A financial market model with confirmation bias

Cafferata, Alessia; Tramontana, Fabio

doi:10.1016/j.strueco.2019.08.004

Cited by 16 publications

(10 citation statements)

References 28 publications

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“…Concerning Figure 8 , it could be noticed that simulated results seem not able to exactly capture the stationarity of real data, even if a decreasing slope can be appreciated for both indexes and assets. In general, it is not easy to explain the existence of volatility clustering [ 82 ], and replicating it by means of a model is difficult and very sensitive to the chosen conditions [ 83 , 84 , 85 ]. In our case, we are not advancing a specific model of trading (as in [ 86 , 87 ], among others) here.…”

Section: Resultsmentioning

confidence: 99%

Noise and Financial Stylized Facts: A Stick Balancing Approach

Biondo

Mazzarino

Pluchino

2023

Entropy

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In this work, we address the beneficial role of noise in two different contexts, the human brain and financial markets. In particular, the similitude between the ability of financial markets to maintain in equilibrium asset prices is compared with the ability of the human nervous system to balance a stick on a fingertip. Numerical simulations of the human stick balancing phenomenon show that after the introduction of a small quantity of noise and a proper calibration of the main control parameters, intermittent changes in the angular velocity of the stick are able to reproduce the most basilar stylized facts involving price returns in financial markets. These results could also shed light on the relevance of the idea of the “planetary nervous system”, already introduced elsewhere, in the financial context.

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Section: Resultsmentioning

confidence: 99%

Noise and Financial Stylized Facts: A Stick Balancing Approach

Biondo

Mazzarino

Pluchino

2023

Entropy

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“…The already existing literature on computational models addressing confirmation bias shows a notable gap between highly abstract models (Pouget & Villeneuve 2012), and models that target very specific topics such as the financial market (Cafferata & Tramontana 2019), attitudes related to climate change policies (Cafferata et al 2021), or cyber-social networks (Mao et al 2020). Usually, abstract models implement very idealized agents and cannot encapsulate all aspects of specific scenarios, which are the subject of the latter models.…”

Section: 7mentioning

confidence: 99%

Confirmation Bias as a Mechanism to Focus Attention Enhances Signal Detection

Vogrin

Wood

Schmickl

2023

JASSS

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Confirmation bias has been traditionally seen as a detrimental aspect of the human mind, but recently researchers have also argued that it might be advantageous under certain circumstances, e.g. when coupled with meta cognition or as a means to arrive at a cognitive division of labor. To test if confirmation bias can improve performance in a perception task, we developed a minimally complex agent-based model in which agents detect binary signals. In our model, biased agents have -compared to unbiased agents -a higher chance to detect the signal they are biased for, and a lower chance to detect other signals. Additionally, detecting signals is associated with benefits, while missing signals is associated with costs. Given these basic model assumptions, biased agents perform better than unbiased agents in a wide variety of possible scenarios. Thus, we can show that confirmation bias increases the fitness of agents and we use an evolutionary algorithm to find optimal bias strengths which make them more successful at detecting signals. We conclude that confirmation bias sensitizes agents towards a certain type of data, which allows them to detect more signals. We discuss our findings in relation to topics such as polarization of opinions, the persistence of first impressions, and the social theory of reasoning.

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“…Fischhoff and Beyth-Marom ( [2]: p.239-260) explained that "confirmation bias has proven to be a catch-all phrase incorporating biases in both information search and interpretation." Confirmation bias may cause individuals to stop collecting information when the evidence collected so far confirms that people want true views or prejudices and may play a role in the emergence and/or other features (e.g., duration, frequency) of speculative bubbles and other important stylized facts in financial markets (Cafferata & Tramontana,[3]). Such natural tendencies in selective collection of information makes the collected information less open-minded and limited, it may greatly affect the market analysis, and becomes a serious problem to the business's operation.…”

Section: Effect Of Confirmation Bias and Survivorship Biasmentioning

confidence: 99%

The Influence of Confirmation Bias and Survivorship Bias on Electronic Industry

Li¹,

Song²,

Zhu³

2022

Advances in Social Science, Education and Humanities Research

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This article explores the practical consequences judgmental biases have on organizations through the use of case study. Specifically, confirmation bias and survivorship bias will be discussed using organizations from the electronic industry. By studying the case of Nokia and Sony, this article aims to explain how the two judgmental biases influence the decision of the enterprises and their marketing pattern. This influence directly contributed to the failure of the smartphone production of the two operations at different points in time. In terms of the existing biases, this article also offers practical suggestions to reduce harmful effects caused by the two judgmental biases. A knowledge management system is introduced as a theoretical solution for confirmation bias and survivorship bias in innovative enterprises.

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A financial market model with confirmation bias

Cited by 16 publications

References 28 publications

Noise and Financial Stylized Facts: A Stick Balancing Approach

Noise and Financial Stylized Facts: A Stick Balancing Approach

Confirmation Bias as a Mechanism to Focus Attention Enhances Signal Detection

The Influence of Confirmation Bias and Survivorship Bias on Electronic Industry

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