本项目是基于经济物理系统研究金融市场波动性质，该领域是应用随机理论和非线性系统研究金融问题，其研究方法和理论主要来自于统计物理理论。国际上该领域的研究工作正在迅猛发展和不断深入。构造适应的金融模型，更精确地预测、分析和模拟金融市场，近年来一直是经济物理研究关注的焦点。本研究主要针对中国证券和能源市场（含股指期货），兼顾国际上的证券和能源市场，进行理论和实证研究：（1）将随机理论引入到神经网络系统中，构建随机时效性神经网络预测系统模型，预测和评估金融市场波动趋势；（2）应用Ising系统、Contact系统、Voter系统和Percolation系统等构建、预测、分析和计算机模拟金融市场波动，以解释金融复杂交互系统内在的波动规律性质；（3）研究金融时间序列回程间隙与波动相关性的统计规律性（包括拟合程度分析、证券市场与能源市场相关性分析、长记忆性分析、相关性分析、波动程度与趋势分析等）。

We study the fluctuation behaviors of financial markets by econophysics theory. Econophysics is an interdisciplinary research field, applying uncertainty or stochastic processes and nonlinear dynamics to solve problems in economics, and its research methods are derived from statistical physics. The research of this field is an active and rapid growing field. The study of forecasting, modelling, analysis and simulation of financial market volatilities has long been a focus of economic research. Our research will mainly investigate the fluctuation behaviors of Chinese financial markets, and the corresponding empirical research will be made. (1) We model a stochastic time effective neural network to predict and evaluate the trends of financial markets; (2) According to Ising system, Contact system, Voter system and Percolation system, we study the financial complex systems; (3) We analyze and make the empirical research on return interval and volatility correlation of financial time series, which include the fitting analysis, the relationship between the financial market and the energy market, the long-memory test for the financial time series, the long-range correlation of the volatility series, the volatility range and the trend analysis, etc.