Using Lyapunov Exponent for Modeling Time Series of Oil Price Based on Logistic Map

In recent years, the theory of nonlinear systems in general and chaotic systems in particular has received a great deal of attentions in the economic research. Nonlinear systems show many behaviors which can be used to explain complex and deterministic features of economic systems. In this paper a new approach is proposed to fit a nonlinear dynamic function to a time series. First Lyapunov exponent of the time series is calculated. Then Lyapunov exponent is calculated from an assumed function. By comparing these two exponents, we are able to estimate the parameters of the function. Logistic map is used as the dynamic function and time series of price of oil is fitted by this function.