Low Debt Quality on UK Stocks (LSE): 6.14% CAGR Over 25 Years

We ran the low-leverage quality screen on LSE-listed UK stocks across 25 years. D/E < 0.5 and Piotroski F-Score >= 7 as the entry conditions. Annual July rebalance, equal weight, all qualifying stocks held. The result: 6.14% CAGR vs 7.83% for SPY. A deficit of -1.69% annually. The strategy never sat in cash. It averaged 61 stocks per rebalance, the largest universe of the European markets we tested.

Contents

1. Method
2. The Signal
3. The Screen (SQL)
4. What We Found
5. 25 years. Behind SPY. High down capture.
6. Annual returns (GBP vs SPY USD, July-to-July)
7. 2001-2002: Telecom and the dot-com crash
8. 2005 and 2009: The strongest periods for the UK screen
9. 2016: Brexit and GBP depreciation
10. 2021: The sharpest loss
11. Backtest Methodology
12. Limitations
13. Takeaway
14. Part of a Series
15. Run This Screen Yourself

The headline is honest: the UK portfolio trailed SPY over 25 years, delivered a max drawdown slightly worse than SPY (-40.59% vs -36.27%), and its down capture (96.58%) means it absorbs nearly all of the market's losses. The story isn't protection. It's the isolated bright spots, 2016 in particular, and what they tell you about how currency and macro events interact with a quality filter on an internationally exposed market.

Method

• Data source: Ceta Research (FMP financial data warehouse)
• Universe: LSE (United Kingdom), market cap > £400M
• Period: 2000-2025 (25 years, 25 annual periods)
• Rebalancing: Annual (July), equal weight all qualifying
• Benchmark: S&P 500 Total Return (SPY)
• Cash rule: Hold cash if fewer than 10 stocks qualify
• Data lag: 45-day point-in-time lag on financial statements (prevents look-ahead bias)

Annual returns are measured July-to-July. The year label marks the start of each 12-month holding period. Returns are in GBP. SPY is in USD.

The Signal

Two filters. Both must pass.

Filter 1: Low Leverage

D/E < 0.5, measured from annual financial statements (FY data). This is a hard cutoff. Companies with debt-to-equity at or above 0.5 are excluded regardless of other metrics.

Filter 2: Piotroski F-Score >= 7

The F-Score aggregates nine binary signals across profitability, cash quality, and financial efficiency. Each signal scores 1 or 0. Stocks must score 7 or higher to qualify.

Score >= 7 of 9 means the company is improving across most dimensions simultaneously. Combined with D/E < 0.5, this targets companies that are both conservatively financed and operationally improving. The LSE produces 61 qualifying stocks on average, a larger pool than Germany (48) or Switzerland (typically under 30). The UK's diverse large-cap base across consumer goods, pharma, mining, and professional services feeds a wide, consistently populated universe.

The Screen (SQL)

The live screen uses TTM proxies as a Piotroski approximation. Full Piotroski requires year-over-year FY comparisons. The TTM screen substitutes ROE, operating margin, and interest coverage as quality proxies. Use this to find candidates, not to replicate the exact backtest signal.

SELECT p.exchange, r.symbol, p.companyName, p.sector,
    ROUND(r.debtToEquityRatioTTM, 3) AS de_ratio,
    ROUND(k.returnOnEquityTTM * 100, 1) AS roe_pct,
    ROUND(r.operatingProfitMarginTTM * 100, 1) AS opm_pct,
    ROUND(r.interestCoverageRatioTTM, 1) AS interest_coverage,
    ROUND(k.freeCashFlowYieldTTM * 100, 2) AS fcf_yield_pct,
    ROUND(k.marketCap / 1e9, 2) AS mktcap_b
FROM financial_ratios_ttm r
JOIN key_metrics_ttm k ON r.symbol = k.symbol
JOIN profile p ON r.symbol = p.symbol
WHERE r.debtToEquityRatioTTM >= 0
  AND r.debtToEquityRatioTTM < 0.50
  AND k.returnOnEquityTTM > 0.08
  AND r.operatingProfitMarginTTM > 0.08
  AND r.interestCoverageRatioTTM > 5.0
  AND p.isActivelyTrading = true
  AND k.marketCap > 400000000
  AND p.exchange IN ('LSE')
ORDER BY de_ratio ASC
LIMIT 30

Run this query on Ceta Research

What We Found

25 years. Behind SPY. High down capture.

Down capture of 96.58% is the sharpest finding here. The strategy absorbed almost all of SPY's losses in down years while only capturing 89.76% of gains in up years. That's the worst capture ratio in our European sample. The Sharpe of 0.136 reflects this: low excess return per unit of volatility, with 19.42% annualised volatility despite a predominantly large-cap universe.

Annual returns (GBP vs SPY USD, July-to-July)

2001-2002: Telecom and the dot-com crash

-28.7% in 2001, -16.6% in 2002. Two consecutive severe years. The LSE had deep exposure to the telecom bubble. Companies like Marconi, BT, and others in the UK telecom and technology space were among the most overextended in Europe. The D/E < 0.5 filter helped screen out some of the worst offenders, but the broader market collapse in the UK's large-cap space dragged even conservatively financed companies down.

The 2002 result is particularly notable: SPY managed +3.3% as US stocks began stabilising, while the UK portfolio lost -16.6%. This was a -19.9% excess return deficit in a single year. The UK tech crash had a longer tail than the US equivalent.

The recovery was sharp: +38.4% in 2003 and +26.7% in 2005 recaptured much of the lost ground. By 2006 the strategy was running alongside SPY.

2005 and 2009: The strongest periods for the UK screen

+26.7% in 2005 vs SPY's +8.9%, a +17.9% excess. This year captured the mid-2000s UK economic expansion, where companies with improving operating metrics and conservative balance sheets benefited from a strong domestic and European economy. The Piotroski filter was selecting companies with rising asset turnover and improving gross margins, exactly the characteristics that drove returns in this environment.

2009 added +29.4% vs SPY's +13.4%, a +16.0% gap. UK quality stocks recovered faster from the financial crisis trough than the S&P 500 composite. Companies that had avoided excessive leverage in the run-up to 2008 were positioned to act when credit markets normalised.

2016: Brexit and GBP depreciation

+31.4% vs SPY's +17.7%, a +13.6% excess. This is the most structurally interesting year in the UK dataset.

The Brexit referendum in June 2016 caused a sharp GBP depreciation. For UK companies that earn revenue in USD or EUR, multinationals, mining companies, pharmaceutical groups. GBP-reported earnings rose automatically as foreign revenue translated back at a weaker pound. Low-debt, high-Piotroski companies in this category saw their GBP returns boosted by the currency move, even without any underlying change in business performance.

The quality filter, in an unintentional but useful way, selected precisely the kind of large UK multinationals that benefited most from GBP weakness. Heavily indebted domestically focused companies generally didn't pass D/E < 0.5. The ones that did were more likely to have international revenue streams.

2021: The sharpest loss

-24.3% vs SPY's -10.2%. A -14.2% excess deficit. This is the LSE strategy's worst relative year.

The July 2021 to July 2022 period covered the peak of UK inflation and the beginning of the Bank of England's rate hike cycle. Small and mid-cap quality stocks, which are disproportionately represented in an equal-weight portfolio, were hit harder than the index. The UK market also had sector-specific headwinds in retail and property during this period.

The same dynamic appeared in the US result (-27.3% in 2021). It's a structural feature of equal-weight quality screens during rate-shock markets: they underweight the large-cap names that hold up during rate rises and overweight the mid-cap quality names that don't.

Backtest Methodology

Limitations

Currency mismatch. Returns are in GBP. SPY is in USD. GBP/USD movements affect the excess return comparison in any given year. 2016 is the clearest example: GBP depreciation boosted the strategy's returns on internationally exposed UK stocks relative to USD-denominated SPY. Years where GBP strengthened would have had the opposite effect for a USD-based investor comparing returns.

High down capture. At 96.58%, the strategy provides almost no downside protection relative to SPY. Investors seeking to use a quality filter as a crisis hedge will find the UK result uninspiring. The 2001-2002 and 2021 drawdowns demonstrate that the Piotroski + D/E combination didn't shield against large market-wide moves on LSE the way it did in some other markets.

Sector exposure. The LSE universe at £400M+ mktcap includes a wide range of sectors. Financial firms and property groups with structural leverage don't pass D/E < 0.5. The portfolio skews toward consumer goods (Unilever-type companies), healthcare (AstraZeneca, GSK tier), and industrial conglomerates. This creates implicit sector bets that aren't visible in the headline numbers.

Survivorship bias. Exchange membership uses current company profiles. Historical delistings, M&A, and deregistrations on the LSE during 2000-2025 aren't fully captured. This likely causes modest upward bias in reported returns.

TTM screen vs backtest signal. The live SQL uses TTM ratios as a Piotroski approximation. The backtest computed Piotroski from FY year-over-year changes. Use the screen for candidate identification, not exact replication.

Takeaway

LSE Low Debt Quality returned 6.14% CAGR vs SPY's 7.83%, a -1.69% annual deficit over 25 years. The max drawdown of -40.59% exceeded SPY's -36.27%, and the 96.58% down capture means the strategy tracked the market's losses almost point for point.

The win rate of 44% is the weakest argument for the strategy: it beat SPY in fewer than half of all years. 2016 (+31.4%) and the 2003-2005 stretch were the high points. The 2001-2002 telecom crash and the 2021-2023 post-COVID period were where it gave ground.

The UK result suggests that the low-debt quality filter doesn't add as much value in the LSE context as it does in markets where the universe is smaller and more concentrated. With 61 stocks on average, the portfolio is well-diversified, which limits both the upside and the downside relative to a broad index. The filter works best when it's selective enough to generate a meaningfully different portfolio. At 61 stocks in a broad market, the selection is less sharp.

Part of a Series

This post is part of our Low Debt Quality global exchange comparison. We ran the same strategy across 15 exchanges worldwide: - Low Debt Quality on US Stocks (NYSE + NASDAQ + AMEX) - 7.09% CAGR, -0.75% excess, 82.83% down capture - Low Debt Quality on Indian Stocks (BSE + NSE) - 14.05% CAGR, +6.22% excess - Low Debt Quality on Canadian Stocks (TSX) - +1.33% excess - Low Debt Quality on Swedish Stocks - +1.14% excess - Low Debt Quality on Swiss Stocks - best Sharpe in the study (0.429) - Low Debt Quality on German Stocks (XETRA) - 6.72% CAGR, -1.11% excess - Low Debt Quality on Japan Stocks (JPX) - 112-stock universe, 75.1% down capture - Low Debt Quality: Global Exchange Comparison - all 15 exchanges

Run This Screen Yourself

The TTM screen SQL above is runnable directly on Ceta Research. Query the FMP financial data warehouse and filter by exchange = 'LSE'. No setup required.

The full backtest code (Python + DuckDB) is on GitHub.

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 GBP. Annual rebalance July, equal weight, 2000-2025.