Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/213444
Authors: 
Zhao, Zhao
Ledoit, Olivier
Jiang, Hui
Year of Publication: 
2020
Series/Report no.: 
Working Paper 328
Abstract: 
We investigate the effects of constraining leverage and shrinking covariance matrix in constructing large portfolios, both theoretically and empirically. Considering a wide variety of setups that involve conditioning or not conditioning the covariance matrix estimator on the recent past (multivariate GARCH), smaller vs. larger universe of stocks, alternative portfolio formation objectives (Global Minimum Variance vs. exposure to profitable factors), and various transaction cost assumptions, we find that a judiciously-chosen shrinkage method always outperforms an arbitrarily-determined leverage constraint. By extending the mathematical connection between leverage and shrinkage from static to dynamic, we provide a new theoretical explanation for our finding from the perspective of degrees of freedom. In addition, both simulation and empirical analysis show that the DCC-NL estimator results in risk reduction and efficiency increase in large portfolios as long as a small amount of leverage is allowed, whereas tightening the leverage constraint often hurts a DCC-NL portfolio.
Subjects: 
DCC
Nonlinear shrinkage
Leverage constraint
Large portfolios
Risk reduction
Markowitz mean-variance efficiency
JEL: 
C13
C58
G11
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.