Chaotic dynamics analysis and forecast of gold futures price
Yongzhao Wang · Tianjin Gongye Daxue xuebao · 2011
The time series which formed by the daily closing price of gold futures of the Shanghai Futures Exchange are studied.Based on phase space reconstruction,it is proved that the studied time series have the chaotic behavior by drawing phase diagram,calculating the characteristic parameters of time series like correlation dimension and the Kolmogorov entropy.Finally,the Radial Basis Function(RBF) neural network is adopted to forecast the further data of time series,and the satisfying forecast result is obtained.