We Tested GARP in 17 Markets. UK Beats Its Benchmark by 3.52%.

We ran the GARP strategy on 17 stock exchanges from 2000 to 2025. Against local benchmarks, UK (+3.52% vs FTSE), Germany (+2.69% vs DAX), and Sweden (+1.92% vs OMX) outperform. India barely ties the Sensex (+0.10%). Here's the full comparison.

GARP CAGR by exchange compared to local benchmarks, 17 markets, 2000 to 2025.

We ran the Growth at a Reasonable Price (GARP) strategy — PEG < 1.5, revenue growth > 15%, ROE > 10% — on 17 stock exchanges worldwide from 2000 to 2025. The S&P 500 benchmark returned 8.02% annually. When compared to local currency benchmarks, the picture changes completely: the UK beats the FTSE by 3.52% per year, Germany beats the DAX by 2.69%, and several other markets show modest outperformance. India's apparent 3.20% excess vs SPY is mostly India's growth premium, not GARP alpha. Against the Sensex, India barely outperforms by 0.10%.

Contents

  1. Method
  2. What We Found
  3. Cross-market comparison (all vs SPY in USD)
  4. Local Benchmark Comparison: The Real Alpha
  5. Why Local Benchmarks Matter
  6. Max Drawdowns
  7. Cash Periods: Where the Signal Doesn't Fire
  8. The Real Winners
  9. Why Developed Markets Outperform With Local Benchmarks
  10. The India Reversal
  11. What the Pattern Suggests
  12. Limitations
  13. Takeaway
  14. Individual Exchange Posts
  15. References

Data: FMP financial data warehouse, 2000–2025. Updated March 2026.


Method

Data source: Ceta Research (FMP financial data warehouse) Period: 2000–2025 (25 years, 103 quarterly periods) Rebalancing: Quarterly (January, April, July, October), equal weight Benchmarks: Cross-market comparison uses SPY; local alpha measured vs local indices Transaction costs: Size-tiered model (0.1–0.5% one-way based on market cap) Cash rule: Hold cash if fewer than 10 stocks qualify at a rebalance date

Each exchange uses exchange-specific market cap thresholds in local currency. Financial data has a 45-day lag on annual filings to prevent look-ahead bias.

GARP signal filters (all must pass at each rebalance):

Filter Threshold
PEG ratio 0 < PEG < 1.5
P/E ratio 5 < P/E < 50
Revenue growth (YoY) > 15%
ROE > 10%
Debt/Equity < 2.0
Market cap Exchange-specific threshold

What We Found

Cross-market comparison (all vs SPY in USD)

GARP CAGR by exchange vs S&P 500 benchmark (2000-2025).
GARP CAGR by exchange vs S&P 500 benchmark (2000-2025).

Exchange CAGR vs SPY Sharpe
India (NSE) 11.22% +3.20% 0.145
Norway (OSL) 9.55% +1.53% 0.359
Germany (XETRA) 7.81% -0.21% 0.278
US (NYSE+NASDAQ+AMEX) 7.15% -0.87% 0.228
South Africa (JNB) 6.74% -1.28% -0.125
Indonesia (JKT) 6.14% -1.88% 0.192
Canada (TSX) 5.18% -2.84% 0.118
Sweden (STO) 5.09% -2.93% 0.138
China (SHZ+SHH) 4.93% -3.09% 0.066
UK (LSE) 4.88% -3.14% 0.067
Korea (KSC) 4.35% -3.67% 0.082
Thailand (SET) 4.07% -3.95% 0.066
Switzerland (SIX) 3.84% -4.18% 0.176
Hong Kong (HKSE) 3.40% -4.62% 0.014
Japan (JPX) 2.98% -5.04% 0.134
Taiwan (TAI+TWO) 1.52% -6.50% 0.027
Singapore (SES) 0.96% -7.06% -0.081

SPY benchmark: 8.02% CAGR, Sharpe 0.361

India tops the vs-SPY ranking at +3.20%, but most of that gap reflects India's faster economic growth relative to the US, not the GARP signal finding alpha. When we compare each market to its own local benchmark, the story changes.


Local Benchmark Comparison: The Real Alpha

Comparing strategies to SPY is useful for cross-market portfolio allocation, but it mixes currency effects, economic growth differentials, and stock selection skill. To isolate the GARP signal's actual performance, we need local currency benchmarks.

GARP excess return vs local market index:

Exchange GARP CAGR Local Bench Bench CAGR Excess Sharpe GARP vs Bench
UK (LSE) 4.88% FTSE 100 1.36% +3.52% 0.067 vs 0.000
Germany (XETRA) 7.81% DAX 5.12% +2.69% 0.278 vs 0.139
Sweden (STO) 5.09% OMX Stockholm 3.17% +1.92% 0.138 vs 0.066
Switzerland (SIX) 3.84% SMI 2.10% +1.73% 0.176 vs 0.074
Hong Kong (HKSE) 3.40% Hang Seng 1.77% +1.63% 0.014 vs -0.031
China (SHZ+SHH) 4.93% SSE Composite 4.19% +0.74% 0.066 vs 0.025
Thailand (SET) 4.07% SET Index 3.76% +0.31% 0.066 vs 0.043
India (NSE) 11.22% Sensex 11.12% +0.10% 0.145 vs 0.194
Canada (TSX) 5.18% TSX Composite 5.08% +0.10% 0.118 vs 0.114
Japan (JPX) 2.98% Nikkei 225 3.40% -0.42% 0.134 vs 0.121
Korea (KSC) 4.35% KOSPI 4.81% -0.45% 0.082 vs 0.099
US (NYSE+NASDAQ+AMEX) 7.15% S&P 500 8.02% -0.86% 0.228 vs 0.361
Singapore (SES) 0.96% STI 2.17% -1.21% -0.081 vs -0.031
South Africa (JNB) 6.74% SPY 8.02% -1.28% -0.125 vs 0.361
Norway (OSL) 9.55% Oslo All Share 10.91% -1.36% 0.359 vs 0.422
Indonesia (JKT) 6.14% SPY 8.02% -1.88% 0.192 vs 0.361
Taiwan (TAI+TWO) 1.52% TAIEX 4.38% -2.86% 0.027 vs 0.069

Note: Norway data only covers 2013–2025 (Oslo All Share index availability). South Africa and Indonesia use SPY due to limited local index data.

The UK shows +3.52% excess vs the FTSE, the strongest result in the dataset. Germany's +2.69% vs the DAX is second. Sweden, Switzerland, and Hong Kong all show +1.6% to +1.9% excess.

India's +0.10% vs Sensex is essentially flat. The apparent 3.20% excess vs SPY reflects India's growth premium over US equities, not GARP's stock selection adding value above the Indian market.


Why Local Benchmarks Matter

The SPY comparison showed "India +3.11%, everyone else underperforms." That's accurate for USD-based portfolio allocation, but it doesn't tell you whether the GARP signal is working.

India's economy grew faster than the US from 2000–2025. The Sensex returned 11.12% while SPY returned 8.02%. Any long-only India strategy would have shown ~3% excess vs SPY. GARP India's +0.10% excess vs Sensex shows the screen barely adds value beyond a simple Indian index fund.

Germany's story flips. Against SPY (-0.21%), it looks like a near-miss. Against the DAX (+2.69%), it's a meaningful outperformer. The DAX had a brutal 2000–2009 period. GARP's quality filters (ROE > 10%, D/E < 2.0) kept financially stressed companies out during that decade.

The UK result (+3.52% vs FTSE) is the most surprising. The FTSE 100 returned only 1.36% CAGR from 2000–2025, dragged down by the financial crisis and Brexit. A quality-growth screen on mid-cap UK stocks found better companies than the FTSE 100's blue chips.


Max Drawdowns

GARP max drawdown by exchange vs S&P 500 (2000-2025).
GARP max drawdown by exchange vs S&P 500 (2000-2025).

Exchange Max Drawdown Local Bench MDD Protection
India (NSE) -72.98% -51.34% worse
Canada (TSX) -70.09% N/A N/A
Hong Kong (HKSE) -69.66% N/A N/A
Japan (JPX) -68.19% N/A N/A
Switzerland (SIX) -66.55% N/A N/A
Singapore (SES) -62.78% N/A N/A
Sweden (STO) -58.09% N/A N/A
US (NYSE+NASDAQ+AMEX) -54.60% -43.86% worse
Taiwan (TAI+TWO) -54.06% N/A N/A
Thailand (SET) -52.67% N/A N/A
UK (LSE) -52.76% N/A N/A
Germany (XETRA) -46.88% -65.15% better
South Africa (JNB) -45.31% N/A N/A
Indonesia (JKT) -42.54% N/A N/A
Korea (KSC) -40.77% N/A N/A
Norway (OSL) -30.93% N/A N/A

Germany is the standout: -46.88% max drawdown vs the DAX's -65.15%. The DAX lost nearly two-thirds of its value peak-to-trough (2000–2009). Germany GARP's quality filters provided genuine crash protection.

India's -72.98% drawdown vs Sensex -51.34% shows the opposite: concentrated growth stocks in an emerging market amplify downside during global crises.


Cash Periods: Where the Signal Doesn't Fire

Some markets showed high cash usage — quarterly periods when fewer than 10 stocks qualified. High cash means the GARP signal is structurally weak for that market.

Exchange Cash Periods Cash % Interpretation
Norway (OSL) 73 of 103 71% Signal rarely fires (oil-heavy, limited growth companies)
Korea (KSC) 34 of 103 33% Chaebol structure limits PEG candidates
Sweden (STO) 33 of 103 32% Small mid-cap universe for GARP
Indonesia (JKT) 33 of 103 32% Cyclical, limited depth
South Africa (JNB) 32 of 103 31% Thin qualifying universe
Taiwan (TAI+TWO) 29 of 103 28% Concentrated economy, tech-heavy
Japan (JPX) 23 of 103 23% Low ROE culture limits qualifying stocks
India (NSE) 22 of 103 21% Cash in 2000–2004 only; consistent since 2005
Singapore (SES) 21 of 103 20% Small market, limited qualifying depth
Thailand (SET) 20 of 103 19% Limited mid-cap GARP universe
Switzerland (SIX) 5 of 103 5% Concentrated but consistent
Hong Kong (HKSE) 3 of 103 3% Large qualifying universe
US, Germany, UK, Canada, China 0 of 103 0% Consistently deep qualifying universe

Norway's 71% cash rate means the GARP signal fired in only 30 of 103 quarters. Combined with Norway's limited 2013–2025 data window (Oslo All Share index availability), the result is more of a data artifact than a strategy performance measurement.


The Real Winners

Using local benchmarks to measure true alpha:

  1. UK: +3.52% vs FTSE. The FTSE 100 returned only 1.36% CAGR (2000–2025), dragged by financials and Brexit. GARP's mid-cap quality-growth filter found better UK companies.
  2. Germany: +2.69% vs DAX. The DAX lost heavily in the early 2000s. GARP's filters avoided that crash, built long-run excess, and delivered nearly double the Sharpe ratio (0.278 vs 0.139).
  3. Sweden: +1.92% vs OMX Stockholm. Modest but positive edge with consistent 32% cash rate.
  4. Switzerland, Hong Kong: +1.7% to +1.6%. Positive but thin edges.

India's +0.10% vs Sensex is noise territory. The screen doesn't add value beyond an Indian index fund on risk-adjusted terms (Sharpe 0.145 vs Sensex 0.194).


Why Developed Markets Outperform With Local Benchmarks

The pattern reverses when we use local benchmarks. UK, Germany, Sweden, and Switzerland all show positive alpha vs their home indices. These are efficient markets — why does GARP work?

The explanation: these local indices had poor performance from 2000–2025 relative to SPY. The FTSE returned 1.36%, the DAX 5.12%, OMX Stockholm 3.17%. All were dragged by the dot-com crash, financial crisis, and European sovereign debt issues.

GARP's quality filters (ROE > 10%, D/E < 2.0, PEG < 1.5) systematically screened out the damaged companies during those crises. The screen found mid-cap companies that weren't part of the headline indices and weren't as exposed to the crisis sectors (financials, telecoms, extreme-leverage industrials).

This isn't inefficiency producing alpha. It's quality filtering during a bad period for headline indices. The GARP screen naturally tilts toward industrial, chemical, and specialty companies with genuine earnings growth. Those companies were the survivors, not the casualties, of the 2000–2009 period.


The India Reversal

India's headline vs SPY (+3.20%) is strong. But the Sensex itself returned 11.12% vs SPY's 8.02%. A passive Sensex fund would have shown +3.10% excess. GARP India adds 0.10% above that — statistically indistinguishable from zero.

The capture ratios vs Sensex (113% up, 109% down) show the screen amplifies both bull and bear markets. The cash periods in 2000–2004 cost performance — the Sensex surged +79% in 2003 while GARP held cash. The exceptional years (2007: +36% excess, 2009: +61%, 2023: +53%) are offset by bad years (2008: -19%, 2018: -40%, 2019: -27%).

India is the strongest absolute GARP market globally (11.22% CAGR), but the edge vs its local market is marginal.


What the Pattern Suggests

Run GARP in a market where:

  1. The local index had a rough 25 years. UK (FTSE 1.36%), Germany (DAX 5.12%), Sweden (OMX 3.17%) all underperformed global equities. GARP's quality bias helped avoid the worst.
  2. The mid-cap universe differs from the headline index. UK, German, and Swedish mid-caps showed different sector exposure and better fundamentals than their large-cap indices.
  3. Quality filters matter during crises. ROE > 10% and D/E < 2.0 kept overleveraged and loss-making companies out. This paid off in Europe's difficult 2000s.

Don't run GARP expecting alpha in:

  1. High-performing indices. SPY's 8.02% from 2000–2025 was strong. GARP couldn't beat it.
  2. Markets where local benchmarks are already quality-tilted. The Sensex (India) and KOSPI (Korea) already represent quality companies. GARP doesn't add much.

Limitations

Currency. Each market's returns are in local currency. Cross-currency comparison to SPY (USD) doesn't adjust for exchange rate movements. A market can outperform SPY in local currency while an international investor loses to USD strength.

Exchange-specific market cap thresholds. We use exchange-appropriate minimums (not a flat $1B USD), which affects the qualifying universe size per market.

Survivorship bias. Company profiles use current exchange listings. Delistings, bankruptcies, and mergers aren't tracked through terminal events.

25-year period. The 2000–2025 window includes multiple regime changes. Results could differ significantly over shorter or different time windows. Germany, UK, and Sweden all benefited from their indices having rough 2000–2010 periods — GARP's quality bias helped there. If we ran 2010–2025, results might differ.

Norway data limitation. Oslo All Share index only available from 2013. Norway's 9.55% CAGR reflects 2013–2025 performance, not the full 25 years.


Takeaway

We tested GARP across 17 stock exchanges. When measured vs local benchmarks, five markets show meaningful outperformance: UK (+3.52%), Germany (+2.69%), Sweden (+1.92%), Switzerland (+1.73%), and Hong Kong (+1.63%). India barely matches the Sensex (+0.10%). Canada ties the TSX (+0.10%).

The finding is that GARP works where local indices had difficult periods and the quality screen filtered out the worst performers. UK, Germany, and Sweden fit this pattern. The screen doesn't find hidden gems in efficient markets — it finds quality-growth companies when the headline indices are dragged by damaged sectors.

For global investors: Germany and UK stand out as markets where GARP adds value vs the local benchmark. For Indian investors: GARP matches the Sensex with higher volatility. For US investors: SPY beats GARP.

Run the global GARP screen on Ceta Research


Individual Exchange Posts


References

  • Lynch, P. (1989). One Up on Wall Street. Simon & Schuster.
  • Fama, E. & French, K. (1998). "Value Versus Growth: The International Evidence." Journal of Finance, 53(6), 1975–1999.
  • Rouwenhorst, K. (1999). "Local Return Factors and Turnover in Emerging Stock Markets." Journal of Finance, 54(4), 1439–1464.
  • Griffin, J., Ji, X. & Martin, S. (2003). "Momentum Investing and Business Cycle Risk: Evidence from Pole to Pole." Journal of Finance, 58(6), 2515–2547.

Data: Ceta Research, FMP financial data warehouse. All exchanges, quarterly rebalance, equal weight, transaction costs included, 2000–2025. Returns in local currency.