AbstractThe common observation made in the empirical nonlinear dynamics literature is the constraints imposed by the availability of a limited number of observations in the implementation of the existing algorithms of Lyapunov exponents. The algorithm discussed here can estimate allnLyapunov exponents of an unknownn‐dimensional dynamical system accurately with limited number of observations. This makes the algorithm attractive for applications to economic as well as financial time‐series data. The implementation of the algorithm is carried out by multilayer feedforward networks which are capable of approximating any function and its derivatives to any degree of accur