Uncertain Covariance Models

8 Pages Posted: 9 Jun 2015 Last revised: 25 Apr 2019

See all articles by Anish Shah

Anish Shah

Investment Grade Modeling

Date Written: August 17, 2016

Abstract

Covariance models of stock returns appear throughout the investment process, e.g., forecasting portfolio risk, hedging, constructing Markowitz return-risk optimal portfolios, and algorithmic trading. Models are usually point estimates, often classically inferred. Techniques are later applied to try to improve the forecast and generate distributions. However, making a decision requires one’s best prediction given the information at hand, along with estimates of accuracy. This paper presents a method for specifying a covariance model’s forecast errors and formulas for the consequent error in portfolio variance forecasts. The knowledge can be used statically to report uncertainty of fixed portfolios or considered during portfolio optimization.

Keywords: Covariance matrices, Estimation, Estimation error, Forecasting, Linear factor models, Portfolio optimization

JEL Classification: C00, C11, C53, G19

Suggested Citation

Shah, Anish, Uncertain Covariance Models (August 17, 2016). Available at SSRN: https://ssrn.com/abstract=2616109 or http://dx.doi.org/10.2139/ssrn.2616109

Anish Shah (Contact Author)

Investment Grade Modeling ( email )

Cogito
210 Broadway #201
Cambridge, MA 02139
United States

HOME PAGE: http://www.linkedin.com/in/anishrshah

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