Dynamics Evolution of Trading Strategies of Investors in Financial Market

Wu, Binghui; Duan, Tingting; He, Jie

doi:10.1007/s10614-016-9639-3

Cited by 4 publications

(5 citation statements)

References 22 publications

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“…In terms of the relationship between financial literacy and lending behavior, Gathergood and Weber (2015) found that the improvement of financial literacy, especially the improvement of loan knowledge, will drive borrowers to choose lower-cost mortgages. Wu, Duan, et al (2018) and Wu, Kun, et al (2018) studied the relationship between financial literacy and household debt behavior and found that the level of financial literacy of Chinese households is generally low, and the improvement of financial literacy can significantly increase the possibility of household debt and reduce excessive debt which is conducive to smooth household consumption. Wu et al (2017) also studied the impact of Chinese investors’ financial literacy on household lending behavior and found that the expansion of household wealth inequality would inhibit the promotion of financial literacy on household lending behavior.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Bragt et al (2001) studied many factors such as matching mechanism and selection intensity, on the level of cooperation and evolutionary stability using evolutionary algorithms with the prisoner's dilemma as the background. Wu, Duan, et al (2018) and Wu, Kun, et al (2018) used the replicator dynamic formula to analyze the dynamic evolution process of investor strategies and conducted computational simulation experiments to verify the equilibrium structure of the formula. They also mentioned the limitations of computer simulation experiments.…”

Section: Behavioral Evolutionary Game Experimentsmentioning

confidence: 99%

“…Wu et al (2017) also studied the impact of Chinese investors’ financial literacy on household lending behavior and found that the expansion of household wealth inequality would inhibit the promotion of financial literacy on household lending behavior. Wu, Duan, et al (2018) and Wu, Kun, et al (2018) and Meng et al (2019) successively studied the influence of financial literacy on credit consumption behavior. After controlling for factors such as income, age, education, and wealth, they found that financial literacy can promote credit consumption, especially the use of credit cards.…”

Section: Literature Reviewmentioning

confidence: 99%

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Investor financial literacy, decision-making behavior, and stock price volatility—Evidence from behavioral experiments.

Yin¹,

Yang²

2022

Journal of Neuroscience, Psychology, and Economics

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Financial literacy is generally considered to be an important factor affecting investors' decision-making, but there is no unified conclusion on whether the improvement of financial literacy can improve the degree of rational decision-making of investors. This article aims to examine whether the improvement of financial literacy can improve the rationality of investors from the perspective of investment psychology and behavior, and on the other hand, to further analyze the impact of the improvement of investor group financial literacy on stock prices. We designed three sets of mutually controlled investment evolutionary game experiments and analyzed the experimental results. We found that the improvement of financial literacy can help investors overcome the "Framework Effect" and "Heuristic Deviation," significantly improve the rationality of investors' decision-making, reduce stock price volatility and improve stock pricing efficiency. The results provide strong empirical evidence for the necessity of investors' financial literacy education.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Behavioral Evolutionary Game Experimentsmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

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Investor financial literacy, decision-making behavior, and stock price volatility—Evidence from behavioral experiments.

Yin¹,

Yang²

2022

Journal of Neuroscience, Psychology, and Economics

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“…They gave up the hypothesis of rational economic man and insisted that the investor had the bounded rationality [15][16][17][18]. In the framework of bounded rationality, investors were mainly divided into two kinds: rational traders and noise traders [19][20][21][22]. Essentially, noise was a signal caused by the shortcomings of market mechanisms or the decisionmaking mistakes of market subjects [23].…”

Section: The Researches Of Risk Contagion In Financial Marketsmentioning

confidence: 99%

Nonlinear Dynamics Characteristic of Risk Contagion in Financial Market Based on Agent Modeling and Complex Network

Duan

2019

Complexity

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Risk contagion is becoming a research hotspot in the field of econophysics with the rise of interdisciplinary studies and gains more and more attention from theoretical circles and practical departments. This paper proposes a new research frame to discuss the microscopic mechanism of risk contagion based on agent modeling technology and complex network theory and reveals nonlinear dynamics characteristic of risk contagion from the perspective of market participants in financial market. Based on the proposed SICM model, financial risk can transmit from susceptible agents to infected agents, to contagious agents, or to immune agents. With the increases of contagious probabilities, the simulation experiments show that (1) the amount of susceptible agents continuously decreases; (2) the amount of infected agents increases first and then decreases; (3) the amount of contagious agents increases first and then decreases with a lower speed, relative to the amount of infected agents; and (4) the amount of immune agents continuously increases. The major contribution of this paper is a new method for studying nonlinear dynamics characteristic of risk contagion, which can be used as a theoretic basis for further researches on the behavioral features of microcosmic subject and the inner mechanisms of risk contagion.

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“…The study of risk contagion has always been a hot topic in financial research fields [52][53][54][55][56][57]. And it has broad prospection in the aspect of analyzing the mechanism of risk contagion based on artificial stock market models.…”

Section: Introductionmentioning

confidence: 99%

Investor Behavior and Risk Contagion in an Information-Based Artificial Stock Market

2020

IEEE Access

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This paper designs an artificial stock market model to discuss investor behavior and risk contagion caused by market information. Considering the investors' trading decisions are attributed to the change of market information, new market information no matter from the macro field or the micro field can influence investor behavior and risk contagion. In our artificial stock market model, we assume new information is the sole factor affecting the fluctuation of stock prices. And investor sentiment is influenced by investor sensitivity to new information, investment decisions of neighboring investors, and investor understanding preference for new information. Through simulation experiments, some conclusions can be drawn as follows. Firstly, stock price volatility becomes stronger with increasing investor sensitivity to new information, under the condition of a smaller fundamental contagion coefficient or larger sensitivity to new information from investor neighbors. Secondly, stock price volatility becomes more moderate with increasing sensitivity to new information from investor neighbors, under the condition of a smaller fundamental contagion coefficient or smaller investor sensitivity to new information. Thirdly, with the increasing fundamental contagion coefficient, stock price volatility may strongly increase under the condition of smaller investor sensitivity to new information and smaller sensitivity to new information from investor neighbors, or slightly increase under the condition of smaller investor sensitivity to new information and larger sensitivity to new information from investor neighbors, or slightly decrease under the condition of larger investor sensitivity to new information and smaller sensitivity to new information from investor neighbors, or show a little change under the condition of larger investor sensitivity to new information and larger sensitivity to new information from investor neighbors.

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Dynamics Evolution of Trading Strategies of Investors in Financial Market

Cited by 4 publications

References 22 publications

Investor financial literacy, decision-making behavior, and stock price volatility—Evidence from behavioral experiments.

Investor financial literacy, decision-making behavior, and stock price volatility—Evidence from behavioral experiments.

Nonlinear Dynamics Characteristic of Risk Contagion in Financial Market Based on Agent Modeling and Complex Network

Investor Behavior and Risk Contagion in an Information-Based Artificial Stock Market

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