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Aggregating Information for Optimal ...

Li, Xiao.

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Aggregating Information for Optimal Portfolio Weights.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Aggregating Information for Optimal Portfolio Weights./
作者:	Li, Xiao.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2019,
面頁冊數:	89 p.
附註:	Source: Dissertations Abstracts International, Volume: 80-11, Section: A.
Contained By:	Dissertations Abstracts International80-11A.
標題:	Finance. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13860149
ISBN:	9781392089316

Aggregating Information for Optimal Portfolio Weights.
Li, Xiao.

Aggregating Information for Optimal Portfolio Weights. - Ann Arbor : ProQuest Dissertations & Theses, 2019 - 89 p.

Source: Dissertations Abstracts International, Volume: 80-11, Section: A.

Thesis (Ph.D.)--The University of Arizona, 2019.

This item must not be sold to any third party vendors.

I attempt to address an important issue of the portfolio allocation literature - none of the allocation rules from prior studies consistently delivers good performance. I develop an approach that aggregates information from a wide range of sources to make allocation decisions. Specifically, this approach models the optimal portfolio weights as a function of a broad set of portfolio weights implied by prior allocation rules, and determines the relative contribution from each allocation rule through Elastic Net, a machine-learning technique. Out-of-sample tests suggest that my approach consistently achieves good performance, whereas none of the alternative rules can match the consistency.

ISBN: 9781392089316Subjects--Topical Terms:

542899
Finance.

Aggregating Information for Optimal Portfolio Weights.
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