通过基于代理的模型中的解耦来检测实验中产生的投机泡沫
Detecting speculative bubbles created in experiments via decoupling in agent based models
摘要：
事实证明，即使是事后证明投机性金融泡沫的存在也是极其困难的，因此事先预测投机性泡沫乍一看似乎是一项不可能完成的任务。正如最近由所谓的次贷危机引发的金融市场动荡所表明的那样，我们显然迫切需要新的工具来理解和处理金融投机泡沫。与快速增长时期相反，在投机泡沫期间，市场动态的性质发生了深刻的变化，在这种情况下，自我包含的策略往往导致无条件的购买。因此，一个关键的问题是，这种特征是否可以量化，如果可以量化，则用于理解创造投机泡沫的充分和必要条件是什么。在这里，我们展示了一种新的技术，基于代理的模拟，给出了一个强大的测量分离的反馈所创建的交易选择，并预测在实验中与人类受试者的投机泡沫的发病。我们使用从人类实验中获得的交易数据作为人工代理的计算机模拟的输入，这些人工代理使用从博弈论定义的自适应策略。
英文摘要：
Proving the existence of speculative financial bubbles even a posteriori has proven exceedingly difficult so anticipating a speculative bubble ex ante would at first seem an impossible task. Still as illustrated by the recent turmoil in financial markets initiated by the so called subprime crisis there is clearly an urgent need for new tools in our understanding and handling of financial speculative bubbles. In contrast to periods of fast growth, the nature of market dynamics profoundly changes during speculative bubbles where self contained strategies often leads to unconditional buying. A critical question is therefore whether such a signature can be quantified, and if so, used in the understanding of what are the sufficient and necessary conditions in the creation of a speculative bubble. Here we show a new technique, based on agent based simulations, gives a robust measure of detachment of trading choices created by feedback, and predicts the onset of speculative bubbles in experiments with human subjects. We use trading data obtained from experiments with humans as input to computer simulations of artificial agents that use adaptive strategies defined from game theory....
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
