EV/EBITDA Sector-Relative Value on Switzerland: 9.32% CAGR With 35%

We ran a sector-relative EV/EBITDA screen on 23 years of Swiss stock data from the SIX Exchange. The signal: buy when a stock's EV/EBITDA falls below 70% of its sector median, filtered for quality (ROE > 8%, D/E < 2.0, MCap > CHF 500M). The strategy returned 9.32% annually vs 7.64% for the S&P 500. But the headline number isn't the return. It's the down-capture: 35.32%. When SPY lost 10%, Switzerland lost only 3.5%. Over the full period, Switzerland matched the US on risk-adjusted terms with a 15-stock portfolio and a smaller universe.

Contents

1. Method
2. The Screen
3. Sector-Relative EV/EBITDA Screen for SIX (SQL)
4. What We Found
5. 23 invested years. 1.67% annual alpha. Sharpe ratio that matches the US.
6. 35% down-capture: the real story
7. Year-by-year returns
8. 2002: +32.4% excess during the dot-com bust
9. 2008: -20.1% while SPY lost 34.3%
10. 2005-2007 and 2009-2010: the accumulation phase
11. The recent regime shift (2019-2024)
12. Backtest Methodology
13. Limitations
14. Conclusion

Method

Financial data sourced from key_metrics_ttm for EV/EBITDA and market cap, financial_ratios_ttm for debt metrics, profile for sector classification. 45-day lag on all financial statements to prevent look-ahead bias.

The Screen

Sector-Relative EV/EBITDA Screen for SIX (SQL)

WITH universe AS (
 SELECT k.symbol, p.companyName, p.exchange, p.sector,
 k.evToEBITDATTM AS ev_ebitda, 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 k.evToEBITDATTM BETWEEN 0.5 AND 25
 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 ('SIX')
),
sector_medians AS (
 SELECT exchange, sector,
 PERCENTILE_CONT(0.5) WITHIN GROUP (ORDER BY ev_ebitda) AS median_ev_ebitda,
 COUNT(*) AS n_sector_stocks
 FROM universe GROUP BY exchange, sector HAVING COUNT(*) >= 5
)
SELECT u.symbol, u.companyName, u.exchange, u.sector,
 ROUND(u.ev_ebitda, 2) AS ev_ebitda_ttm,
 ROUND(sm.median_ev_ebitda, 2) AS sector_median_ev_ebitda,
 ROUND(u.ev_ebitda / sm.median_ev_ebitda, 3) AS ev_ratio_to_sector,
 ROUND((1 - u.ev_ebitda / sm.median_ev_ebitda) * 100, 1) AS discount_pct,
 ROUND(u.roe * 100, 1) AS roe_pct,
 ROUND(u.de, 2) AS debt_to_equity,
 ROUND(u.marketCap / 1e9, 2) AS mktcap_b
FROM universe u JOIN sector_medians sm ON u.exchange = sm.exchange AND u.sector = sm.sector
WHERE u.ev_ebitda / sm.median_ev_ebitda < 0.70
ORDER BY u.ev_ebitda / sm.median_ev_ebitda ASC LIMIT 30

Run this screen on Ceta Research

What We Found

23 invested years. 1.67% annual alpha. Sharpe ratio that matches the US.

The Sharpe ratio of 0.467 is nearly identical to the US result (0.468) in the same backtest. Switzerland achieved that with an average of 15.1 stocks per year, roughly a third the size of the US portfolio, and in a currency that performed independently of the USD benchmark.

Max drawdown of -29.61% is the lowest of all 13 exchanges we tested. Switzerland never fell as far as SPY (-34.90%) in any prolonged downturn.

35% down-capture: the real story

The down-capture ratio of 35.32% is the headline finding. When SPY drops 10%, this Swiss portfolio dropped only 3.5% on average. That protection compounds over time. Avoiding the full force of down years is worth as much as capturing up years at a discount.

The win rate of 64% reinforces this: the strategy beat SPY in 14 of 21 invested years. That's the opposite of the German result in this same backtest (48% win rate), and it makes the Swiss experience smoother for investors who care about year-by-year tracking.

Year-by-year returns

2002: +32.4% excess during the dot-com bust

The strategy was in cash in 2000 and 2001, which was probably fortunate. When it deployed in 2002, the US was still falling (-19.9%) while the Swiss portfolio returned +12.4%. Swiss quality industrials and healthcare names at sector discounts had already priced in the broader market pessimism. The gap between a beaten-down sector discount and its median closed even as the US selloff continued.

2008: -20.1% while SPY lost 34.3%

The global financial crisis is the acid test for any value strategy. Switzerland passed it better than most. The portfolio fell -20.1% vs SPY's -34.3%, a +14.2% relative cushion. Swiss companies tend to have conservative balance sheets and multi-national revenue diversification. The quality filters (ROE > 8%, D/E < 2.0) kept the most leveraged names out of the portfolio before the crash.

2005-2007 and 2009-2010: the accumulation phase

Three years of strong outperformance from 2005 to 2007, followed by the 2008 drawdown, and then two years of recovery outperformance in 2009 and 2010. The cumulative gap built substantially in this period. The strategy caught the mid-2000s European expansion and the post-crisis rebound, while the down-capture ratio limited the damage in 2008.

The recent regime shift (2019-2024)

Five of the last six years produced negative excess returns, including -36.9% in 2023 and -26.0% in 2024. This is the same growth-regime headwind that hit other Western value strategies. When US tech stocks led the market, Swiss industrial and consumer names at sector discounts didn't benefit from the same re-rating. The CHF also strengthened against the USD in some of these years, which may have affected the benchmark comparison.

The longest losing streak in the backtest is these recent years. Investors running this strategy needed conviction during a prolonged underperformance regime.

Backtest Methodology

Full methodology: backtests/METHODOLOGY.md

Limitations

Recent underperformance. Five of the last six years (2019-2024) produced negative excess returns. The growth-dominated regime that rewarded US tech left Swiss value stocks behind. This may be cyclical or it may represent a structural shift in how global capital allocates.

Small universe. Switzerland averages 15.1 stocks per year. That's workable, but concentration risk is higher than in deeper markets. A 15-stock portfolio has meaningful single-stock exposure.

Currency effects. Portfolio returns are in CHF. The benchmark (SPY) is in USD. EUR/CHF and USD/CHF fluctuations add noise to the comparison. The Swiss franc is a safe-haven currency that historically appreciates in crises, which may have contributed to the down-capture advantage in some years.

2 cash years (2000-2001). The strategy had no qualifying stocks in its first two potential years. This means the track record starts from 2002. The full 25-year SPY comparison assumes cash returns for 2000-2001.

MaxDD worst year (2018: -29.6%). The maximum drawdown of -29.61% came from a single bad year, not a sustained selloff. That's different from a multi-year drawdown, but a -29.6% single-year loss still tests conviction.

Conclusion

Sector-relative EV/EBITDA on Switzerland's SIX Exchange delivered 9.32% CAGR over 23 invested years, with a Sharpe ratio of 0.467 that matches the US result and a down-capture of 35.32% that beats it. The max drawdown of -29.61% is the lowest of 13 global exchanges tested in this strategy.

The recent six-year underperformance is a genuine caveat. The early track record (2002-2018) is strong. The post-2018 regime has been difficult for this type of signal.

For investors who prioritize downside protection and risk-adjusted returns over raw alpha, Switzerland's result is one of the cleanest in this global test. The question, as always with value strategies, is whether you can hold through multi-year underperformance before the discount closes.

Part of a Series: Global | US | UK | Japan | India | Hong Kong | Germany | China

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 CHF (local currency). Benchmark S&P 500 in USD. Past performance doesn't guarantee future results. See full methodology at github.com/ceta-research/backtests.