EV/EBITDA Sector Discount on UK Stocks: Consistent, Not Spectacular
The UK market doesn't generate headlines. It doesn't deliver the +74% years you get in India or the explosive recoveries you see in the US after crises. What 25 years of LSE data gives you is something more useful for most investors: consistent, steady outperformance with limited drawdowns.
Contents
- Method
- The Screen
- What We Found
- Annual Returns
- The Dot-Com Years: UK's Strongest Structural Edge
- The Brexit Uncertainty Period: 2013-2016
- Crisis Comparison
- 2017 and the Recovery
- Limitations
- Conclusion
We ran a sector-relative EV/EBITDA screen on London Stock Exchange stocks from 2000 through 2025. The result: 10.35% CAGR against 7.64% for SPY, with a max drawdown of -31.12% and zero cash periods across all 25 years.
Here's what we found.
Method
We screened LSE-listed stocks each January, computed sector median EV/EBITDA, and selected the 30 stocks trading at the deepest discount to sector peers. The portfolio held for 12 months before the next reset.
| Parameter | Value |
|---|---|
| Universe | LSE (London Stock Exchange) |
| Market cap minimum | £500M |
| EV/EBITDA range | 0.5x to 25x |
| ROE filter | > 8% |
| D/E filter | < 2.0 |
| Sector discount required | ≥ 30% below sector median |
| Selection | Top 30 by deepest discount |
| Rebalancing | Annual (January) |
| Cash condition | If fewer than 10 qualify |
| Data source | Ceta Research (FMP financial data warehouse) |
| Filing lag | 45 days (point-in-time, avoids look-ahead) |
| Period | 2000-2025 (25 years) |
| Benchmark | SPY (S&P 500 Total Return) |
| Returns currency | GBP |
Why EV/EBITDA works particularly well in the UK.
The LSE has a high concentration of capital-intensive industries: oil and gas, mining, utilities, financial services, and industrials. These sectors carry significant debt by nature. P/E ratios in these businesses are distorted by interest charges, making cross-sector comparison misleading. EV/EBITDA neutralizes that by measuring operating earnings relative to the full enterprise value before financing costs.
The sector-relative framing matters because UK sector valuations diverge substantially. UK consumer staples have historically traded at 12-16x EV/EBITDA while basic materials names sit at 4-7x. Measuring discount relative to sector peers correctly identifies value within the context of what's normal for that industry.
A note on the benchmark. Returns are reported in GBP. The benchmark is SPY in USD. GBP/USD fluctuations affect the comparison in any given year. 2016 in particular was distorted by the post-Brexit vote sterling collapse, which inflated GBP returns when translated back to any dollar-denominated comparison. We use SPY as a global reference point.
The Screen
Here's the current sector-relative EV/EBITDA screen for UK stocks, running against the live FMP warehouse.
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 ('LSE')
),
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 query on the live data: cetaresearch.com/data-explorer?q=WbioTyff-7
What We Found
The UK strategy held investments all 25 years, with a smaller average portfolio size (15.1 stocks) than the US (21.9). The LSE is a more concentrated exchange at the £500M threshold, with fewer names in some sectors. Despite the smaller holding count, performance was consistent.
$10,000 invested in January 2000 grew to $117,000 by end of 2025 (total return 1,072.69%). SPY turned $10,000 into $63,000 over the same period.
| Metric | Strategy | SPY |
|---|---|---|
| CAGR | 10.35% | 7.64% |
| Excess return | +2.70% | — |
| Total return | 1,072.69% | 530.71% |
| Sharpe ratio | 0.354 | — |
| Sortino ratio | 0.696 | — |
| Calmar ratio | 0.333 | — |
| Max drawdown | -31.12% | -34.90% |
| Down capture | 69.94% | 100% |
| Up capture | 113.3% | 100% |
| Win rate | 60% | — |
| Cash periods | 0 / 25 | — |
| Invested periods | 25 / 25 | — |
| Avg stocks held | 15.1 | — |
The Sharpe of 0.354 and max drawdown of -31.12% tell the story. This is a lower-volatility implementation than the US or India versions. You capture 113% of the upside and absorb only 70% of the downside. The up/down asymmetry is smaller than the US result (129.98% up / 62.91% down), but the lower volatility produces a cleaner, more investable risk profile.
Annual Returns
| Year | Strategy | SPY | Excess |
|---|---|---|---|
| 2000 | -4.9% | -10.5% | +5.6% |
| 2001 | +3.5% | -9.2% | +12.7% |
| 2002 | +5.2% | -19.9% | +25.1% |
| 2003 | +36.7% | +24.1% | +12.6% |
| 2004 | +19.4% | +10.2% | +9.2% |
| 2005 | +37.9% | +7.2% | +30.8% |
| 2006 | +20.9% | +13.7% | +7.3% |
| 2007 | +18.2% | +4.4% | +13.8% |
| 2008 | -31.1% | -34.3% | +3.2% |
| 2009 | +40.7% | +24.7% | +15.9% |
| 2010 | +21.0% | +14.3% | +6.7% |
| 2011 | -8.8% | +2.5% | -11.2% |
| 2012 | +28.6% | +17.1% | +11.5% |
| 2013 | +10.4% | +27.8% | -17.4% |
| 2014 | -1.3% | +14.5% | -15.8% |
| 2015 | -7.3% | -0.1% | -7.1% |
| 2016 | +10.9% | +14.4% | -3.5% |
| 2017 | +35.4% | +21.6% | +13.8% |
| 2018 | -13.8% | -5.2% | -8.6% |
| 2019 | +19.1% | +32.3% | -13.2% |
| 2020 | +7.2% | +15.6% | -8.4% |
| 2021 | +36.1% | +31.3% | +4.9% |
| 2022 | -20.3% | -19.0% | -1.3% |
| 2023 | +12.0% | +26.0% | -14.0% |
| 2024 | +26.0% | +25.3% | +0.7% |
The Dot-Com Years: UK's Strongest Structural Edge
The UK's best outperformance came during the dot-com bust period. From 2000 to 2002, the strategy posted -4.9%, +3.5%, and +5.2% while SPY fell -10.5%, -9.2%, and -19.9%. Over those three years, the cumulative excess was more than 44 percentage points.
The UK market's composition explains this. The LSE in 2000-2002 was heavily weighted toward value sectors: energy, mining, pharmaceuticals, and financial services. Tech exposure was limited. When the US growth bubble deflated, UK sector-relative value names barely felt the contagion. The screen was already tilted toward the sectors that were about to outperform globally.
Then came 2005 (+37.9%, +30.8% excess) and the 2003-2007 run more broadly. UK equities benefited from the commodity supercycle, strong financial sector profits, and emerging market demand for UK-listed resources companies.
The Brexit Uncertainty Period: 2013-2016
Three years of subdued performance coincided with the build-up to the Brexit vote. From 2013 to 2016, the strategy returned +10.4%, -1.3%, -7.3%, and +10.9%. SPY returned +27.8%, +14.5%, -0.1%, and +14.4%. The UK market was repriced downward as uncertainty over trade relationships, regulatory access, and capital flows kept institutional investors cautious about LSE exposure.
This wasn't a signal failure. It was a macro overhang on the entire market. The strategy's value names were no more immune to UK-specific macro headwinds than any other UK equity. The sector-relative discount signal identifies relative mispricing within UK markets, not protection from UK-wide de-rating.
Crisis Comparison
| Event | Strategy | SPY | Excess |
|---|---|---|---|
| Dot-com bust (2000-2002) | +4.3% cumulative | -34.2% cumulative | +38.5% |
| GFC 2008 | -31.1% | -34.3% | +3.2% |
| Eurozone stress 2011 | -8.8% | +2.5% | -11.2% |
| Brexit uncertainty (2013-2016) | +10.3% cumulative | +56.2% cumulative | -45.9% |
| COVID 2020 | +7.2% | +15.6% | -8.4% |
| Rate shock 2022 | -20.3% | -19.0% | -1.3% |
The GFC comparison is notable for its modesty. The UK strategy fell -31.1% versus SPY's -34.3% in 2008. That 3.2 percentage point difference is the same story as the US version: limited protection in a systemic, liquidity-driven crash. EV/EBITDA discounts stop mattering when forced selling dominates every asset class.
2017 and the Recovery
After the Brexit vote in June 2016 and the ensuing sterling depreciation, UK equities staged a significant recovery. The portfolio gained +35.4% in 2017 (+13.8% excess). Companies with high international revenues benefited from the weak pound, and the sector-relative discount signal identified the specific names within those sectors trading at the steepest discounts.
2021 added another +36.1% (+4.9% excess) as the UK market recovered from COVID and the Brexit trade deal was finalized. The signal worked well in both recovery phases.
Limitations
Small portfolio size. Averaging 15.1 stocks means the UK portfolio is meaningfully more concentrated than the US (21.9) or India (26.0). Individual company blowups have higher impact. This is a structural feature of the £500M market cap filter applied to a smaller exchange.
Currency. UK returns are in GBP, benchmark in USD. The 2016 sterling depreciation was a one-time event that distorted year-level comparisons. Long-term returns smooth this out, but year-to-year comparisons require care.
Brexit-specific risk. The 2013-2016 underperformance shows this strategy isn't immune to market-wide political repricing. Any future UK-specific macro shock (trade policy changes, regulatory divergence) could repeat the pattern.
Sector concentration. The LSE at £500M+ has deep representation in energy, mining, and financial services, and thinner coverage in technology. The sector-relative signal will naturally tilt toward the heavier sectors, which may not always be what an investor wants.
Lower excess than US. At +2.70% excess CAGR, UK outperformance is real but modest. After transaction costs, the practical advantage narrows. This is a risk-adjusted story (lower max drawdown than SPY) as much as an alpha story.
Conclusion
A sector-relative EV/EBITDA screen on UK stocks produced 10.35% annualized over 25 years against 7.64% for SPY, with lower max drawdown and consistent investment across all 25 years. The dot-com protection (2000-2002) is the most striking performance characteristic, driven by UK market structure rather than the signal itself.
The honest summary: the UK result is steady outperformance with modest excess returns and lower drawdowns than the global benchmark. It's not a high-octane strategy. For investors seeking consistent value exposure on the LSE, the sector-relative EV/EBITDA filter provides a structured, data-driven way to identify the mispriced names.
The 2013-2016 Brexit uncertainty period is the cautionary note. Macro headwinds on a country-level can overwhelm the signal for multiple years.
What's your experience with UK value strategies? Does the sector-relative framing work better or worse than absolute multiple filters on the LSE?
Part of a Series: Global | US | Switzerland | Japan | India | Hong Kong | Germany | China
Data: Ceta Research (FMP financial data warehouse). Backtest covers 2000-2025 using point-in-time financial data with 45-day filing lag. Returns in GBP. Benchmark (SPY) in USD. Results are hypothetical and don't reflect actual investment results. Past performance doesn't guarantee future results.
