Heterogeneous agent-based modeling of endogenous boom-bust cycles in financial markets with adaptive expectations and dynamically switching fractions between contrarian and fundamental market entry strategies

Financial systems present nonlinear dynamics whilst in some conditions chaotic behaviours emerge, rendering the stability of these systems utterly volatile. In this novel study we investigate boom-bust cycles in stock markets with heterogeneous agent-based modeling, yet incorporating endogenously evolving fractions of market participants, particularly those switching between contrarian and fundamental strategies. The dynamical behavior of various market entry behaviours of market agents are studied via numerical simulations and analyses of phase portraits, bifurcation diagrams and Lyapunov exponents. If the system adjusts in a partial equilibrium of at least one positive Lyapunov exponent, we observe the emergence of chaotic dynamics. Overall, chaos emerges via endogenous boom-bust cycle dynamics, caused by time-varying fractions of switching strategies between contrarian versus fundamental trading strategies. Our results prove to be invaluable to different types of market participants, such as traders, arbitrageurs, investors, speculators and institutional market makers.

Automated summary

In this study, we use a heterogeneous agent-based modeling approach to explore boom-bust cycles in stock markets. We focus on the dynamics of market participants switching between contrarian and fundamental strategies. Our numerical simulations and analysis of phase portraits, bifurcation diagrams, and Lyapunov exponents reveal that chaotic dynamics emerge when the system adjusts with at least one positive Lyapunov exponent. These findings are valuable for traders, arbitrageurs, investors, speculators, and institutional market makers.