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Record W2034671104 · doi:10.5539/ibr.v5n3p40

Factors Affecting the Disposition Effect in Tehran Stock Market

2012· article· en· W2034671104 on OpenAlexvenueno aff
Reza Tehrani, Niloofar Gharehkoolchian

Bibliographic record

VenueInternational Business Research · 2012
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFinancial Markets and Investment Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsDisposition effectOverconfidence effectDispositionPsychologyRegretStatistical significanceSocial psychologyEconometricsStock exchangeEconomicsStatisticsMathematicsGeography

Abstract

fetched live from OpenAlex

Given the significance and perceived inevitability of disposition effect and its impact on investment decisions, we investigate factors affecting the disposition effect in the Tehran Stock Exchange. Four hypotheses were developed and the data used in the study were collected through availability sampling. One-sample t-test, two-sample t-test and one-way ANOVA were run to analyze the data while Pearson correlation test and multiple regressions were used to assess relationships among variables in question. The results of the analyses indicate that overconfidence and mental accounting were not significantly correlated with disposition effect. Regret aversion had a positive relationship with disposition effect while self control was negatively associated. It was also observed that there was a negative relationship between participants’ level of education and their disposition effect indicating that the higher the level of education, the less the rate of disposition effect. Furthermore, the results of the study show that males enjoy a higher level of overconfidence than females, and 20 to 30 year-old age groups displayed much overconfidence than other age groups.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.110
Threshold uncertainty score0.844

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.095
GPT teacher head0.333
Teacher spread0.238 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations14
Published2012
Admission routes1
Has abstractyes

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