Price-to-Tangible-Book in Germany: 8.83% CAGR and a Negative Down

Price-to-Tangible-Book in Germany: 8.83% CAGR and a Negative Down Capture That Decouples from US Drawdowns

The P/TBV strategy on Germany's XETRA exchange returned 8.83% annualised over 25 years, beating SPY's 7.83% by 1.00% per year. The CAGR is the least dramatic number in this dataset. The real story is down capture: -22.69%. When SPY falls, Germany's low-P/TBV stocks don't just hold their ground, they go up. In 2007, SPY dropped 13.71% while this portfolio gained 1.19%. That's not a hedge ratio anomaly. It's a structural feature of what XETRA's industrial base actually is.

Contents

  1. The Strategy
  2. What We Found
  3. Annual Returns
  4. The Current Screen
  5. Limitations
  6. Part of a Series

The Strategy

Price-to-Tangible-Book removes goodwill and intangible assets from book value before dividing into market cap: P/TBV = marketCap / (totalStockholdersEquity - goodwill - intangibleAssets). The result is a ratio that values only what physically exists in the business. Equipment, inventory, property, receivables.

German XETRA is dominated by Mittelstand-adjacent industrial companies: machinery manufacturers, automotive suppliers, chemical producers, specialty engineers. These businesses hold substantial tangible asset bases. Low P/TBV in Germany doesn't mean a distressed tech company trading below amortised software. It means a profitable manufacturer trading below the replacement value of its factories.

Quality filters prevent buying cheap-but-broken: ROE above 8%, ROA above 3%, operating profit margin above 10%. These keep the portfolio in companies generating real returns on their tangible base, not just cheap on paper.

Parameter Value
Signal P/TBV ascending (lowest first)
Quality filters ROE > 8%, ROA > 3%, OPM > 10%
Rebalance Annual (July), 45-day filing lag
Portfolio size Top 30, equal weight
Minimum stocks 10 (else cash)
Market cap threshold €500M (~$545M USD)
Universe XETRA (Germany)
Period 2000-2025 (25 years)
Benchmark SPY

What We Found

Germany's most visible number is 2000: +68.80% while SPY lost 14.78%. That's an 83-percentage-point gap in a single year. German manufacturers, automotive companies, and chemical producers had no exposure to the US dot-com bubble. They made things. Their book values were tangible. When US equities collapsed on multiple compression in growth names, XETRA's industrial base re-rated upward as global earnings held steady. Low P/TBV captured exactly that: companies that were cheap on tangible assets and profitable, in a market uncorrelated to what was imploding in the US.

The down capture of -22.69% is the defining characteristic. A negative down capture means the portfolio has historically gained in years when the benchmark fell. This isn't a hedging artefact. It's the result of holding companies whose earnings drivers are European industrial demand, not US consumer sentiment or tech growth rates. Beta of 0.482 confirms it: German tangible-book stocks move at roughly half the speed of SPY, and sometimes in the opposite direction.

The 2007-2008 sequence tells that story clearly. In 2007, the strategy returned +1.19% while SPY dropped 13.71%. In 2008, when the financial crisis hit globally, the strategy fell 23.32% against SPY's 26.14%. Germany absorbed the crisis better. When the damage was systemic and unavoidable, the strategy still lost less.

2014 is another inflection: +17.45% against SPY's +7.38%. European industrial earnings held up as the ECB's accommodative policy supported capex cycles, and low-P/TBV German industrials re-rated as real asset values became more appreciated by European institutional money.

The recent years have been harder. 2019 brought -8.38% as German manufacturing contracted, especially in automotive (diesel scandal aftermath, EV transition costs). 2021 through 2024 saw a mixed picture: energy cost shocks post-2022 hit German industrials structurally, and that shows in the numbers. The strategy still kept pace in 2022 (+10.07%) and 2023 (+13.10%), but 2024 at +4.74% versus SPY's +14.67% reflects genuine pressure on the German industrial model.

Germany averaged 19.5 stocks per period with zero cash years. The quality filter maintained a viable universe throughout, which is notable given how tight the screen is.

Annual Returns

Year Strategy SPY
2000 +68.80% -14.78%
2001 -14.31% -20.77%
2002 -22.74% +3.29%
2003 +17.96% +16.44%
2004 +14.26% +7.94%
2005 +24.69% +8.86%
2006 +23.68% +20.95%
2007 +1.19% -13.71%
2008 -23.32% -26.14%
2009 +26.02% +13.42%
2010 +12.13% +32.94%
2011 -1.24% +4.10%
2012 +7.33% +20.85%
2013 +29.02% +24.50%
2014 +17.45% +7.38%
2015 -4.65% +3.36%
2016 +28.18% +17.73%
2017 +14.88% +14.34%
2018 +3.29% +10.91%
2019 -8.38% +7.12%
2020 +34.32% +40.68%
2021 -12.93% -10.17%
2022 +10.07% +18.31%
2023 +13.10% +24.60%
2024 +4.74% +14.67%

The Current Screen

The US screen is available at cetaresearch.com/data-explorer?q=z9gpaUlNfi. Exchange-specific queries for XETRA and other markets can be run on the data explorer at cetaresearch.com.


Limitations

Currency exposure is significant. Returns are calculated in EUR. A non-European investor takes on EUR/USD risk. Post-2022 EUR weakness has been a drag for USD-based investors in European equities.

The portfolio is structurally concentrated in industrials and chemicals. When German manufacturing faces a structural headwind, as it has since 2019 (automotive transition, energy costs), there's no diversification within the strategy's natural universe. The quality filter can't protect against sector-level economic deterioration.

Average portfolio size of 19.5 stocks is smaller than the target of 30. The €500M market cap threshold and quality filters together create a tight screen. The strategy has been capacity-constrained by design, which is a reasonable trade-off but worth understanding.

The 2000 return of +68.80% is real but not repeatable in isolation. It reflects a one-time decoupling event between US tech and German industrials during the dot-com collapse. Excluding 2000, the return profile is more modest. Don't use that single year to set return expectations.


Part of a Series

This post is part of a multi-exchange series on the Price-to-Tangible-Book strategy. The US flagship backtest, including full methodology and global results summary, is at ptbv-strategy-us-backtest.


Data: Ceta Research (FMP financial data warehouse), 2000-2025. Full methodology: backtests/METHODOLOGY.md

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