以广义回归神经网络预测共同基金报酬

Forecast for mutual fund returns with gerenal regression neural network

鉴于近年来许多相关文献成功地运用广义回归神经网络进行财经方面的预测,以及国内共同基金净值之预测与报酬率评估。通过搜集国内基金资料,以灰关联分析法进行各基金投资绩效分析,挑选投资绩效良好的共同基金作为投资标的;再以广义回归神经网络建立预测模型,与灰预测模型、多元回归模型进行预测能力及报酬率的比较分析。5种预测绩效评价指标、5组数据交互验证散布图及报酬率分析表明:广义回归神经网络在预测能力及预测报酬率上均有很好的表现。

In recent years, there are many relevant documents that are successfully in general regression regression eval ne ne ural ural the analysizes network for the financial network for the prediction return of the investment. its investment performance sector forecasts. of the net value of The author picks with grey relation This paper adoptes the general the domestic mutual fund and for out a lot of fund information at al analysis, and select some good investment performances of mutual funds as investment targets. Through general regression neural network model, he sets up the prediction model and with grey prediction and multiple regression model, he conducts the comparative analysis on the accuracy of the prediction and the return rate. It is found that it is better to predict the return rate with general regression neural network than with grey prediction and multiple regression model. On the basis of the evaluation of the 5 indexes of the performance management, and 5 group interactive data validation map, the gereral regression neural network can perform well in prediction and the prediction of return rates.