DocumentCode
3106777
Title
Weight shrinkage for portfolio optimization
Author
Pollak, Ilya
Author_Institution
Sch. of Electr. & Comput. Eng., Purdue Univ., West Lafayette, IN, USA
fYear
2011
fDate
13-16 Dec. 2011
Firstpage
37
Lastpage
40
Abstract
The paper starts by reviewing the basics of the modern portfolio theory and its very well known drawbacks. After a brief overview of the existing literature that attempts to address these drawbacks, a novel portfolio mixing method is proposed. The method is then illustrated using US stock market data, and is shown to outperform both portfolios that it combines in a statistically significant way. Several avenues of further research are summarized to conclude the paper.
Keywords
investment; optimisation; US stock market data; portfolio mixing method; portfolio optimization; portfolio theory; weight shrinkage; Covariance matrix; Educational institutions; Estimation; Finance; Optimization; Portfolios; Vectors; Markowitz; Portfolios; covariance; diversification; finance; market; shrinkage; stock;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2011 4th IEEE International Workshop on
Conference_Location
San Juan
Print_ISBN
978-1-4577-2104-5
Type
conf
DOI
10.1109/CAMSAP.2011.6136031
Filename
6136031
Link To Document