Loss aversion, overconfidence and their effects on a virtual stock exchange

Bertella, Mário Augusto; Silva, Jonathas N.; Stanley, H. Eugene

doi:10.1016/j.physa.2019.123909

Cited by 9 publications

(10 citation statements)

References 15 publications

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“…Using an intraday data for Taiwan stock market, Ho (2013) claims that private information causes an increase in market trading volume and then an increase in return volatility. Bertella et al (2020) argue that when there are only fundamentalists in the stock exchange, no excessive trading volume or excessive price volatility are observed; however, in the presence of a small number of chartist agents, an increase in trading volume and an excessive price volatility appear.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Motivated by this strand of literature, theoretical and empirical studies in behavioural finance have modelled the investors behaviour as an overestimation of the accuracy of their private information signals (Odean, 1998; Wang, 1998). They show that overconfidence influences the investors' behaviour in financial markets and causes overreaction to private information, excessive trading volume and excessive stock price volatility (Bertella, Silva, & Stanley, 2020; Chuang & Lee, 2006; Chuang & Susmel, 2011; Czaja & Röder, 2020; Daniel, Hirshleifer, & Subrahmanyam, 1998; Gervais & Odean, 2001; Merkle, 2017; Statman, Thorley, & Vorkink, 2006).…”

Section: Introductionmentioning

confidence: 99%

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Implications of the overconfidence bias in presence of private information: Evidence from MENA stock markets

Boussaidi

2020

Int. J Fin Econ

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This paper extends the empirical literature on overconfidence by investigating the implications of this bias on the trading activity and the market volatility for different levels of private information. Using individual data for 10 MENA stock markets, we found a positive unidirectional causal relation from market return to trading volume in most markets, indicating that overconfident investors attribute past market gains to their own talent in selecting securities and trade later as if they had generated these gains. Consistent with the hypothesis of the investors' overreaction to private information, we found that the trading activity becomes more excessive as the level of private information increases. Moreover, the overconfidence helps explain the observed excessive volatility in presence of high level of private information.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Implications of the overconfidence bias in presence of private information: Evidence from MENA stock markets

Boussaidi

2020

Int. J Fin Econ

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“…In conditions of uncertainty, regret drove an investor's decision-making away from extremes (Rocciolo, Gheno, & Brooks, 2019). Meanwhile, overconfident investors traded more in options than stocks (Bertella, Silva, & Stanley, 2020;De Bondt, 2020). In terms of cultural differences, individual investors in collectivist emerging economies were prone to behavioral biases which were usually more pronounced than among investors in developed, more individualistic countries (Tekçe & Yılmaz, 2015).…”

Section: Financial Theories and Stock Marketsmentioning

confidence: 99%

Co-Integration among COVID-19, Investor Sentiment, and the Stock Market

Xiao

Aumeboonsuke

2022

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This study focuses on stock market performance during the COVID-19 pandemic, aiming to research the co-integration among COVID-19 cases, investor sentiment, and the stock market. The data for the study comprised index returns, trading volume, turnover rate, and volatility from CSI300 index from January 2020 to December 2021. The paper planned to introduce methods that used the autoregressive distributed lag model, co-integration test, and error correction model to achieve the aims. The results show that there is a long-term co-integration relationship among these variables. However, when we consider the long-term association between COVID-19 and investor sentiment and individual stock market variables separately, we find no association among COVID-19 and market volatility, trading volume, or turnover rates. From the perspective of investor sentiment, there is no long-term relationship between investor sentiment and market volatility. Therefore, the model results show that there is a long-term relationship among the variables only when the data are integrated, but this relationship does not always persist when considering individual variables. As the COVID19 still continues, the study results would have the implications for the investment decision-making and risk avoidance to face the pandemic.

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“…Chen et al [34] found that firms led by overconfident CEOs are less responsive to corrective feedback in improving management forecast accuracy. Adebambo and Yan [35] showed that investor overconfidence is significantly related to firm valuation and corporate decisions, and Bertella et al [9] studied the effects of overconfidence and loss aversion in an artificial stock exchange.…”

Section: Overconfidence Theorymentioning

confidence: 99%

“…Overconfidence is an innate psychological feature of human beings. Moreover, it is among the most deep-rooted psychological characteristics of human beings, specifically in the decision-making field [9][10][11]. Therefore, this paper focuses on the influence of overconfidence on OSNID.…”

Section: Introductionmentioning

confidence: 99%

Online Social Network Information Dissemination Integrating Overconfidence and Evolutionary Game Theory

et al. 2021

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Public opinion inversion and other nonlinear phenomena often occur during online social network information dissemination (OSNID) in modern society. To explore the influence of overconfidence on OSNID, we develop a multi-agent simulation model integrating overconfidence and evolutionary game s, as previous research has scarcely paid any attention to irrational behavior in information dissemination. This integrated paradigm provides an effective tool for managers to control the spread of OSNID and reduce the harm caused by rumors. The theoretical model is constructed from the perspective of an evolutionary game and , combined with overconfidence theory, three overconfidence scenarios are designed: benefit overconfidence, cost overconfidence, and both benefit and cost overconfidence. Then, a multi-agent simulation model of OSNID under different overconfidence scenarios is realized. The proposed simulation model exhibited better performance (e.g., faster diffusion speed) than the traditional Bass model; its performance was also validated by comparison with real-world cases. The results demonstrate that (1) with increasing benefit overconfidence, the convergence speed of OSNID will be accelerated, and the user group will reach stability at a faster speed. (2) With increasing cost overconfidence, the user's decision will change from adopting dominant to titfor-tat, and the adoption ratio will gradually decrease. (3) Compared with overconfidence in earnings, overconfidence in costs is more conducive to improving stability. This study attempts to provide new ideas for OSNID and attempts to propose an integration framework for behavioral theory and simulation methods.

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Loss aversion, overconfidence and their effects on a virtual stock exchange

Cited by 9 publications

References 15 publications

Implications of the overconfidence bias in presence of private information: Evidence from MENA stock markets

Implications of the overconfidence bias in presence of private information: Evidence from MENA stock markets

Co-Integration among COVID-19, Investor Sentiment, and the Stock Market

Online Social Network Information Dissemination Integrating Overconfidence and Evolutionary Game Theory

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