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The cyclically adjusted price/earnings ratio was introduced by John Campbell and Robert Shiller in their 1988 research paper, “Stock Prices, Earnings, and Expected Dividends.” The Shiller CAPE ratio is the most widely followed long-term valuation metric in finance. Central banks, the International Monetary Fund, and the Bank for International Settlements all cite it.

Researchers have documented its strong negative relationship with subsequent 10-year stock returns: When the CAPE ratio is high, future returns tend to be lower, and vice versa. In a June 2026 study, “Aggregation Consistency and Return Predictability: Evidence from CAPE Ratios,” a group of researchers raises an important problem with the conventional CAPE ratio and offers a straightforward fix that meaningfully improves its forecasting power.

The CAPE ratio’s problem: A hidden weighting mismatch

The standard CAPE ratio—call it the Aggregate CAPE ratio—is calculated by dividing the S&P 500 price level by the average of the past 10 years of total index earnings. This seems intuitive. However, the authors show it contains a flaw. Because the denominator is constructed by summing individual firm earnings, the resulting ratio is implicitly an earnings-weighted average of firm-level CAPE ratios.

That matters because stock market returns are value-weighted. Each company’s contribution to index returns is proportional to its market capitalization, not its earnings. High-CAPE companies (today’s mega-cap technology firms) have high prices relative to their earnings. That means their earnings are small relative to their market cap, so they receive less weight in the Aggregate CAPE than they deserve based on their actual influence on index returns. The conventional CAPE ratio systematically underweights the most expensive—and often the largest—stocks in the index.

The paper’s authors prove mathematically that the gap between the Aggregate CAPE ratio and a correctly constructed value-weighted CAPE ratio equals the cross-sectional variance in firm-level CAPE ratios divided by the Aggregate CAPE ratio itself. This means the distortion grows precisely when it matters most: during periods of high valuation dispersion across stocks, which often coincide with market extremes.

The fix: a component CAPE ratio

The solution is straightforward. Rather than aggregating earnings to the index level and then dividing by the index price, the authors calculate a CAPE ratio for each S&P 500 constituent and then take the value-weighted (market-cap-weighted) average of those firm-level CAPE ratios. They call this the Component CAPE ratio.

The Component CAPE ratio is consistently and significantly higher than the conventional Aggregate CAPE ratio. Using data from 1964 through 2024, the average Component CAPE ratio (10-year earnings) is 29.74, versus 21.65 for the Aggregate CAPE ratio—a difference of more than 37%. And as the theory predicts, the gap widens during periods of high valuation dispersion, such as the late-1990s tech bubble and the recent concentration of mega-cap technology stocks.

This is not a trivial distinction. The current Aggregate CAPE ratio, widely reported by Shiller and cited extensively in the financial media, materially understates the true valuation of the S&P 500 as experienced by investors holding the index.

The forecasting evidence

The empirical results are compelling. In-sample, the Component CAPE ratio explains 73.9% of the variation in subsequent 10-year returns, compared with 58.8% for the Aggregate CAPE ratio—a difference in R-squared of 15 percentage points, statistically significant at the 10% level. For five-year earnings versions of the ratio, the Component CAPE ratio’s advantage is even larger: 71.4% versus 52.4%, with the difference significant at the 5% level.

The out-of-sample results are equally strong. Using a constant-slope forecasting approach across 10-year periods beginning in 1974 and rolling forward annually through 2015, the Component CAPE ratio’s out-of-sample R-squared is 57.5%, versus 46.7% for the Aggregate CAPE ratio—an improvement of nearly 11 percentage points, significant at the 1% level. For five-year earnings, the gap is even larger at nearly 14 percentage points. The Component CAPE ratio outperforms across both early and later subsamples, suggesting the results are not period-specific.

The authors also decompose the mean squared forecast error into bias and variance components. The Aggregate CAPE ratio’s inferior performance is driven primarily by systematic forecast bias—exactly what the theory predicts—rather than by noisier estimates. The Component CAPE ratio is simply a more accurate representation of the valuation signal relevant to forecasting value-weighted index returns.

The improvement extends to longer horizons. For 15-year forecasts, the Component CAPE ratio’s out-of-sample R-squared reaches 70.3%; for 20-year forecasts, it reaches 75.8%. The Aggregate CAPE ratio lags meaningfully at both horizons.

Asset allocation value

The authors translate these statistical improvements into economic terms using certainty-equivalent returns for a risk-averse investor allocating between equities and Treasury bills based on CAPE ratio signals. Under power utility assumptions with no leverage, a strategy based on the Component 10-Year Earnings CAPE ratio achieves a CER of 5.97%, compared with 5.62% for the Aggregate 10-Year CAPE ratio and 5.39% for the historical mean benchmark. The Component CAPE ratio also dominates a static 60/40 portfolio and a fully invested equity portfolio. These results hold under multiple utility specifications and both with and without leverage.

The results are also robust to a wide range of alternative CAPE ratio constructions: exponentially weighted earnings, total return CAPE ratio (which adjusts for buybacks), when each year’s earnings are adjusted for retained earnings, street earnings (which exclude special items), and payout-adjusted CAPE ratios. In nearly every variant, the Component CAPE ratio version outperforms the Aggregate CAPE ratio.

Key investor takeaways

Several practical implications follow from this research:

  • The widely quoted Shiller CAPE ratio materially understates the true valuation of the S&P 500 as experienced by index investors. Because the conventional ratio underweights high-CAPE, high-market-cap companies, investors who rely on it to assess market valuation are working with a biased signal. The market is, in an important sense, more expensive than the conventional CAPE ratio suggests.
  • The distortion is not fixed—it varies with cross-sectional valuation dispersion. In today’s environment, where a small number of mega-cap technology companies trade at CAPE ratios far above the index average and constitute a historically large share of index market cap, the gap between the Aggregate and Component CAPE ratios is likely near its widest. Investors using the conventional CAPE ratio as a market-timing or asset allocation tool may be systematically underestimating the headwind to future returns.
  • The predictive improvement from the Component CAPE ratio is not merely statistical. It translates into meaningful economic gains for investors using CAPE-based signals to calibrate their equity allocations. The fix is conceptually simple and grounded in a clear theoretical framework: The weighting of the valuation signal should match the weighting of the returns being forecast.
  • The underlying insight extends beyond the CAPE ratio. The authors note that other aggregate valuation ratios—such as dividend yield and book/price—may be subject to similar weighting mismatches whenever individual firm data is summed to produce an index-level ratio and then used to forecast value-weighted returns. This is a methodological issue worth examining across the broader return predictability literature.

The bottom line

The CAPE ratio remains the best single predictor of long-horizon equity returns. But the conventional version is built on a structural flaw. The Component CAPE ratio, constructed by value-weighting firm-level CAPE ratios rather than aggregating earnings, is both theoretically correct and empirically superior. Investors and researchers who rely on the CAPE ratio as a valuation and forecasting tool should take note.

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