Evidence map›Paper›PMID 41886486›Full record

ArticlePloS one2026

Adaptability factors and behavioral biases of investors in frontier markets: An adaptive market hypothesis perspective.

Jannatunnesa Jannatunnesa, Nurul Shahnaz Mahdzan, Abu Hanifa Md Noman

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Jannatunnesa JannatunnesaUM Business School, Faculty of Business and Economics, Universiti Malaya, Kuala Lumpur, Malaysia.ORCID https://orcid.org/0009-0002-7945-252X
Nurul Shahnaz MahdzanDepartment of Finance, Faculty of Business and Economics, Universiti Malaya, Kuala Lumpur, Malaysia.
Abu Hanifa Md NomanFaculty of Social Science, Southampton Malaysia Business School, University of Southampton-Malaysia Campus, Iskandar Puteri, Johor, Malaysia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Adaptive Market Hypothesis (AMH) suggests that investors are imperfect but adaptive, allowing behavioral biases to persist and evolve over time. However, empirical research on how adaptability factors influence these biases in stock investment remains limited, especially in frontier markets. This study examines the impact of adaptability factors on herding (HRD) and overconfidence (OVR) biases among individual investors in Bangladesh, a frontier market. Employing purposive sampling, data were collected through structured face-to-face and online questionnaire surveys from 640 retail investors on the Dhaka Stock Exchange (DSE). Data were managed using the Statistical Package for the Social Sciences (SPSS) and analyzed using SmartPLS 4.0 for Partial Least Squares Structural Equation Modeling (PLS-SEM). The results show that all the external adaptability factors (social influence, consultation with financial advisors, and media) positively influence herding, while the internal adaptability factors (trading experience, self-reflection, and desire for learning) positively influence overconfidence. Financial literacy negatively affects both biases. The study offers insights for policymakers, regulators, and investors on the cognitive and social elements driving biased investment decisions, especially in frontier markets. To the best of the authors' knowledge, this study pioneers a market adaptability model incorporating novel variables, labelled 'adaptability factors', grounded in AMH and bounded rationality.

Indexed as

InvestmentsBangladeshHumansModels, EconomicSurveys and Questionnaires

Identifiers

PMID41886486
PMCPMC13020831

What OpenQuestion holds

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LicenceCC BY
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.