Modern financial markets encapsulate vast number of interconnected financial entities, instruments, and strategies. Understanding these complex dynamical systems requires multidisciplinary efforts from a wide range of quantitative fields including mathematics, statistics, data mining, and operations research. While conventional financial research focuses mostly on linear models of variables of interest, they cannot cope with real-world financial phenomena. In the past decade, we have seen significant progress in our fundamental understanding of dynamical financial and economic behaviors, both from the micro- and macroprospective, using nonlinear systems and methodologies. Powerful techniques borrowed from traditional nonlinear models and new methods invented have been brought to almost every aspect of financial research, including asset pricing, risk management, and financial forecasting. Still, there exist many challenging problems. The goal of this special issue is to gather recent research efforts on the development and applications of nonlinear techniques to address the critical issues in finance. We invite investigators to contribute original research and review articles on nonlinear methods as well as the applications of existing nonlinear models to finance.

Potential topics include but are not limited to the following:

• Portfolio selection and optimization
• Asset pricing and arbitrage techniques
• Behavioral finance modeling
• Risk assessment and credit analysis
• Financial time series modeling and forecasting
• Financial diagnosis and control
• Dynamical analysis of stability, chaos, and bifurcation
• Stochastic analysis and stochastic control
• Numerical computation and simulations
• Financial network models
• Agent-based computational finance
• Nonlinear dynamical system for finance