Earnings Yield Calculator
Calculate a stock's earnings yield — the inverse of P/E — as the percentage of earnings per share relative to current share price. Use it to compare equity returns directly against bond yields and CD rates for asset allocation decisions.
Last updated: May 2026
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About this calculator
The formula is straightforward: earningsYield = (EPS / stockPrice) × 100. This is the inverse of the P/E ratio expressed as a percentage. A stock with $5 EPS at $100 share price has earnings yield of 5% — meaning if all earnings were paid as dividends, the investor would receive 5% annual return on their share purchase. The metric makes equities directly comparable to fixed-income yields: a 5% earnings yield is roughly comparable to a 5% bond yield in terms of nominal current cash generation, though equities have additional risk and growth characteristics. Edge cases: zero or negative EPS produces zero or negative earnings yield (companies with losses cannot generate positive earnings yield); near-zero stock price approaches infinite yield (mathematical edge case for distressed stocks). Trailing EPS uses last-4-quarters data; forward EPS uses analyst projections; "normalized" EPS removes one-time items. Each tells a different story. The Fed Model (popularized in the 1990s) compared earnings yield directly to 10-year Treasury yield: when earnings yield > Treasury yield, equities offered better current returns and were attractive. This framework worked in some periods, broke down spectacularly in others (1990s tech bubble had earnings yield well below Treasury yield with continued equity rally for years; 2009-2021 had earnings yield far above Treasury yield with strong equity rally). Modern use: earnings yield is one input among many in valuation comparisons rather than a standalone signal. Comparing earnings yields across sectors helps identify relative value: high earnings yield + stable business model = potentially undervalued; low earnings yield + uncertain business = expensive growth bet. Always verify EPS quality (one-time gains, accounting restatements) before relying on the headline number.
How to use
Example 1 — Mature dividend stock. JPMorgan Chase (JPM): trailing EPS $16.50, share price $240. Enter earnings_per_share 16.50, stock_price 240. Result: (16.50 / 240) × 100 = 6.875% earnings yield. ✓ Compare to 10-year Treasury yield (~4.3% in late 2025); JPM's 6.9% earnings yield offers ~2.5% premium for equity risk and growth potential. This is consistent with a mature financial-sector stock; growth stocks (NVDA, TSLA) often have earnings yields below Treasury rates because the market prices in earnings growth. Example 2 — High-growth tech stock. Nvidia (NVDA): trailing EPS $2.20, share price $145. Enter 2.20, 145. Result: (2.20 / 145) × 100 = 1.52% earnings yield. ✓ Earnings yield well below Treasury yield (~4.3%). The market is pricing significant earnings growth — at current AI infrastructure spend trajectory, NVDA forward earnings could 2–3× over 3 years, pulling forward earnings yield into the 4–6% range. Whether this prices in too much growth or not enough is the central debate; earnings yield alone doesn't answer it, but reveals the implicit growth assumption.
Frequently asked questions
How is earnings yield different from P/E ratio?
Mathematically, earnings yield = 1 / P/E ratio (then multiply by 100 for percentage). A stock with P/E of 20 has earnings yield of 5%; P/E of 10 has earnings yield of 10%; P/E of 25 has earnings yield of 4%. The two metrics convey identical information but optimize for different mental models. P/E ratio: how many years of current earnings would it take to recoup the purchase price (assuming zero growth)? Earnings yield: what current annual return rate on capital does the stock represent? Earnings yield is more useful when comparing against other yield instruments (bonds, CDs, REITs) because the units match directly — 5% earnings yield versus 4.3% Treasury yield is an apples-to-apples comparison. P/E is more useful when comparing growth profiles across stocks within an industry. Most professional investors use both interchangeably and switch based on context. For sector ETFs and broad market indices, the inverse-P/E "earnings yield" of the index is the standard way to talk about market-level valuation versus bonds.
What is the Fed Model and does it work?
The Fed Model compares the S&P 500's earnings yield directly against the 10-year Treasury yield. When earnings yield > Treasury yield, the model says equities offer better current returns and are attractive; when earnings yield < Treasury yield, bonds are relatively more attractive. Background: a 1997 paper at the Federal Reserve referenced this comparison; the name "Fed Model" was popularized by analysts (Ed Yardeni and others) in the late 1990s. The model has critics. 1) Earnings are nominal; bond yields are nominal — but inflation expectations matter for relative attractiveness. 2) Earnings yield assumes earnings continue indefinitely; in reality earnings cycle and decline in recessions. 3) The model worked in the 1980s–2010s when the relationship was meaningful but failed in the 1990s tech bubble (low earnings yield, continued rally) and the 2009-2021 expansion (high earnings yield relative to Treasury, but Treasury yield was artificially low). 4) Across long historical periods, earnings yield and Treasury yields have not been consistently related. Modern view: the Fed Model is a useful starting framework for asset allocation discussion but not a reliable timing signal. Use it as one input among several (valuation cycles, sector positioning, macro context) rather than a standalone decision tool.
Should I prefer high or low earnings yield stocks?
High earnings yield (low P/E) stocks are typically classic "value" plays — established companies in mature industries trading at lower multiples. They generate current earnings reliably but often have lower growth expectations. Examples: financial sector (JPM, BAC, WFC often around 6-9% earnings yield); energy (XOM, CVX around 7-10%); utilities (DUK, NEE around 5-7%); some industrials. Low earnings yield (high P/E) stocks are "growth" plays — companies expected to grow earnings significantly over coming years, justifying current premium prices. Examples: AI/cloud (NVDA, AMD, MSFT around 2-4%); high-growth software (CRM, NOW around 2-4%); biotech with pipeline assets. Neither category is universally "better." Long-run academic evidence (Fama-French factors) shows value stocks have outperformed growth stocks across many time periods, but with significant drag during specific eras (1990s tech, 2010s growth bull). Portfolio approach: diversify across both. Pure value strategies risk holding declining businesses (value traps where earnings yield is high because earnings are about to decline); pure growth strategies risk paying too much for uncertain future growth. Most balanced portfolios hold both with rebalancing based on relative valuation. Check earnings yield quality: a $5 EPS that came from one-time legal settlement gain is not as reliable as $5 EPS from recurring operations.
What are the most common mistakes with earnings yield?
The biggest is using trailing EPS for cyclical companies near earnings peaks (auto manufacturers, semiconductors, commodities) — high trailing earnings yield can flip to low when the cycle turns. Use normalized or forward EPS for cyclical analysis. The second is relying on GAAP EPS without checking for one-time items (tax benefits, asset sales, restructuring gains/losses); adjusted/non-GAAP EPS often better reflects ongoing earnings power. The third is comparing earnings yield across industries without context; financial sector "normal" earnings yield differs from tech sector "normal." Compare to peer group averages, not cross-industry. The fourth is treating earnings yield as a guarantee of cash return; companies retain most earnings for reinvestment, so investors get earnings via stock appreciation rather than cash. Dividend yield (cash actually paid) is often much lower than earnings yield (payout ratios 20–60% common). The fifth is forgetting that earnings yield is point-in-time; stock price moves continuously while EPS updates only quarterly. The sixth is using earnings yield in isolation without considering growth — a 5% earnings yield with 10% earnings growth is not equivalent to 5% earnings yield with 0% growth. PEG ratio and price-to-earnings-growth metrics adjust for this. The seventh is ignoring debt — a highly leveraged company with high earnings yield may have those earnings consumed by interest payments; check earnings yield relative to enterprise value, not just market cap. The eighth is comparing earnings yield directly to Treasury yields without accounting for equity risk premium; equities have additional risk vs Treasuries.
When should I not use earnings yield?
Skip it for companies with negative or near-zero earnings (early-stage growth, biotech, companies in restructuring) where the formula breaks or produces meaningless results; use revenue, price-to-sales, or enterprise-value-to-sales instead. It is the wrong tool for REITs which trade on FFO (Funds From Operations) rather than GAAP earnings — use price-to-FFO yield instead. Do not use it for banks and insurance without adjusting for asset/liability structure; their earnings can be misleading (insurers had massive 2008 earnings yield right before huge losses). For commodity-cycle companies near peak earnings, use normalized earnings rather than current; energy and mining stocks at peak earnings yield often disappoint. For tech and high-growth stocks where earnings will multiply many times in coming years, current earnings yield is largely irrelevant — forward earnings yield (1-2 years out) is more meaningful. For valuation across countries, account for different accounting standards and tax regimes (Japan, China, EU have different GAAP/IFRS implementations). For private companies, you cannot use traditional earnings yield because the share price is not publicly known; use private market multiples instead. And for periods of significant economic disruption (2009, 2020), trailing earnings yields are temporarily distorted; wait for normalization before relying on the metric.