A Hybrid Valuation Framework and Dynamic Asset Allocation Strategy: Evidence from U. S. Markets (2000–2024)

DOI: https://doi.org/10.62517/jse.202611110

Author(s)

Diyu Wang1, Ruixuan Wang2, Zihan Wang3,*

Affiliation(s)

Beijing Normal-Hong Kong Baptist University, Zhuhai, China *Corresponding Author

Abstract

This study proposes a hybrid valuation framework that integrates discounted cash flow (DCF) models, the Capital Asset Pricing Model (CAPM), and statistical factor analysis to evaluate pricing discrepancies in U. S. equity and bond markets, and constructs a valuation-driven dynamic investment strategy. Using monthly data from January 2000 to December 2024 for the S&P 500 Index and Bloomberg Barclays U. S. Aggregate Bond Index, theoretical prices are estimated and deviations are quantified. For bonds, the DCF model yields a theoretical price close to the IEF ETF market price (0.44% premium at end-2019), with liquidity dynamics and interest rates as primary drivers. For equities, the constant growth dividend discount model (DDM) produces a theoretical S&P 500 level far below the actual market price, highlighting model limitations. Building on these insights, a dynamic strategy is designed that adjusts equity weight between 50% and 70% based on the S&P 500's P/E ratio relative to its historical median. Back testing from 2008 to 2024 shows the dynamic strategy outperforms the static 60/40 benchmark on all metrics: annualized return (7.85% vs. 7.12%), volatility (7.92% vs. 8.34%), maximum drawdown (-24.18% vs. -28.45%), and Sharpe ratio (0.92 vs. 0.78). the strategy excels during bear markets and valuation recoveries. Decomposition analysis confirms excess returns stem from timing ability rather than static factor exposures.

Keywords

Dynamic Strategy; Dividend Discount Model; Capm; Sharpe Ratio

References

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