P/E Mean Reversion on German Stocks: 10.39% CAGR With 36% Down-Capture
We tested a sector-relative P/E mean reversion screen on 25 years of German stock data from XETRA. The signal triggers when a stock's P/E ratio falls 40% below its sector median, filtered for quality. The strategy returned 10.39% annually vs 7.64% for the S&P 500, with 2.75% excess return, the highest Sharpe ratio of all 13 exchanges tested (0.404), and down-capture of just 35.84%.
Contents
- Method
- What Is Sector-Relative P/E Mean Reversion?
- The Screen
- Sector-Relative P/E Screen for XETRA (SQL)
- What We Found
- 25 years. 2.75% annual alpha. Best Sharpe ratio of 13 exchanges tested.
- The asymmetry story
- Year-by-year returns
- 2000-2001: resilience while SPY collapsed
- 2005-2007: pre-crisis surge
- 2008: the worst year
- 2016-2020: the growth regime drag
- 2022: standout downside protection
- 2024: Germany in recession
- Backtest Methodology
- Limitations
- Conclusion
Method
- Data source: Ceta Research (FMP financial data warehouse)
- Universe: XETRA, market cap > €500M
- Period: 2000-2024 (25 years, 0 cash periods)
- Rebalancing: Annual (January), equal weight, top 30 by discount to sector median
- Benchmark: S&P 500 Total Return (SPY)
- Cash rule: Hold cash if fewer than 10 stocks qualify
Financial data sourced from financial_ratios_ttm for P/E ratios and debt metrics, key_metrics_ttm for ROE and market cap, profile for sector classification. 45-day lag on all financial statements to prevent look-ahead bias.
What Is Sector-Relative P/E Mean Reversion?
This strategy looks for stocks trading at a steep discount to their own sector peers. If the median Industrials stock on XETRA trades at 18x earnings and a specific company trades at 10x, that's a 44% discount. The bet is that the gap closes: either the stock's multiple expands, its earnings grow, or both.
The key distinction from time-series P/E compression is the comparison point. We're not asking "is this stock cheap relative to its own history?" We're asking "is this stock cheap relative to what the market is currently paying for similar businesses?" That cross-sectional view updates with market conditions and doesn't require years of historical P/E data per stock.
Signal: - Stock P/E < 60% of sector median P/E (40%+ discount to peers) - P/E range: 3-50 (exclude loss-making and extreme valuations) - Minimum 5 stocks per sector required to compute a valid median
Quality filters:
| Criterion | Metric | Threshold |
|---|---|---|
| Profitable | Return on Equity | > 8% |
| Manageable debt | Debt-to-Equity | < 2.0 |
Size:
| Criterion | Metric | Threshold |
|---|---|---|
| Institutional grade | Market Cap | > €500M |
Stocks must pass all filters. The top 30 by deepest discount to sector median are selected each year, equal weighted.
The Screen
Sector-Relative P/E Screen for XETRA (SQL)
WITH universe AS (
SELECT k.symbol, p.companyName, p.exchange, p.sector,
fr.priceToEarningsRatioTTM AS pe_ttm, k.returnOnEquityTTM AS roe,
fr.debtToEquityRatioTTM AS de, k.marketCap
FROM key_metrics_ttm k
JOIN financial_ratios_ttm fr ON k.symbol = fr.symbol
JOIN profile p ON k.symbol = p.symbol
WHERE fr.priceToEarningsRatioTTM BETWEEN 3 AND 50
AND k.returnOnEquityTTM > 0.08
AND (fr.debtToEquityRatioTTM IS NULL OR (fr.debtToEquityRatioTTM >= 0 AND fr.debtToEquityRatioTTM < 2.0))
AND k.marketCap > 500000000
AND p.sector IS NOT NULL
AND p.exchange IN ('XETRA')
),
sector_medians AS (
SELECT exchange, sector,
PERCENTILE_CONT(0.5) WITHIN GROUP (ORDER BY pe_ttm) AS median_pe,
COUNT(*) AS n_sector_stocks
FROM universe GROUP BY exchange, sector HAVING COUNT(*) >= 5
)
SELECT u.symbol, u.companyName, u.sector,
ROUND(u.pe_ttm, 2) AS pe_ttm, ROUND(sm.median_pe, 2) AS sector_median_pe,
ROUND(u.pe_ttm / sm.median_pe, 3) AS pe_ratio_to_sector,
ROUND((1 - u.pe_ttm / sm.median_pe) * 100, 1) AS discount_pct,
ROUND(u.roe * 100, 1) AS roe_pct, ROUND(u.de, 2) AS debt_to_equity,
ROUND(u.marketCap / 1e6, 0) AS mktcap_m_eur
FROM universe u JOIN sector_medians sm ON u.exchange = sm.exchange AND u.sector = sm.sector
WHERE u.pe_ttm / sm.median_pe < 0.60
ORDER BY u.pe_ttm / sm.median_pe ASC LIMIT 30
Run this query on Ceta Research
What We Found
25 years. 2.75% annual alpha. Best Sharpe ratio of 13 exchanges tested.
| Metric | P/E Mean Reversion (Germany) | S&P 500 |
|---|---|---|
| CAGR | 10.39% | 7.64% |
| Total Return | 1,083.84% | 530.71% |
| Sharpe Ratio | 0.404 | 0.322 |
| Sortino Ratio | 0.707 | 0.556 |
| Max Drawdown | -48.68% | -34.90% |
| Up Capture | 107.51% | 100% |
| Down Capture | 35.84% | 100% |
| Win Rate vs SPY | 48% | - |
| Avg Stocks per Year | 18.8 | - |
| Cash Periods | 0 of 25 | - |
$10,000 grew to $118,384 vs $63,071 for the S&P 500. That's nearly double the terminal wealth, despite returns denominated in EUR against a USD benchmark.
The Sharpe ratio of 0.404 ranked first across all 13 exchanges in this study. The Sortino jumped from 0.556 to 0.707. The down-capture of 35.84% is the standout number: on average, when SPY lost 10%, this portfolio lost just 3.6%.
Zero cash periods. The German market across sectors consistently produced qualifying stocks meeting the P/E discount, quality, and size filters every single year over 25 years.
The asymmetry story
The win rate is 48%. The strategy beat SPY in fewer than half the individual years. Yet it delivered +2.75% annual alpha and roughly doubled SPY's terminal wealth. That's not a contradiction. It's an asymmetric return profile.
When Germany value wins, it wins big. The early 2000s, 2005-2007, and the 2022 inflation shock all produced large positive excess returns. When it loses, the losses are smaller in magnitude. A 36% down-capture ratio means the drag in bad years is damped relative to the gains in good years. Over 25 years, the compounding does the rest.
Year-by-year returns
| Year | P/E Mean Reversion | S&P 500 | Excess |
|---|---|---|---|
| 2000 | +19.5% | -10.5% | +30.0% |
| 2001 | +19.0% | -9.2% | +28.2% |
| 2002 | -20.7% | -19.9% | -0.8% |
| 2003 | +40.1% | +24.1% | +16.0% |
| 2004 | +6.8% | +10.2% | -3.5% |
| 2005 | +30.2% | +7.2% | +23.1% |
| 2006 | +32.9% | +13.7% | +19.3% |
| 2007 | +31.5% | +4.4% | +27.1% |
| 2008 | -48.7% | -34.3% | -14.4% |
| 2009 | +23.8% | +24.7% | -0.9% |
| 2010 | +29.6% | +14.3% | +15.3% |
| 2011 | -6.1% | +2.5% | -8.6% |
| 2012 | +26.3% | +17.1% | +9.2% |
| 2013 | +35.4% | +27.8% | +7.6% |
| 2014 | +13.3% | +14.5% | -1.2% |
| 2015 | +13.9% | -0.1% | +14.1% |
| 2016 | +3.8% | +14.4% | -10.6% |
| 2017 | +12.9% | +21.6% | -8.7% |
| 2018 | -11.8% | -5.2% | -6.6% |
| 2019 | +20.8% | +32.3% | -11.5% |
| 2020 | +11.2% | +15.6% | -4.5% |
| 2021 | +34.8% | +31.3% | +3.5% |
| 2022 | -6.5% | -19.0% | +12.5% |
| 2023 | +12.9% | +26.0% | -13.1% |
| 2024 | -8.7% | +25.3% | -33.9% |
2000-2001: resilience while SPY collapsed
The dot-com crash hit US growth stocks hardest. Germany's value-tilted industrial and financial sectors stayed steady. While the S&P 500 dropped -10.5% and -9.2% in back-to-back years, this portfolio returned +19.5% and +19.0%. The cumulative gap from those two years alone was +58 percentage points.
The sector-relative screen filtered toward companies that were cheap within their own industry context, not just cheap in absolute terms. German industrials and consumer names trading at discounts to sector peers had less air to let out when sentiment turned negative.
2005-2007: pre-crisis surge
Three consecutive years of strong outperformance: +23.1%, +19.3%, and +27.1% excess returns. This was the peak of the European economic expansion, and German exporters and financials were pricing in high earnings growth. Stocks trading at discounts to sector medians caught up as earnings reverted upward.
By the end of 2007, the portfolio was ahead of SPY on a cumulative basis.
2008: the worst year
| Event | P/E Mean Reversion | S&P 500 | Gap |
|---|---|---|---|
| Dot-com bust (2000-2002) | +14.5% | -35.1% | +49.6% |
| Financial crisis (2008) | -48.7% | -34.3% | -14.4% |
| Euro debt/growth slowdown (2011) | -6.1% | +2.5% | -8.6% |
| 2022 inflation shock | -6.5% | -19.0% | +12.5% |
2008 was brutal. German industrials and financials were directly exposed to the global credit crisis. The -48.68% drawdown exceeded SPY's -34.3% by 14 percentage points. No quality filter protects a concentrated portfolio of small-to-mid-cap German stocks when the global financial system seizes up.
The down-capture advantage of 36% is a 25-year average. Individual crisis years can be far worse. 2008 proves that.
2016-2020: the growth regime drag
Five of these years produced negative excess returns, with 2016, 2017, 2019, and 2020 all underperforming SPY by more than 4 percentage points. Global capital was repricing toward tech and US growth assets. German industrials and chemicals companies, even when cheap relative to sector peers, weren't the destination.
The Dax underperformed US indices for most of this period anyway. The value tilt made it worse.
2022: standout downside protection
The inflation shock of 2022 was different. When high-multiple growth stocks collapsed under rising rates, German value stocks held up. The portfolio fell only -6.5% while SPY dropped -19.0%, a +12.5% excess return. That's the asymmetry working: the strategy has low exposure to the duration risk embedded in growth stocks, so rate-driven selloffs hit it less.
2024: Germany in recession
The most severe underperformance year was 2024: -33.9% excess return (-8.7% portfolio vs +25.3% SPY). Germany entered recession. German industrial output declined. Automotive and chemicals earnings contracted. The same sectors that drove outperformance in earlier years became the drag when the domestic economy stalled while the US AI trade sent tech valuations higher.
Backtest Methodology
Full methodology documentation: backtests/METHODOLOGY.md
| Parameter | Choice |
|---|---|
| Universe | XETRA, Market Cap > €500M |
| Signal | Stock P/E < 60% of sector median, P/E 3-50, ROE > 8%, D/E < 2.0 |
| Portfolio | Top 30 by deepest discount to sector median, equal weight |
| Rebalancing | Annual (January) |
| Cash rule | Hold cash if < 10 qualify |
| Benchmark | S&P 500 Total Return (SPY) |
| Period | 2000-2024 (25 years) |
| Data | Point-in-time (45-day lag on FY financial statements) |
| Transaction costs | 0.1% one-way (size-tiered by market cap) |
Limitations
Severe 2008 drawdown. The -48.68% max drawdown is substantially worse than SPY's -34.90%. German industrials and financials were among the hardest-hit sectors in the global financial crisis. The 36% average down-capture doesn't protect against years when sector-relative discounts don't matter because everything sells.
Small effective portfolio in early years. From 2000 to 2003, the XETRA universe after quality and size filters produced only 4-8 qualifying stocks in some years. Returns are real but concentration risk was high. The 18.8 average across all 25 years is dragged down by these early years.
Win rate of 48%. The strategy underperformed in more individual years than it outperformed. Investors who evaluate performance annually will see losses relative to SPY in most years. The payoff comes from the asymmetric size of wins vs losses, not from frequency. That requires conviction.
EUR vs USD returns. The portfolio returns are in EUR. The benchmark (SPY) is in USD. Currency movement adds or removes return for non-EUR investors. A European investor gets these returns directly. A USD-based investor needs to account for EUR/USD fluctuation.
2024 recession sensitivity. Germany's economic cycle is heavily tied to global industrial production and China demand. When those slow simultaneously, the industrial-heavy XETRA universe compresses earnings and multiples together. The sector-relative filter finds "cheap" stocks, but cheap can get cheaper when the whole sector is under pressure.
Sector concentration. Without a sector cap, the screen can cluster in Industrials and Consumer Cyclical names in down cycles. Single-sector concentration risk isn't bounded by the strategy design.
Conclusion
Sector-relative P/E mean reversion on XETRA delivered 10.39% CAGR over 25 years, with the highest Sharpe ratio of 13 exchanges tested (0.404) and down-capture of just 35.84%. The $10,000 terminal value of $118,384 vs $63,071 for SPY shows the compounding effect of that asymmetric structure.
The win rate of 48% tells the real story. This isn't a strategy that beats SPY most years. It's one that wins big when German value reverts and limits losses when it doesn't. That asymmetry, sustained over 25 years, compounds into meaningful outperformance.
The strategy works best in macro environments where European industrials and quality value names are in favor: the post-dot-com recovery, 2005-2007 expansion, 2010 rebound, and 2022 value rotation all delivered. It struggles when US growth dominates or when Germany's domestic economy faces structural headwinds.
For investors with European equity exposure, a sector-relative discount screen adds a systematic quality and value tilt that has historically paid off over full cycles.
Part of a Series: Global | US | UK | India
Run It Yourself
Explore the data behind this analysis on Ceta Research. Query our financial data warehouse with SQL, build custom screens, and run your own backtests across 70,000+ stocks on 20 exchanges.
Data: Ceta Research (FMP financial data warehouse). Returns in EUR (local currency). Benchmark S&P 500 in USD. Past performance doesn't guarantee future results. See full methodology at github.com/ceta-research/backtests.
