岭回归视角下金融数据分析与算法实现

Financial data analysis and algorithm realization from the perspective of the ridge regression

随着我国金融行业的快速发展,大量繁杂的金融数据需要快速有效的处理,而通过最小二乘法来估计参数的多元线性回归算法处理金融数据,难以得到准确的结果。因此,基于岭回归基本原理,针对深证指数数据,运用岭回归分析和处理金融数据,通过与最小二乘法模型的对比分析,显示基于岭回归的金融数据分析方法能够有效地避免多重共线性对于金融数据的影响,克服了传统的最小二乘法进行回归分析所带来的模型失真问题。

With the rapid development of China＇s financial industry, a large number of financial data are complicated to be treated quickly and effectively, and by using the least square method to estimate the parameters of the muhivariate linear regression algorithm to deal with the financial data, it is difficult to obtain accurale results. Therefore, the ridge regression based on the basic principles, the Shenzhen stock index data,using the ridge regression analysis and processing of financial data,by comparing the model and the method of least squares analysis, showed that the financial data of ridge regression analysis method can effectively avoid the multicollinearity effect on financial data hosed on least square method, has overcome the traditional was brought about by regression analysis model distortion.