The Requirement of a Positive Definite Covariance Matrix of Security Returns for Mean-Variance Portfolio Analysis: A Pedagogic Illustration

This study considers, from a pedagogic perspective, a crucial requirement for the covariance matrix of security returns in mean-variance portfolio analysis. Although the requirement that the covariance matrix be positive definite is fundamental in modern finance, it has not received any attention...

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Main Author: Clarence C. Y. Kwan
Format: Article
Language:English
Published: Bond University 2010-07-01
Series:Spreadsheets in Education
Subjects:
Online Access:http://epublications.bond.edu.au/ejsie/vol4/iss1/4
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spelling doaj-82c958b2e8fb47da849482c4a0479a3a2020-11-25T02:15:25ZengBond UniversitySpreadsheets in Education1448-61562010-07-01411078The Requirement of a Positive Definite Covariance Matrix of Security Returns for Mean-Variance Portfolio Analysis: A Pedagogic IllustrationClarence C. Y. KwanThis study considers, from a pedagogic perspective, a crucial requirement for the covariance matrix of security returns in mean-variance portfolio analysis. Although the requirement that the covariance matrix be positive definite is fundamental in modern finance, it has not received any attention in standard investment textbooks. Being unaware of the requirement could cause confusion for students over some strange portfolio results that are based on seemingly reasonable input parameters. This study considers the requirement both informally and analytically. Electronic spreadsheet tools for constrained optimization and basic matrix operations are utilized to illustrate the various concepts involved.http://epublications.bond.edu.au/ejsie/vol4/iss1/4Mean-Variance Portfolio AnalysisPositive Definite Covariance MatrixExcel Illustration
collection DOAJ
language English
format Article
sources DOAJ
author Clarence C. Y. Kwan
spellingShingle Clarence C. Y. Kwan
The Requirement of a Positive Definite Covariance Matrix of Security Returns for Mean-Variance Portfolio Analysis: A Pedagogic Illustration
Spreadsheets in Education
Mean-Variance Portfolio Analysis
Positive Definite Covariance Matrix
Excel Illustration
author_facet Clarence C. Y. Kwan
author_sort Clarence C. Y. Kwan
title The Requirement of a Positive Definite Covariance Matrix of Security Returns for Mean-Variance Portfolio Analysis: A Pedagogic Illustration
title_short The Requirement of a Positive Definite Covariance Matrix of Security Returns for Mean-Variance Portfolio Analysis: A Pedagogic Illustration
title_full The Requirement of a Positive Definite Covariance Matrix of Security Returns for Mean-Variance Portfolio Analysis: A Pedagogic Illustration
title_fullStr The Requirement of a Positive Definite Covariance Matrix of Security Returns for Mean-Variance Portfolio Analysis: A Pedagogic Illustration
title_full_unstemmed The Requirement of a Positive Definite Covariance Matrix of Security Returns for Mean-Variance Portfolio Analysis: A Pedagogic Illustration
title_sort requirement of a positive definite covariance matrix of security returns for mean-variance portfolio analysis: a pedagogic illustration
publisher Bond University
series Spreadsheets in Education
issn 1448-6156
publishDate 2010-07-01
description This study considers, from a pedagogic perspective, a crucial requirement for the covariance matrix of security returns in mean-variance portfolio analysis. Although the requirement that the covariance matrix be positive definite is fundamental in modern finance, it has not received any attention in standard investment textbooks. Being unaware of the requirement could cause confusion for students over some strange portfolio results that are based on seemingly reasonable input parameters. This study considers the requirement both informally and analytically. Electronic spreadsheet tools for constrained optimization and basic matrix operations are utilized to illustrate the various concepts involved.
topic Mean-Variance Portfolio Analysis
Positive Definite Covariance Matrix
Excel Illustration
url http://epublications.bond.edu.au/ejsie/vol4/iss1/4
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