Detecting speculative bubbles created in experiments via decoupling in agent based models

TL;DR

This paper introduces a new agent-based simulation technique that quantifies market detachment and predicts the onset of speculative bubbles using experimental human trading data.

Contribution

It presents a novel method combining human experiment data with agent-based models to detect and understand the formation of speculative bubbles.

Findings

The technique predicts bubble onset in experimental markets.

Agent feedback detachment correlates with bubble formation.

The method offers a new tool for anticipatory analysis of market bubbles.

Abstract

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....