Nonlinear Force Affecting Stock Market Volatility

Abstract We transform stock price time series to the dependent force parameters using Newton’s second law (a kind of information filtering). The acts on a point in space data. One ten parameters, if its value short interval is extremely large, announces increasing uncertainty. This delayed effect nonlinear we interpret as sensitivity initial conditions, for chaos combined with stochasticity, considering generated by differential equations fluctuating function included. Our aim improve understanding and rough prediction processes complex systems.