Asset pricing model uncertainty: a tradeoff between bias and variance

Research output: Contribution to journalArticleResearchpeer-review

Abstract

This paper draws a parallel between model combination and the mean–
variance tradeoff in Modern Portfolio Theory (Markowitz 1952) and proposes
a bias–variance tradeoff framework. Building on the bias–variance tradeoff
framework, the paper proposes a Model Portfolio Approach (MPA) and a
Global Minimum Variance (GMV) weighting scheme to mitigate asset pricing
model uncertainty. Using a well-conditioned pricing covariance estimator,
the proposed approach improves out-of-sample pricing performance over six
widely used asset pricing models, a model selection method and two most
popular benchmarks in existing model combination studies, that is, the
simple arithmetic average (“1/N”) and Ordinary Least Square (OLS) weighting
methods.
LanguageEnglish
Pages289-324
Number of pages36
JournalInternational Review of Finance
Volume17
Issue number2
DOIs
Publication statusPublished - 2017
Externally publishedYes

Fingerprint

Trade-offs
Model uncertainty
Asset pricing models
Pricing
Modern portfolio theory
Mean-variance
Assets
Minimum variance
Uncertainty
Estimator
Model selection
Portfolio model
Weighting
Ordinary least squares
Benchmark

Cite this

@article{28748b528b8c41118709228f764a9c91,
title = "Asset pricing model uncertainty: a tradeoff between bias and variance",
abstract = "This paper draws a parallel between model combination and the mean–variance tradeoff in Modern Portfolio Theory (Markowitz 1952) and proposesa bias–variance tradeoff framework. Building on the bias–variance tradeoffframework, the paper proposes a Model Portfolio Approach (MPA) and aGlobal Minimum Variance (GMV) weighting scheme to mitigate asset pricingmodel uncertainty. Using a well-conditioned pricing covariance estimator,the proposed approach improves out-of-sample pricing performance over sixwidely used asset pricing models, a model selection method and two mostpopular benchmarks in existing model combination studies, that is, thesimple arithmetic average (“1/N”) and Ordinary Least Square (OLS) weightingmethods.",
author = "Qing Zhou",
year = "2017",
doi = "10.1111/irfi.12112",
language = "English",
volume = "17",
pages = "289--324",
journal = "International Review of Finance",
issn = "1369-412X",
publisher = "John Wiley & Sons",
number = "2",

}

Asset pricing model uncertainty : a tradeoff between bias and variance. / Zhou, Qing.

In: International Review of Finance, Vol. 17, No. 2, 2017, p. 289-324.

Research output: Contribution to journalArticleResearchpeer-review

TY - JOUR

T1 - Asset pricing model uncertainty

T2 - International Review of Finance

AU - Zhou,Qing

PY - 2017

Y1 - 2017

N2 - This paper draws a parallel between model combination and the mean–variance tradeoff in Modern Portfolio Theory (Markowitz 1952) and proposesa bias–variance tradeoff framework. Building on the bias–variance tradeoffframework, the paper proposes a Model Portfolio Approach (MPA) and aGlobal Minimum Variance (GMV) weighting scheme to mitigate asset pricingmodel uncertainty. Using a well-conditioned pricing covariance estimator,the proposed approach improves out-of-sample pricing performance over sixwidely used asset pricing models, a model selection method and two mostpopular benchmarks in existing model combination studies, that is, thesimple arithmetic average (“1/N”) and Ordinary Least Square (OLS) weightingmethods.

AB - This paper draws a parallel between model combination and the mean–variance tradeoff in Modern Portfolio Theory (Markowitz 1952) and proposesa bias–variance tradeoff framework. Building on the bias–variance tradeoffframework, the paper proposes a Model Portfolio Approach (MPA) and aGlobal Minimum Variance (GMV) weighting scheme to mitigate asset pricingmodel uncertainty. Using a well-conditioned pricing covariance estimator,the proposed approach improves out-of-sample pricing performance over sixwidely used asset pricing models, a model selection method and two mostpopular benchmarks in existing model combination studies, that is, thesimple arithmetic average (“1/N”) and Ordinary Least Square (OLS) weightingmethods.

UR - http://www.scopus.com/inward/record.url?scp=85006826713&partnerID=8YFLogxK

U2 - 10.1111/irfi.12112

DO - 10.1111/irfi.12112

M3 - Article

VL - 17

SP - 289

EP - 324

JO - International Review of Finance

JF - International Review of Finance

SN - 1369-412X

IS - 2

ER -