The Predictive Power of SIRRIPA as a Forward-Looking Equity Return Metric: Empirical Evidence from U.S. Technology Stocks (2024–2026)

This article introduces and empirically evaluates SIRRIPA (Stock Internal Rate of Return Including Price Appreciation) as a structural, forward-looking return metric for equities. Unlike traditional valuation ratios expressed in price space—most notably the P/E ratio—SIRRIPA expresses valuation directly in return space and is derived from the Potential Payback Period (PPP), a time-based valuation framework that explicitly incorporates earnings growth, discounting, and time. Using a sample of 15 major U.S. technology companies, SIRRIPA is calculated as of February 9, 2024 and compared to realized stock price performance over the subsequent two-year period ending February 9, 2026. We find a strong positive relationship between SIRRIPA and realized performance, with a Pearson correlation of 0.63 across the full sample. When one firm affected by exogenous regulatory and governance shocks (Super Micro Computer) is excluded, the correlation rises to 0.74, explaining more than half of the cross-sectional variation in realized returns. For comparison, we also examine the predictive behavior of the P/E ratio measured at the same date. Contrary to its conventional interpretation as a valuation warning signal, higher P/E ratios were not associated with weaker subsequent performance. This result highlights the limitations of static valuation multiples that omit growth and discounting effects and exhibit wide, economically ambiguous dispersion. Overall, the findings provide empirical evidence that return-based structural metrics such as SIRRIPA offer more coherent and interpretable predictive content than traditional price-space ratios.