Application of Neural Networks based on Monte-Carlo-Adaptation Rule in Index Futures Price Prediction

沪深300股指期货在中国上市已经有四个年头，它在金融市场中扮演着分散风险的重要角色，不仅为机构投资提供了一种降低系统风险的渠道，也为投机者提供了一种高风险、高收益的投资机会。然而股票市场风云变幻，以其为标的物的股指期货价格也随之剧烈波动，加之期货交易自身的高杠杆性，也给投资者带来巨大的风险。因此股指期货的价格预测，一直是相关领域研究的热点问题。随着人工神经网络技术的发展，其强大的非线性逼近能力很快被用于各种金融问题的研究中。但是传统的人工神经网络方法也存在一些缺陷，例如容易对学习样本过拟合而降低泛化能力，参数优化等问题。本文将基于随机变异-优化选择规则（MCA）设计的神经网络用于股指期货的价格...Hushen 300 index futures has been on the market for four years, and play a important role in risk distribution of China's financial market: institutional investors use it to avoid systemic risk and speculators use it to get a higher risk-reward. But the stock market swings and high leverage trait put investors into a big risk, finding a way to forecast the futures price is a center problem for eve...学位：理学硕士院系专业：物理与机电工程学院_理论物理学号：1982011115286

Application of a Newtype of Neural Networks in the Futures Price Forecast

文章利用随机变异—优化选择设计规则的神经网络对沪深300股指期货的价格时间序列进行仿真预测。研究发现该方法在解决实际问题的过程中效果更佳,能够解决bP网络参数不易确定,预测精度不高的问题。A new type of neural networks,which is designed by Monte-Carlo-Adaptation rule,is used toforecast the futures price.This method is proved to be more effective than BP neural networks,and obtain higheraccuracy of predicting.In addition,it can also give a way to solve the problem of network parameters optimization