The Behavioral Analysis and Financial Performance of Individual Investors at Pakistan Stock Exchange

Mahmood, Tahir; Ayyub, Rana Muhammad; Imran, Muhammad; Naeem, Saira; Abbas, Waseem

doi:10.32479/ijefi.10112

Cited by 7 publications

(6 citation statements)

References 29 publications

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“…The results of this study are in line with the research of [13,17,28,30,38,46]. This is because investors who have an anchoring bias will focus on the issuer's historical stock prices, dividend history, and profitability through horizontal and vertical analysis [31]. This means that investors who have an anchoring bias continue to conduct stock analysis as they should, however, stock investment decisions are made irrational.…”

Section: Data Analysis and Discussion Of Findingsupporting

confidence: 84%

Covid 19: Investment Decisions of Individual Investor Based on Behavioral Finance Factors

Afriany¹,

Putranti²,

Herdiany³

et al. 2022

Proceedings of the 1st UPY International Conference on Education and Social Science (UPINCESS 2022)

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Positive achievements in trading and investment are reflected in the increasing public interest in investing in the Indonesian capital market. In theory, EMH assumes that there are many rational investors who try to maximize profits. Behavioral finance theory is an empirical study of contradictions that proves that investors are not completely rational. This is because there are psychological factors that influence investment decisions. The existence of this human psychological factor makes various financial decisions bias. This study aims to determine and analyze the effect of several behavioral biases, namely overconfidence bias, anchoring bias, and herding on stock investment decisions in Indonesian investors. This research is a quantitative and survey research with primary data. The research population includes individual stock investors in Indonesia. The sampling technique used is purposive sampling. The sample obtained was 129 respondents. The statistical method for testing the data is Structural Equation Modeling-Partial Least Square (SEM-PLS) with SmartPLS Version 3.0 software. Statistical test results show that overconfidence bias has a positive and significant effect on stock investment decisions, anchoring bias has a positive and significant effect on stock investment decisions, herding behavior is formed when investors adopt the actions of others, in this study herding has a negative and significant effect on stock investment decisions.

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Section: Data Analysis and Discussion Of Findingsupporting

confidence: 84%

Covid 19: Investment Decisions of Individual Investor Based on Behavioral Finance Factors

Afriany¹,

Putranti²,

Herdiany³

et al. 2022

Proceedings of the 1st UPY International Conference on Education and Social Science (UPINCESS 2022)

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“…A closer look at the literature reveals several gaps and shortcomings. The studies conducted in Pakistan focused on behavioral biases and investment decision making of investors (Ali et al, 2021; Anum, 2017; Asab et al, 2014; Aurengzeb, 2022; Ayub, 2018; Badshah et al, 2014; Farooq & Sajid, 2015; Ishfaq, 2015; Khan et al, 2018, 2021; Mahmood et al, 2020; Mumtaz & Ahmad, 2020; Parveen et al, 2021; Quddoos et al, 2020; Rasheed et al, 2018; Raza, 2014; Rehan et al, 2021; Zafar & Siddiqui, 2020). This study contributes to explore the investment behavior in blue-chip stocks with mediating role of risk perception.…”

Section: Introductionmentioning

confidence: 99%

Mediating Role of Risk Perception Between Behavioral Biases and Investor’s Investment Decisions

Ahmed

Rasool²,

Saleem

et al. 2022

Sage Open

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This study aims to examine the direct and indirect links between behavioral biases and investor’s investment decisions via the mediating role of risk perception through structural equation modeling. The study is conducted among individual investors who are engaged in investment for several years in Pakistan Stock Exchange. Purposive sampling technique was used for data collection and the sample size was consisted of 450 questionnaires. The findings contribute that risk perception mediates between blue-chip stocks and investment decisions. Furthermore, risk perception does not play the mediating role between herding bias, disposition effect, and investment decisions. However, the disposition effect has a strong direct relationship with risk perception. The study is beneficial to individual investors who can make investment decisions by self-estimation rather than to follow the others’ opinion. The proper training and education to the investors is also an appropriate path to overcome these biases. Risk is the major factor that discourages investment decisions but blue-chip stocks are a major risk eliminating factor while building investment decisions. Most of the prior studies focused on behavioral biases and investment decisions of individual investors but this study contributed to the mediating effect of risk perception. Human capital, anomalies, computer literacy, and artificial technology could also be used as a mediator and moderator for future orientation.

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“…In the paper (Mahmood et al, 2020), investing decisions and their resulting results are examined to ascertain the influence of behavioral elements. The primary data was obtained by distributing questionnaires to individuals who regularly engage in activities within the Pakistan Stock Exchange.…”

Section: Behavioral Analysismentioning

confidence: 99%

Stock market and securities index prediction using artificial intelligence: A systematic review

Singh,

Malhotra

2024

Multidiscip. Rev.

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The recognition of the value and importance of recognizing patterns in the stock market is widely accepted. As a result, using innovative decision-making strategies is expected to lead to significant returns in stock prices. Predicting the stock market proves challenging because of the limited volatility and inherent disorderliness observed within the data. Hence, investors need help optimizing their profits through informed predictions in the stock market. Stock market projections are made by employing mathematical approaches and machine learning methods. The stock market is inherently vulnerable to unforeseen changes due to its intricate nature and absence of a linear progression. Since the advent of personal computers and the proliferation of technological advancements in the 1990s, scholars have investigated the application of artificial intelligence in the investment sector. Many solutions have been created to tackle the matter of volatility in stock market prices. This study examined a total of 146 research articles that were published in academic journals over twelve years (2011-2023). These papers focused on applying artificial intelligence in predicting stock market trends. The listed works encompass several methodologies, including technical analysis, fundamental analysis, sentiment analysis, and time series analysis. Every academic field is comprehensively explored, encompassing its initial findings and most recent advancements. Moreover, the existing body of literature suggests a growing focus on this particular sector, with a heightened level of specialization and an expanded range of topics being explored.

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The Behavioral Analysis and Financial Performance of Individual Investors at Pakistan Stock Exchange

Cited by 7 publications

References 29 publications

Covid 19: Investment Decisions of Individual Investor Based on Behavioral Finance Factors

Covid 19: Investment Decisions of Individual Investor Based on Behavioral Finance Factors

Mediating Role of Risk Perception Between Behavioral Biases and Investor’s Investment Decisions

Stock market and securities index prediction using artificial intelligence: A systematic review

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