Behavioral agent-based framework for interacting financial markets

Abstract

PurposeThis paper aims at developing a behavioral agent-based model for interacting financial markets. Additionally, the effect of imposing Tobin taxes on market dynamics is explored.Design/methodology/approachThe agent-based approach is followed to capture the highly complex, dynamic nature of financial markets. The model represents the interaction between two different financial markets located in two countries. The artificial markets are populated with heterogeneous, boundedly rational agents. There are two types of agents populating the markets; market makers and traders. Each time step, traders decide on which market to participate in and which trading strategy to follow. Traders can follow technical trading strategy, fundamental trading strategy or abstain from trading. The time-varying weight of each trading strategy depends on the current and past performance of this strategy. However, technical traders are loss-averse, where losses are perceived twice the equivalent gains. Market makers settle asset prices according to the net submitted orders.FindingsThe proposed framework can replicate important stylized facts observed empirically such as bubbles and crashes, excess volatility, clustered volatility, power-law tails, persistent autocorrelation in absolute returns and fractal structure.Practical implicationsArtificial models linking micro to macro behavior facilitate exploring the effect of different fiscal and monetary policies. The results of imposing Tobin taxes indicate that a small levy may raise government revenues without causing market distortion or instability.Originality/valueThis paper proposes a novel approach to explore the effect of loss aversion on the decision-making process in interacting financial markets framework.