QQ客服 官方微博 反馈留言

	Nonnegative-lasso and application in index tracking
	Wu, Lan ; Yang, Yuehan ; Liu, Hanzhong
	2014
关键词	Index tracking Nonnegative-lasso Variable selection consistency Multiplicative updates DANTZIG SELECTOR MODEL SELECTION REGRESSION PORTFOLIO SHRINKAGE RETURNS FUNDS
英文摘要	This paper proposes the nonnegative-lasso method for variable selection in high dimensional sparse linear regression models with the nonnegative constraints on the coefficients. This method is an extension of Lasso and is shown to have variable selection consistency and estimation consistency under certain condition similar to Irrepresentable Condition in Lasso. To get the solution of the nonnegative-lasso, many algorithms such as Lars, coordinate decent can be used, among which multiplicative updates approach is preferred since it is faster and simpler. The constrained index tracking problem in stock market without short sales is studied in the latter part. The tracking results indicate that nonnegative-lasso can get small tracking error and is successful in assets selection. (C) 2013 Elsevier B.V. All rights reserved.; http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000328306800009&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701 ; Computer Science, Interdisciplinary Applications; Statistics & Probability; SCI(E); EI; 2; ARTICLE; yangyuehan8841@163.com; 116-126; 70
语种	英语
出处	EI ; SCI
出版者	computational statistics data analysis
内容类型	其他
源URL	[http://hdl.handle.net/20.500.11897/157429]
专题	数学科学学院
推荐引用方式 GB/T 7714	Wu, Lan,Yang, Yuehan,Liu, Hanzhong. Nonnegative-lasso and application in index tracking. 2014-01-01.

个性服务

查看访问统计

相关权益政策

暂无数据

收藏/分享

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。