Determinants of Individual Investor Behaviour  in Stock Investment Decisions

Pahlevi, Reza Widhar; Oktaviani, Indri Irma

doi:10.26905/afr.v1i2.2427

Cited by 22 publications

(27 citation statements)

References 11 publications

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“…Since the demography of respondents of this research is varied and is not overpowered by any particular groups, it can be concluded that herding bias affects all types of investors. This finding is consistent with findings by Ghalandari and Ghahremanpour (2013), Kengatharan and Kengatharan (2014), Mahanthe and Sugathadasa (2018), Pahlevi and Oktaviani (2018), Sochi (2018), andQasim et al (2019).…”

Section: H2: There Is a Significant Relationship Between Herding Bias With Investment Decisionsupporting

confidence: 92%

“…A lot of the studies found positive significant relationship between herding bias and investment decision. This finding is supported by Kengatharan and Kengatharan ( 2014), Mahanthe and Sugathadasa (2018), Pahlevi and Oktaviani (2018), Sochi (2018), and Qasim et al (2019). H2: There is a significant relationship between overconfidence and investment decision.…”

Section: Relationship Between Herding Bias and Investment Decisionmentioning

confidence: 68%

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Analysis of the Impact of Anchoring, Herding Bias, Overconfidence and Ethical Consideration Towards Investment Decision

Robin

Angelina

2020

j. ilm. manaj.

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Section: H2: There Is a Significant Relationship Between Herding Bias With Investment Decisionsupporting

confidence: 92%

Section: Relationship Between Herding Bias and Investment Decisionmentioning

confidence: 68%

Analysis of the Impact of Anchoring, Herding Bias, Overconfidence and Ethical Consideration Towards Investment Decision

Robin

Angelina

2020

j. ilm. manaj.

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“…It is a human tendency to attach to certain reference points called an anchor. When the investor focuses on such aspects, he may give less importance to long-term trends (Pahlevi & Oktaviani, 2018). -Framing.…”

Section: Literature Reviewmentioning

confidence: 99%

Investigation of the Herding and Contrarian Behaviour of Investors

Maknickienė

Masėnaitė

Stasytytė

et al. 2021

International Scientific Conference „Contemporary Issues in Business, Management and Economics Engineering"

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Purpose – The paper analyses two different paradigms of investor behaviour that exist in the financial mar-ket – the herding and contrarian behaviour. The main objective of the paper is to determine which pattern of investor behaviour better reflects the real changes in the prices of financial instruments in the financial markets. Research methodology – Algorithms of technical analysis, deep learning and classification of sentiments were used for the research; data of positions held by investors were analysed. Data mining was performed using “Tweet Sentiment Visualization” tool. Findings – The performed analysis of investor behaviour has revealed that it is more useful to ground financial decisions on the opinion of the investors contradicting the majority. The analysis of the data on the positions held by investors helped to make sure that the herding behaviour could have a negative impact on investment results, as the opinion of the majority of investors is less in line with changes in the prices of financial instruments in the market. Research limitations – The study was conducted using a limited number of investment instruments. In the future, more investment instruments can be analysed and additional forecasting methods, as well as more records in social networks can be used. Practical implications – Identifying which paradigm of investor behaviour is more beneficial to rely on can offer ap-propriate practical guidance for investors in order to invest more effectively in financial markets. Investors could use investor sentiment data to make practical investment decisions. All the methods used complement each other and can be combined into one investment decision strategy. Originality/Value – The study compared the ratio of open positions not only with real price changes but also with data obtained from the known technical analysis, deep learning and sentiment classification algorithms, which has not been done in previous studies. The applied methods allowed to achieve reliable and original results.

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“…If the enterprise decides to increase its surplus proportion in a given year, its cash dividend will be reduced. Investors adopt a diverse range of assessment criterion, including maximum profitability, minimum risk considerations, company financial considerations, and the advice of experts and friends [58].…”

Section: Application Of Modified Delphi Approachmentioning

confidence: 99%

“…When facing various decisions, people need to consider the influence factors at different levels or assessment indicators. Therefore, scholars have developed the study method of Multi-Criteria Decision-Making (MCDM) in order to solve the issues of analysis, assessment, and decision-making [56][57][58]. This approach can help decision-makers to avoid only considering a single criterion, which cannot lead to a correct, reasonable, and data-based decision.…”

Section: Fuzzy Sets Theory and Fuzzy Analytic Hierarchy Processmentioning

confidence: 99%

Analysis of the Dividend Policy Decision-Making Mechanism of Chinese and Taiwanese Lithium Battery Industries

et al. 2020

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This study mainly focuses on the mechanisms and influencing factors of formulating dividend policies in the Chinese and Taiwanese lithium battery industries. According to the relevant literature, enterprises should consider financial status, project operations, the decision preferences of their executives, and shareholder equity when drawing up dividend policies. This study first uses the Modified Delphi Approach to set up the hierarchy analysis structure, and then use the Fuzzy Analytical Hierarchy Process for the study method. From the empirical results, this study finds that there exist differences between Chinese and Taiwanese lithium battery manufacturing supply chains, in terms of the process and considered factors when making decisions regarding dividend policies. The empirical results of the study show that dividend policies of Chinese lithium battery manufacturers emphasize more on the future growth of enterprises, earnings expectation and retained earnings, investment decisions, enterprise scale, and operating performance and profit whereas Taiwanese lithium battery manufacturers focus more on information asymmetry.

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Determinants of Individual Investor Behaviour in Stock Investment Decisions

Cited by 22 publications

References 11 publications

Analysis of the Impact of Anchoring, Herding Bias, Overconfidence and Ethical Consideration Towards Investment Decision

Analysis of the Impact of Anchoring, Herding Bias, Overconfidence and Ethical Consideration Towards Investment Decision

Investigation of the Herding and Contrarian Behaviour of Investors

Analysis of the Dividend Policy Decision-Making Mechanism of Chinese and Taiwanese Lithium Battery Industries

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