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- 2017
函数型非参数部分自回归模型及其在金融中的应用
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Abstract:
结合金融市场中的滞后现象以及函数型协变量和响应变量之间的非线性关系提出了函数型非参数部分自回归模型，接着使用profile最小二乘方法和非参数核估计方法给出了该模型的估计，并通过统计模拟验证了该方法的有效性，最后通过上证指数的实例验证了模型的预测能力.
Functional data analysis is an important method of analyzing high-frequency data of the financial market. Combining the lag phenomenon on the financial market and the nonlinear relationship between the functional covariate and the response variable, this paper proposes a functional nonparametric partial auto-regression model. Then, the profile least square method and the nonparametric kernel estimation are used to obtain the estimators of the model. Statistical simulation verified its validity. A real example about Shanghai Stock Index data is used to demonstrate the good prediction ability of the model
| [1] | 许梁, 孙涛, 徐箭, 等. 基于函数型非参数回归模型的中长期日负荷曲线预测[J]. 电力自动化设备, 2015, 35(7): 89-94. |
| [2] | YUAN G, WEI Z. Non Monotone Backtracking Inexact BFGS Method for Regression Analysis[J]. Communications in Statistics-Theory and Methods, 2013, 42(2): 214-238. DOI:10.1080/03610926.2011.579370 |
| [3] | FERRATY F, VIEU P. Nonparametric Functional Data Analysis: Theory and Practice[M]. New York: Springer, 2006. |
| [4] | RAMSAY J O, SILVERMAN B W. Functional Data Analysis[M]. New York: Springer, 1997. |
| [5] | 程丽娟. 上证指数的函数型主成分分析预测[J]. 岭南师范学院学报, 2016, 37(3): 39-43. |
| [6] | 龙文, 李楠, 王惠文, 等. 金融危机过程中不同类型国家经济发展的差异性比较——基于函数数据分析方法[J]. 管理评论, 2014, 26(3): 3-10. |
| [7] | WASSERMAN L. All of Nonparametric Statistics[M]. New York: Springer, 2006. |
| [8] | 蔺顺锋, 易丹辉, 肖宏伟. 基于函数型数据分析视角的我国副省级城市年平均工资差异研究[J]. 现代管理科学, 2015(3): 27-29. |
| [9] | 马晓波, 冯凌秉, 李玮. 高频数据日内波动特征的函数型分析[J]. 企业导报, 2011(22): 76-77. |
