magistrsko delo
Katarina Pikec (Author), Günter Strobl (Mentor), Frauke Stehr (Co-mentor)

Abstract

Čredno vedenje na finančnih trgih je pojav, pri katerem vlagatelji posnemajo druge, saj predvidevajo, da imajo drugi boljše informacije. Čredno vedenje je bilo doslej večinoma preučevano s statističnimi analizami tržnih podatkov, medtem ko eksperimentalne raziskave na tem področju ostajajo redke (Komalasari et al., 2021). V nasprotju s preteklimi študijami, ki samozavest obravnavajo kot enoten pojav (Bernardo in Welch, 2001; Chang in Lin, 2015), ta magistrska naloga preučuje vlogo pretirane natančnosti, specifične oblike samozavesti pri vplivanju na čredno vedenje. To smo preučevali z uporabo Banerjeejovega (1992) modela črednega vedenja. Naš vedenjski model napoveduje, da lahko pretirana natančnost do neke mere zmanjša čredno vedenje, saj so posamezniki s pretiranim zaupanjem v svoje zasebne informacije manj nagnjeni k sledenju preteklih odločitev. Za preverjanje te hipoteze predlagamo eksperimentalni načrt, v katerem človeški udeleženci sodelujejo z računalniško simuliranimi agenti v različnih eksperimentalnih pogojih. Model in načrt eksperimenta ponujata strukturiran pristop za oceno vpliva pretirane natančnosti na čredno vedenje v finančnih okoljih. Ta raziskava prispeva k vedenjskim financam s tem, da razlikuje med različnimi oblikami samozavesti in zagotavlja empirični okvir za preučevanje črednega vedenja.

Keywords

čredno vedenje;pretirana samozavest;pretirana natančnost;vedenjski model;finančno odločanje;

Data

Language: Slovenian
Year of publishing:
Typology: 2.09 - Master's Thesis
Organization: UL PEF - Faculty of Education
Publisher: [K. Pikec]
UDC: 159.923.3(043.2)
COBISS: 242367747 Link will open in a new window
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Downloads: 28
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Other data

Secondary language: English
Secondary title: Adaptation of three selected picture books for easy reading
Secondary abstract: Herding in financial markets occurs when investors imitate others, assuming that others possess superior information. While herding has been extensively studied through statistical analysis of market data, experimental research remains limited (Komalasari et al., 2021). This thesis examines the role of overprecision, a specific form of overconfidence, in influencing herding behavior. Unlike prior studies that treat overconfidence as a uniform phenomenon (Bernardo & Welch, 2001; Chang & Lin, 2015), this research incorporates overprecision into Banerjee’s (1992) herd behavior model to analyze its effects on sequential decision-making. Our behavioral model predicts that overprecision can reduce herding to some extent, as individuals with excessive confidence in their private information are less likely to conform to prior decisions. To test this, we propose an experimental design, where human subjects interact with computer-simulated agents under different treatment conditions. The model and experimental design together offer a structured approach to evaluate how overprecision influences herding in financial settings. This research contributes to behavioral finance by distinguishing between different forms of overconfidence and providing an empirical framework for studying herding beyond correlation-based analyses.
Secondary keywords: herding behavior;overconfidence;overprecision;behavioral model;financial decision making;Kognitivna znanost;Univerzitetna in visokošolska dela;
Type (COBISS): Master's thesis/paper
Study programme: 0
Thesis comment: Univ. v Ljubljani, Skupni interdisciplinarni študijski program druge stopnje Kognitivna znanost, v sodelovanju z Universität Wien, Univerzita Komenského v Bratislave in Eötvös Loránd Tudományegyetem ter s Sveučilištem u Zagrebu
Pages: 1 spletni vir (1 datoteka PDF (68 str.))
ID: 26712144