使用卡尔曼滤波器和 LagLasso 对 S&P 500 指数建模][Modeling the S&P 500 Index using the Kalman Filter and the LagLasso]

使用卡尔曼滤波器和 LagLasso 对 S&P 500 指数建模 Modeling the S&P 500 Index using the Kalman Filter and the LagLasso


课程网址:	http://videolectures.net/amlcf09_mahler_mtsp/
主讲教师:	Nicolas Mahler
开课单位:	卡尚高等师范学院
开课时间:	2009-08-21
课程语种:	英语
中文简介:	本视频介绍了一种通过使用宏观经济和金融解释变量来预测 S&P 500 指数每月向上和向下变化的方法。该方法基于卡尔曼滤波执行的去噪步骤与套索型程序执行的变量选择步骤的组合。特别是，我们提出了一种名为 LagLasso 的 Lasso 方法的实现，其中包括为各个因素选择滞后。我们基于朴素的交易规则提供了有前景的预测模型回测结果。
课程简介:	This video introduces a method to predict upward and downward monthly variations of the S&P 500 index by using a pool of macro-economic and financial explicative variables. The method is based on the combination of a denoising step, performed by Kalman filtering, with a variable selection step, performed by a Lasso-type procedure. In particular, we propose an implementation of the Lasso method called LagLasso which includes selection of lags for individual factors. We provide promising backtesting results of the prediction model based on a naive trading rule.
关键词:	计算金融; 计算机科学; 卡尔曼滤波器
课程来源:	视频讲座网
数据采集:	2023-11-28：wujk
最后编审:	2023-11-28：wujk
阅读次数:	17

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