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Information,Time,Alternative Choices And Individual Investors Decision

Posted on:2022-01-02Degree:DoctorType:Dissertation
Country:ChinaCandidate:J ZhangFull Text:PDF
GTID:1520307034962369Subject:Management Science and Engineering
Abstract/Summary:PDF Full Text Request
Internet technology has changed the decision-making environment of individuals,which increased the types of information,accelerated the speed of decision and changed the way of investment.Using the data of an online lending platforms which relies on non-professional individuals to screen loans,this paper explores the influence of information,time and alternative options on the decision-making behavior of individual investors.Based on the signal theory,this paper explores the influence of information on individuals’ decisions.After improving the existing loan quality measurement model,the study found that loans with higher excess returns are more likely to be funded and are bid on more quickly than other loans,which proves that investors can process signals and form the correct investment behavior at the market level.Voluntary and unverifiable information plays a significant moderating role in the decision-making process,and the degree of adjustment increases with the increase of excess returns.Based on the dual-system thinking model,this paper investigates the impact of time on individuals’ decisions.Through empirical and experimental methods,we find that the profit increases with the increase of the relative decision time at the investor and bidding level.The decision time changes the investment strategy,the quick decision maker ignores default risks,and reduces the accuracy of decision.When the loan is funded within 10 seconds,all investors make too fast decisions and fail to start System 2,which leads that the positive correlation between relative decision time and profit is no longer valid.Based on regret theory,this paper examines the influence of alternative options on individual investors’ decision making.It was found that the investment criteria did not change significantly before and after the first use of automatic bidding,but changed with the increase of the number of times it was used,suggesting that the expected regret was generated by the investment experience.At the level of portfolio,regret value is significantly positively correlated with return rate,indicating that expected regret can improve the quality of decision,but the positive and negative effects of regret value have different effects on investors’ risk attitude.When the regret value is positive,the probability that the expected future automatic method will obtain high returns is high,and the investment standard is more risk averse;while when the regret value is negative,the probability that the expected future automatic method will obtain high returns is low,and the investment standard is more risk preference.Our study makes several contributions to the literature.This paper fills the gap that different kinds of signals play different roles in the decision-making process.It provides new evidence for the identification of high-quality loans at the market level for the dispute over whether non-professional individual investors have the right decisionmaking ability.Secondly,the research results of the relationship between decision time and decision quality in real market are supplemented,and the threshold value between decision time and investment profit is found for the first time.Finally,the evidence of the effect of anticipated regret on decision-making behavior in the real market is supplemented,and the research gaps of the mechanism of anticipated regret and the risk attitude of decision makers under the regret theory are made up.This study describes the new rules of investors’ micro-behaviors under the new financial market environment in the Internet era,and provides theoretical support for the supervision and prevention of market risks under the Internet background.
Keywords/Search Tags:Individual Decision Behavior, Signal Theory, Decision Time, Regret theory, Fintech
PDF Full Text Request
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