The fractal feature and price trend in the gold future market at the Shanghai Futures Exchange (SFE)

被引:16
作者
Wu, Binghui [1 ]
Duan, Tingting [2 ]
机构
[1] South China Normal Univ, Sch Econ & Management, Guangzhou 510006, Peoples R China
[2] Lanzhou Univ Finance & Econ, Dept Finance, Lanzhou 730020, Peoples R China
关键词
Gold future; Fractal analysis; Hurst index; Neural network; SFE;
D O I
10.1016/j.physa.2016.12.048
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
The price of gold future is affected by many factors, which include the fluctuation of gold price and the change of trading environment. Fractal analysis can help investors gain better understandings of the price fluctuation and make reasonable investment decisions in the gold future market. After analyzing gold future price from January 2th, 2014 to April 12th, 2016 at the Shanghai Futures Exchange (SFE) in China, the conclusion is drawn that the gold future market has sustainability in each trading day, with all Hurst indexes greater than 0.5. The changing features of Hurst index indicate the sustainability of gold future market is strengthened first and weakened then. As a complicatedly nonlinear system, the gold future market can be well reflected by Elman neural network, which is capable of memorizing previous prices and particularly suited for forecasting time series in comparison with other types of neural networks. After analyzing the price trend in the gold future market, the results show that the relative error between the actual value of gold future and the predictive value of Elman neural network is smaller. This model that has a better performance in data fitting and predication, can help investors analyze and foresee the price tendency in the gold future market. (C) 2017 Elsevier B.V. All rights reserved.
引用
收藏
页码:99 / 106
页数:8
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