Eye tracking can facilitate understanding irrational decision-making in contexts such as financial risk-taking.For this purpose,we develop an experimental framework in which participants trade a risky asset in a simul...Eye tracking can facilitate understanding irrational decision-making in contexts such as financial risk-taking.For this purpose,we develop an experimental framework in which participants trade a risky asset in a simulated bubble market to maximize individual returns while their eye movements are recorded.Returns are sensitive to eye movement dynamics,depending on the presented visual stimuli.Using eye-tracking data,we investigated the effects of arousal,attention,and disengagement on individual payoffs using linear and nonlinear approaches.By estimating a nonlinear model using attention as a threshold variable,our results suggest that arousal positively influences trading returns,but its effect becomes smaller when attention exceeds a certain threshold,whereas disengagement has a higher negative impact on reduced attention levels and becomes almost irrelevant when attention increases.Hence,we provide a neurobehavioral metric as a function of attention that predicts financial gains in boomand-bust scenarios.This study serves as a proof-of-concept for developing future psychometric measures to enhance decision-making.展开更多
We study the concept of financial bubbles in a market model endowed with a set P of probability measures,typically mutually singular to each other.In this setting,we investigate a dynamic version of robust superreplic...We study the concept of financial bubbles in a market model endowed with a set P of probability measures,typically mutually singular to each other.In this setting,we investigate a dynamic version of robust superreplication,which we use to introduce the notions of bubble and robust fundamental value in a way consistent with the existing literature in the classical case P={P}.Finally,we provide concrete examples illustrating our results.展开更多
文摘Eye tracking can facilitate understanding irrational decision-making in contexts such as financial risk-taking.For this purpose,we develop an experimental framework in which participants trade a risky asset in a simulated bubble market to maximize individual returns while their eye movements are recorded.Returns are sensitive to eye movement dynamics,depending on the presented visual stimuli.Using eye-tracking data,we investigated the effects of arousal,attention,and disengagement on individual payoffs using linear and nonlinear approaches.By estimating a nonlinear model using attention as a threshold variable,our results suggest that arousal positively influences trading returns,but its effect becomes smaller when attention exceeds a certain threshold,whereas disengagement has a higher negative impact on reduced attention levels and becomes almost irrelevant when attention increases.Hence,we provide a neurobehavioral metric as a function of attention that predicts financial gains in boomand-bust scenarios.This study serves as a proof-of-concept for developing future psychometric measures to enhance decision-making.
文摘We study the concept of financial bubbles in a market model endowed with a set P of probability measures,typically mutually singular to each other.In this setting,we investigate a dynamic version of robust superreplication,which we use to introduce the notions of bubble and robust fundamental value in a way consistent with the existing literature in the classical case P={P}.Finally,we provide concrete examples illustrating our results.
