Nonlinear Force Affecting Stock Market Volatility

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