---
title: 'We Backtested Price-to-Tangible-Book on 25 Years of Global Data'
source: 'https://www.youtube.com/watch?v=s14rTvRSBoA'
video_id: 's14rTvRSBoA'
date: 2026-09-13
duration_sec: 620
channel: 'Ceta Research'
---

# We Backtested Price-to-Tangible-Book on 25 Years of Global Data

> Source: [We Backtested Price-to-Tangible-Book on 25 Years of Global Data](https://www.youtube.com/watch?v=s14rTvRSBoA)

## Summary

This video presents a comprehensive global backtest of the price-to-tangible book value investment strategy across 15 exchanges over 25 years. It reveals that the strategy outperformed local benchmarks in 14 of 15 markets, with only Korea failing due to its chaebol corporate structure. The analysis includes detailed performance metrics, quality filters, and practical implementation details.

### Key Points

- **Global Outperformance** [00:00] — 14 of 15 global exchanges beat their local benchmark over 25 years using the price-to-tangible book value strategy. Only Korea fails. China's portfolio beat the SSE composite by 7.41% annually.
- **India's Performance** [00:18] — India beat the Sensex by 2.58% annually with a 64% win rate. In 2008, India gained 19.61% while the Sensex gained 7.27%.
- **Methodology: Market Cap Thresholds** [00:34] — Each exchange uses its own market cap threshold: $1 billion for NYSE, NASDAQ, Amex; $20 billion for India; $100 billion for Japan. Amex and SIO excluded due to data quality issues.
- **Universe and Filters** [00:59] — The universe is the full exchange, not a constrained index. Quality filters: ROE > 8%, ROA > 3%, operating profit margin > 10%. Annual rebalance in July with 45-day lag.
- **Tangible Equity Calculation** [02:10] — Tangible equity = total stockholders' equity - goodwill - intangible assets. Null values treated as zero. Positive tangible equity required; negative disqualifies.
- **Theoretical Basis** [03:14] — Companies valued on hard assets have a floor independent of market sentiment. Works best in manufacturing, financial services, and basic materials; struggles in services/software.
- **US Results** [03:27] — US CAGR 11.31% with down capture of 3.89%. Dot-com crash was the signal's finest hour: +25.20% in 2000 vs SPY -14.78%; +23.37% in 2001 vs SPY -22.45%.
- **India's Asset-Heavy Economy** [04:24] — India CAGR 14.64% vs Sensex 12.06%. 2008: +19.61% vs Sensex +7.27%. Recent results +42% (2022) and +69% (2023) reflect manufacturing boom.
- **China's Outperformance** [05:29] — China CAGR 9.84% vs SSE 2.43%, excess 7.41% annually with 72% win rate. Beta 0.958. 2008: +42.90% vs SSE +15.41%.
- **Germany's Results** [06:16] — Germany CAGR 6.90% vs DAX 5.40%, excess 1.86%. Worst drawdown -32% vs DAX -53%, beta 0.61.
- **Korea's Failure** [07:05] — Korea CAGR 4.06%, trailing KOSPI by 1.30%. Sat in cash 28% of time due to few qualifying stocks. Chaebol crossholdings muddy tangible book values.
- **Japan and Singapore** [07:35] — Japan beat Nikkei by 2% annually. Singapore CAGR 4.49% vs SPI, excess 1.82%, with average 12.5 stocks per period.
- **2019 Value Crash** [08:27] — 2019 hit all price-to-tangible book markets simultaneously due to global growth dominance. Not a failure of individual markets but a global factor rotation.
- **Limitations** [09:10] — Not a market timing tool. Tangible book is backward-looking (historical cost). Sector concentration toward financials remains a risk.

### Conclusion

Price-to-tangible book value is a robust global strategy, outperforming in 14 of 15 markets over 25 years. Its success hinges on asset-heavy economies, but it requires patience through multi-year underperformance and carries risks from sector concentration and backward-looking accounting.

## Transcript

14 of 15 global exchanges beat their local benchmark over 25 years with the price-to-tangible book value strategy. The only market that fails is Korea. China's price-to-tangible book value portfolio beat the SSE composite by 7.41% annually.
India beat the Sensex by 2.58% with a 64% win rate. India gained 19.61% in 2008, while the Sensex gained 7.27%. Here's what 25 years of data looks like across the full world map.
We tested price-to-tangible book value globally, not just the U.S. Each exchange uses its own market cap threshold, calibrated to domestic market size. $1 billion for NYSE, NASDAQ, and Amex.
$20 billion for India. $100 billion for Japan. Amex and SIO were excluded entirely for data quality reasons. Both have adjusted close-split artifacts that distort returns.
Every other exchange ran cleanly. The universe is the full exchange, not a constrained index like the S&P 500. Running on the full universe captures more qualifying stocks, reduces cash periods,
and tests the signal against a wider company set without the pre-selection bias built into index membership. The quality filters handle the noise. Return on equity, above 8%. Return on assets, above 3%.
Operating profit margin, above 10%. Those three filters ensure we're buying cheap companies with real earnings power, not distressed operations with shrinking asset bases. We use annual fiscal year filings with a 45-day lag.
The rebalance happens in July each year, using financials from the prior fiscal year that had at least 45 days to be filed and adjusted. Annual frequency suits price to tangible book because tangible book changes most meaningfully at annual filing time,
and goodwill impairments are tested annually. Quarterly rebalancing would mostly track noise. Transaction costs. Use a size-tiered model. 0.1% for large cap, 0.3% for mid cap, 0.5% for small cap.
The tangible equity calculation starts with total stockholders' equity, subtracts goodwill, and subtracts intangible assets. If either value is null, we treat it as zero, which is correct because some companies simply don't report goodwill or intangibles when they have none.
Price to tangible book equals market cap divided by that tangible equity figure. Positive tangible equity is required A company with negative tangible book has either taken on too much debt or paid so heavily for intangibles that its physical asset base is effectively zero
Both conditions disqualify it from the screen. The theory behind the signal is straightforward. Companies valued on hard assets have a floor that doesn't depend on market sentiment. Physical capital, whether it's steel mills, cement plants, or bank loan portfolios,
is valued by local fundamentals. During U.S. market crashes, non-U.S. tangible book companies can decouple entirely because their operations are unaffected by whatever drove the U.S. decline. Prices to tangible books should perform best in economies where tangible assets drive most of the value.
Manufacturing, financial services, basic materials. It should struggle where services, software, or intangible heavy industries dominate. Each exchange is now measured against its own local benchmark.
SPY for the U.S., Sensex for India, SSE Composite for China, DAX for Germany, and so on. Here's the full scorecard. The U.S. returned a compound annual growth rate of 11.31%,
with a down capture of 3.89%. That means when SPY had negative annual returns, the price-detangible book value portfolio lost only about 4 cents for every dollar SPY lost.
The dot-com crash was the signal's finest hour. In 2000, the portfolio returned positive 25.20%, while SPY fell 14.78%, then positive 23.37% versus SPY's negative 22.45% in 2001.
Companies with actual physical assets held value, while technology companies with no tangible book and no earnings collapsed. The worst U.S. year was 2019 at negative 32.67% versus size positive 7.43%,
the peak of the growth versus value divergence that hit every price-to-tangible book value market globally that year. India returned a 14.64% compound annual growth rate versus the Sensex's 12.06%,
an excess of 2.58% annually with a 64% win rate. In 2008, India priced a tangible book value returned positive 19.61%, while the Sensex gained 7.27%, a 12-point excess in the worst year for global equities in decades.
India's economy is asset-heavy by structure, steel producers, cement companies, chemical manufacturers, engineering conglomerates. These businesses have decades of physical capital accumulation that shows up directly in tangible book and price to tangible book targets exactly that universe The recent results plus 42 in
2022 and plus 69% in 2023, reflect India's manufacturing boom as global supply chains relocated away from China. Tangible asset companies were the direct beneficiaries.
China returned 9.84% compound annual growth rate versus the SSE composites, 2.43%, an excess of 7.41% annually with a 72% win rate.
Beta to the SSE composite, 0.958, so the portfolio moves with the Chinese market but consistently outperforms it. In 2008, China price to tangible book returned positive 42.90%, while the SSE gained 15.41%.
Chinese share markets are driven primarily by domestic retail investors, not global institutional flows. The 2006 and 2014 results, plus 138% and plus 117%, were Chinese domestic bull markets driven by policy and liquidity.
The price-to-tangible book signal captured these moves and amplified them by concentrating in the cheapest hard asset mains. Germany returned 6.90% compound annual growth rate versus the DAX's 5.40%, an excess of 1.86% annually.
The portfolio's worst drawdown was negative 32%, far shallower than the DAX's negative 53%, with a beta of just 0.61 to the index. Auto suppliers, chemical companies, and industrial manufacturers provided a tangible asset base that the broader DAX, with its tech and pharma weighting, didn't fully capture.
Here are the standout years across all exchanges. Against local benchmarks, price to tangible bookworks almost everywhere, 14 of 15 exchanges beat their own domestic index. The only failure is Korea.
Korea returned 4.06% compound annual growth rate, trailing the KOSP by 1.30%. The screen also sat in cash for 7 of 25 periods, 28% of the time, because too few stocks qualified.
The culprit is the cable structure. Samsung, SK, and Hyundai carry complex crossholdings that create opaque tangible book values. After stripping goodwill, the tangible equity figure still includes non-operating assets from subsidiary holdings.
The signal is muddied by corporate structure, not by the metric itself. Japan returned 5 compound annual growth rate beating the Nikkei by 2 against its local benchmark Japan actually works Japanese companies maintain persistently low price to tangible books through conservative accounting and high cash retention
With the quality filters, return on equity 8%. Select the companies that do generate returns. The discount doesn't close fully, but it narrows enough to beat the broader index. Singapore returned 4.49% compound annual growth rate, beating the SPI by 1.82%.
The universe is thin, with an average of 12.5 stocks per period. But even with that concentration, the signal adds value over the local benchmark. The 2019 value crash hit every price to tangible book market simultaneously.
Growth stocks and U.S. tech dominated globally. Germany, Canada, India, and the U.S. all underperformed that year. it was a global factor rotation, not a failure of any individual market. The breadth of outperformance tells a compelling story.
When compared to SPY, several non-U.S. exchanges look like failures. Measured against their own benchmarks, the signal works in manufacturing economies, financial services heavy markets, and basic materials exporters alike.
Only Korea's chaebol structure defeats it. Price to tangible book isn't a market timing tool. It doesn't tell you when the market will re-rate cheap tangible assets. The 2019 drawdown proved re-rating can take longer than any patient's threshold.
The strategy requires holding through multi-year underperformance while the signal waits for recognition. Tangible book is backward-looking. Assets are carried at historical cost, not replacement cost or economic value.
A factory built in 1980 might be worth far more or far less than its carrying value today. Price to tangible book gives you the accounting floor, not the economic floor, and those two numbers can diverge significantly in old capital industries.
Even in markets where the signal works, sector concentration toward financials remains. A banking crisis can overwhelm the strategy's quality filters entirely. The 2008 U.S. result, while saw better than SPY, still saw financials take hits because they make up a large share of the low price to tangible book universe.
That's what the data shows across 15 exchanges and 25 years. Full results, exchange-by-exchange charts, and the backtest code are on the blog. Link in the description. Run the current price to tangible books for yourself at sedaresearch.com.
The full backtest code is open at github.com slash sedaresearch slash backtests. If the global downcapture story was interesting, subscribe. More backtested strategies every week.