-lasting investors.

Why Traders Might be Subject to the Disposition Effect

The "disposition effect," according to Weber and Camerer (2018), is the tendency to sell value-added assets ("winner") that retain value-added investments ("lost"). The prospect theory can describe disposition effects in two ways: the notion that people value gains and losses concerning a benchmark (the initial purchase price of shares) and the tendency to risk when faced with potential losses and avoid risk when there is a certain amount of profit. According to Weber and Camerer (2018), their studies will be conducted to see if they show the findings. Six risky assets were acquired and sold by the participants. Asset values fluctuated at all times. Unlike Bayesian optimization, topics preferred to sell winners and retain losers. The disposition effect was significantly reduced when the shares were automatically sold after each stage. According to Weber and Camerer, the disposition effect will harm investors' returns in  other ways and increase taxes (2018). The stock's return is cyclical, and investors who sell too fast risk losing their profits.

Data Collection and Sampling Method

The data in this research were gathered by Jaiyeoba and Haran (2016) using Google Docs as the medium in an online survey method. Jaiyeoba and Haran (2016) also used online surveys because their location is cheaper and convenient and can reach people. Therefore, Jaiyeoba and Haran (2016) used twenty questions in the questionnaire, five of which are demographic, and the other 15 relating to their research. Kahneman arranges the questions such that the demographic questions are in Section A, the risk tolerance issues in Section B, the social cultures & religions in Section C, and the time horizons in Section D. The questions are all in the form of statements, excluding demographic issues, in which the respondents must decide what to do, and agree with the statement as asserted by Jaiyeoba and Haran (2016). Additionally,  Jaiyeoba  and  Haran (2016) used an interval scale with the strong agreement, neutrality, disagreement, and vigorous disagreement with answers' choices. The experienced investor in the study area completed and responded to 60 questionnaires as asserted by Jaiyeoba and Haran (2016). Jaiyeoba and Haran (2016) also collected primary data from respondents' data via the questionnaire presented concerning primary and secondary data.

Data Analysis Method

According to Kahneman (2019), IBM's Statistical Social Science Package (SPSS) is the best analytical approach. This is software that provides advanced statistical analysis to execute the information acquired from their research. Kahneman (2019) states that the high volume of data is stored in SPSS, and the software carries out several analyzes. SPSS can carry out analyzes of reliability, descriptive, t-test, regression, and correlation analyzes. It is a convenient and user­ friendly application that students can use with the lecturer's guidance.

The Extent to Which Experimental Evidence Relates to the Empirical Results

The Theoretical Framework

The theoretical framework is essential for all research, Dickason (2017) states, to clarify the theory implicitly in a more clearly defined way. Dickason (2017) also claims that theoretical framework enables researchers to consider their limitations and approaches that challenge their perspectives. Theoretical data are defined as the data collection process for generating theory.

The analyst collects, codes, and analyzes the data and decides which data to collect next and find it to develop the approach, as Dickason states (2017). One of the advantages of theoretical data is that the collection, coding, and analysis process is considerable and straightforward during the academic sampling process to generate a theory (2017). This sampling is closely linked to the Merton-based theory methodology (2017). Besides, since it is a highly systemic process, the theoretical sampling method's application requires more resources, such as time and money, than numerous other sampling methods, the disadvantage of the theoretical data stated by Weber and Camerer (2018). The practical application of theoretical sampling is not subject to transparent processes or guidance.

The Experimental Data (Framework)

Jaiyeoba and Haran (2016) present the data in Table 1, which shows that 50,0 per cent of the responses received come from women in 60 responses. The rest of the 50,0 per cent of reactions are from men. The research conducted by Jaiyeoba and Haran (2016) found out that 10.0% of their respondents aged between 19 and 21 are the least respondents. 30% of respondents are between 22 and 24 years of age. In the meantime, from 25 to 27 years, a total of 15 per cent contributed. Jaiyeoba and Haran (2016) received 45 per cent of the total respondents from people 28 years of age. 53.3% of their respondents are single, and 46.7% are married, as indicated in the table below. Besides, Jaiyeoba and Haran (2016) assert that at least a bachelor's degree was obtained by most respondents, who were 58.3%. A total of 26,7 per cent of them have a degree. 10% of respondents holding only a master's degree. Finally, Jaiyeoba and Haran (2016) observed that the PhD level is the least 5.0% of their respondents' qualifications. In Table 2, the proportion of respondents with stock investment experience is 100%, as shown in Jaiyeoba and Haran (2016) research.

Table 1: Thepro file of the Respondents

Table 2: Stock Investment Experience Responses

According to Jaiyeoba and Haran (2016), the advantage of these experimental data is that researchers have control over all variables, and it provides a greater transferability compared to other anecdotal research. On the other hand, Jaiyeoba and Haran (2016) show the demerits of experimental data as an approach subject to human error. The sample used is not likely to be representative.

The Neurological Data (Framework)

Jaiyeoba and Haran (2016) conducted a study in which they measured their intellectual activity using functional magnetic resonance imaging and subject trade stocks on an experimental market. All trade-in all subjects is inadequate. Jaiyeoba and Haran (2016) have been using neural data to test their behaviour. Jaiyeoba and Haran (2016) found that the activity exemplified by the predictions of realization usefulness in the two brain areas important to economic decision- making. These results support the utility model for implementation. More generally, neural data can help test investment behaviour models.

Reliability Test

According to Table 3, Jaiyeoba and Haran (2016) show that the study's first-time horizon factor is the highest alpha in Cronbach of 0.635, which indicates that their scale with this specific example is highly consistent in its internal composition. Risk tolerance at 0.585 is Cronbach's second-highest alpha. The lowest alpha of Cronbach in social culture and religion, on the other hand, is just 0.417. This shows that their scale with this specific sample is unacceptable because of low internal coherence and internal inconsistency. Jaiyeoba and Haran (2016) present the 5 items in Section B, asserting that the alpha coefficient is .585, which suggests that the items are relatively uniform internally. This also shows reliable variance for 56.6 per cent of results. As a solution, Jaiyeoba and Haran (2016) show some items can now be removed from the questionnaire "Risk Tolerance." The alpha coefficient increases to .616 with the removal of item QBl. In Section C, the alpha coefficient of the 5 items is .4417, which shows a relatively small internal consistency for each item. It also means there is a confident variance in 43.1% of the scores, according to Jaiyeoba and Haran (2016) research. As a solution, certain things can be removed from the questionnaire "Social Culture & Religion." The alpha factor rises to .486 by removing item QC3. The removal of QC3 is suitable, as Jaiyeoba and Haran (2016) argue.

The 5 items in Section D have an alpha coefficient of .635, which suggests that the items are relatively small internal consistency, as shown by Jaiyeoba and Haran (2016). 63.8% of the results show reliable variance. In the "Time Horizon" questionnaire, Jaiyeoba and Haran (2016) remove certain items as a solution. The alpha coefficient is increased to .637 by removing item QD4. QD4 removal is advisable, as stated by Jaiyeoba and Haran (2016).

Jaiyeoba and Haran (2016) used the Independent T-test to compare means between two unrelated groups of the same continuous dependent variable.

Table 4: The T-test result of investment decision

Additionally, Jaiyeoba and Haran (2016) used a p-value of 0.05 as the cutoff for meaning in these independent t-test analyses. According to Jaiyeoba and Haran (2016), the null hypothesis that the p-value is less than 0.005 is dismissed, and Jaiyeoba and Haran (2016) conclude that there is no difference between the media. If the p-value is more significant than 0.05, it's impossible to state a substantial difference, as Jaiyeoba  and Haran (2016) assert. Consequently, Sections B, C, and D are not relevant, according to their findings. As a result, Jaiyeoba and Haran (2016) state that the null hypothesis is accepted.

Theoretical, experimental and neurological sources can be synthesized effectively, according to Dickason (2017), since they are all designed to quantify the problem by generating numerical  or  transformable  data  into  utilizable  statistics.  Dickason  (2017)  also  asserts  that attitudes, opinions, behaviour, and other variables are quantified and results generalized from an increased population of samples are quantified.

Conclusion

In conclusion, this study is designed to assess the factors that affect investor  decision­ making. Data from 60 respondents were collected, focusing primarily on experienced investors from the area of study. According to Tversky and Kahneman (2015) the gender, tolerance of risk, social culture and religion, and the time horizon are factors that influence comfortability financing and investment decision-making. All of the studied objectives of gender, risk tolerance, social culture, and religion have an essential relationship to the investment process. Jaiyeoba and Haran (2016) found that only the time horizon, which results in 0.635, is acceptable from the reliability analysis factor. The lowest alpha in Cronbach, with only 0.585 and 0.417, is risk tolerance and social culture & religion. This shows that this specific sample scale is unacceptable because of low internal coherence and internal inconsistency.

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