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A microscopic model of financial markets is considered, consisting of manyinteracting agents (spins) with global coupling and discrete-time thermal bathdynamics, similar to random Ising systems. The interactions between agentschange randomly in time. In the thermodynamic limit the obtained time series ofprice returns show chaotic bursts resulting from the emergence of attractorbubbling or on-off intermittency, resembling the empirical financial timeseries with volatility clustering. For a proper choice of the model parametersthe probability distributions of returns exhibit power-law tails with scalingexponents close to the empirical ones.

Volatility Clustering and Scaling for Financial Time Series due to Attractor Bubbling