Etd

Comparative Analysis of Ledoit's Covariance Matrix and Comparative Adjustment Liability Management (CALM) Model Within the Markowitz Framework

Public

Downloadable Content

open in viewer

Estimation of the covariance matrix of asset returns is a key component of portfolio optimization. Inherent in any estimation technique is the capacity to inaccurately reflect current market conditions. Typical of Markowitz portfolio optimization theory, which we use as the basis for our analysis, is to assume that asset returns are stationary. This assumption inevitably causes an optimized portfolio to fail during a market crash since estimates of covariance matrices of asset returns no longer re ect current conditions. We use the market crash of 2008 to exemplify this fact. A current industry standard benchmark for estimation is the Ledoit covariance matrix, which attempts to adjust a portfolio's aggressiveness during varying market conditions. We test this technique against the CALM (Covariance Adjustment for Liability Management Method), which incorporates forward-looking signals for market volatility to reduce portfolio variance, and assess under certain criteria how well each model performs during recent market crash. We show that CALM should be preferred against the sample convariance matrix and Ledoit covariance matrix under some reasonable weight constraints.

Creator
Contributors
Degree
Unit
Publisher
Language
  • English
Identifier
  • etd-050814-143737
Keyword
Advisor
Defense date
Year
  • 2014
Date created
  • 2014-05-08
Resource type
Rights statement
Last modified
  • 2021-01-28

Relations

In Collection:

Items

Items

Permanent link to this page: https://digital.wpi.edu/show/gt54kn15p