Fundamental Analysis and Mean-Variance Optimal Portfolios

Matthew R. Lyle, Teri Lombardi Yohn

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

We integrate fundamental analysis with mean-variance portfolio optimization to form fully optimized fundamental portfolios. We find that fully optimized fundamental portfolios produce large out-of-sample factor alphas with high Sharpe ratios. They substantially outperform equal-weighted and value-weighted portfolios of stocks in the extreme decile of expected returns, an approach commonly used in fundamental analysis research. They also outperform the factor-based and parametric portfolio policy approaches used in the prior portfolio optimization literature. The relative performance gains from mean-variance optimized fundamental portfolios are persistent through time, robust to eliminating small capitalization firms from the investment set, and robust to incorporating estimated transactions costs. Our results suggest that future fundamental analysis research could implement this portfolio optimization approach to provide greater investment insights.

Original languageEnglish (US)
Pages (from-to)303-327
Number of pages25
JournalAccounting Review
Volume96
Issue number6
DOIs
StatePublished - Apr 2022

Keywords

  • fundamental analysis
  • fundamentals-based expected returns
  • modeling
  • portfolio optimization
  • valuation

ASJC Scopus subject areas

  • Accounting
  • Finance
  • Economics and Econometrics

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