基于岭回归的证券指数的预测分析——以上证综合指数为例

Forecast Analysis of Securities Index Based on Ridge Regression—In Case of Shanghai Composite Index

证券市场的是衡量一个国家总体经济发展水平的重要指标。而证券指数是对各个证券市场总体水平的反映,是广大投资者关注的重要指数。它不仅反映了证券市场的基本状况,同时对经济走向也具有重要的导向作用。对证券指数的预测分析以及趋势研判对稳定市场、引导投资者具有重大意义。然而,在建立相应统计预测模型时自变量之间常常出现严重的多重共线。本文通过对模型进行改进,综合运用岭回归解决了自变量间多重共线性的问题。并且以我国上证综合指数的真实数据为例,将改进后岭回归模型的预测值与真实值进行对比,拟合结果较好。

Security market is an important indicator to measure a country’s overall level of economic devel-opment. The securities index is a reflection of the overall level of the securities market, and it is an important index of the majority of investors concerned. It not only reflects the basic situation of the securities market, but also plays an important role in guiding the economic trend. Prediction of securities index and trend analysis plays an important role to stabilize market and guide investors. However, serious multi-collinearity between variables often appears in the establishment of the corresponding statistical prediction model. In this paper, the model is improved, and the problem of multi-collinearity between independent variables is solved by using ridge regression. And taking the real data of Shanghai Composite Index as an example, the predicted value of the improved ridge regression model is compared with the true value, and the fitting result is better.