Post-Earnings Drift Across 14 Markets: A Global Event Study

Post-Earnings Announcement Drift is a global phenomenon. We ran the same event study on 14 exchanges with next-day close entry (MOC execution) and local currency benchmarks. 13 of 14 show a positive Q5-Q1 quintile spread. The effect is nearly universal.

Contents

1. Method
2. Global Results
3. What the Data Shows
4. The Asia-Pacific vs Major Developed Split
5. Taiwan: Widest Quintile Spread, Miss-Dominated Signal
6. How We Handled Exchange Selection
7. Screen for Global Earnings Surprises
8. Limitations
9. Takeaway
10. References

The story splits roughly along market depth lines. Emerging and Asia-Pacific markets (India, Hong Kong, China, Taiwan) show meaningful post-entry drift. Major developed markets (US, Japan, Korea) show negligible or negative beat drift after entry. Smaller European markets sit in between. The announcement-day reaction, which you can't trade on, accounts for most of the "drift" in traditional PEAD studies.

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

Method

Same event study design applied to each exchange independently:

• Signal: (epsActual - epsEstimated) / |epsEstimated|
• Universe: Exchange-specific market cap filters (historical FY key_metrics)
• Period: Exchange-dependent start date, all through 2025
• Execution: Next-day close (MOC). Entry at the close of the first trading day after the announcement.
• Benchmark: Local currency index per exchange (Sensex for India, Nikkei for Japan, FTSE for UK, SPY for US, etc.)
• Windows: T+1, T+5, T+21, T+63 trading days from entry
• Surprise cap: |surprise| <= 200%
• Single-period return cap: |return| <= 200% (filters price data artifacts)
• Min entry price: $1 (skips penny stock adjClose errors)
• Price data cleanup: Removes oscillation artifacts (phantom holiday rows, broken split adjustments) before any price lookups.
• Winsorization: 1st/99th percentile
• Excluded: ASX, SAO, SGX excluded for known fatal adjClose data quality issues.

Global Results

All 14 exchanges, with next-day close entry and local currency benchmarks. Sorted by beats CAR at T+63:

What the Data Shows

Five findings stand out.

1. 13 of 14 exchanges have a positive Q5-Q1 spread. The exception is Norway (OSL, 1,613 events), which has too thin a dataset for reliable conclusions. The relative signal (sorting by surprise magnitude and taking the extremes) works almost everywhere, even in markets where beats don't drift positively in absolute terms.

2. Asia-Pacific and smaller markets show meaningful post-entry beat drift. India (+2.93%), Hong Kong (+2.55%), China (+1.75%), Canada (+1.28%), Thailand (+1.05%), Taiwan (+0.85%), Switzerland (+0.82%), UK (+0.73%). These markets produce positive abnormal returns for beats even after entering at the next-day close. Major developed markets (US -0.32%, Japan -0.30%, Korea -0.14%) show no positive beat drift post-entry. The announcement-day reaction accounts for most of the "drift" in efficient markets.

3. Taiwan has the widest quintile spread. Q5-Q1 = +4.55pp vs TAIEX, edging out India (+4.28pp). The pattern in Taiwan is dominated by miss-side underperformance (Q1 = -3.13% at T+63) more than beat-side outperformance. Semiconductor concentration likely amplifies the disappointment reaction.

4. The miss signal is robust in most developed markets. Germany (misses -1.66%), Taiwan (misses -1.68%), Korea (misses -0.91%), US (misses -0.91%). The miss-avoidance signal survives MOC execution better than the beat-chasing signal. Two exceptions: China and Hong Kong misses drift positive vs local indices (+0.70% and +0.93% at T+63), reflecting market-wide momentum rather than failure of the relative signal. Q5-Q1 stays positive in both.

5. Smaller European markets show modest post-entry beat drift. Switzerland (+0.82%), UK (+0.73%), Sweden (+0.36%) all produce mildly positive beats vs local benchmarks. Sample sizes are smaller (1,766 to 11,414 events), so confidence intervals are wider, but the direction is consistent with the rest of the data.

The Asia-Pacific vs Major Developed Split

The pattern is clearer when you group by market depth and analyst coverage:

Asia-Pacific and emerging (India, Hong Kong, China, Taiwan, Thailand): Average beats T+63 = +1.83%

Smaller developed (Canada, UK, Switzerland, Sweden, Germany): Average beats T+63 = +0.69%

Major developed (US, Japan, Korea): Average beats T+63 = -0.25%

The contrast between Asia-Pacific and the most analyst-saturated developed markets is the cleanest split. Major developed market beats are essentially flat or negative post-entry, while Asia-Pacific beats show meaningful positive drift. Smaller developed markets sit in between. This fits what the academic literature predicts. Bernard and Thomas (1989, 1990) documented that PEAD is stronger for low-coverage stocks. Markets with less analyst coverage per listed company show larger drift because the announcement-day reaction doesn't fully capture the information.

Taiwan: Widest Quintile Spread, Miss-Dominated Signal

Taiwan (TAI+TWO) is the standout. The Q5-Q1 spread is +4.55%, the widest in the global study, ahead of India's +4.28%. Beats at T+63 are +0.85% vs TAIEX and misses are -1.68%. The drift pattern is dominated by the miss side. Q1 at T+63 shows -3.13%, the largest miss-quintile penalty in the global study.

This makes PEAD in Taiwan primarily a "miss avoidance" signal rather than a "beat chasing" signal. Taiwan's semiconductor and electronics concentration likely amplifies the earnings disappointment reaction, as supply chain signals are tracked closely by institutional investors and bad numbers cascade through the sector.

How We Handled Exchange Selection

Three exchanges were excluded for known fatal data quality issues: - Australia (ASX): adjClose oscillation errors affecting hundreds of stocks - Brazil (SAO): same root cause as ASX - Singapore (SGX): empty profile table in the FMP warehouse

The remaining 14 exchanges ran cleanly through the same methodology with new data quality guards (oscillation cleanup, $1 min entry price, 200% single-period return cap). Two exchanges are borderline on data volume (Norway: 1,613 events; Switzerland: 1,766). Both showed interpretable patterns and are included with the caveat that confidence intervals are wider. Norway's Q5-Q1 spread of -1.36pp is the one outlier from the otherwise universal positive-spread finding, but given the thin sample, it's not a reliable signal.

Screen for Global Earnings Surprises

SELECT e.symbol,
    p.exchange,
    p.country,
    CAST(e.date AS DATE) AS event_date,
    e.epsActual AS actual_eps,
    e.epsEstimated AS est_eps,
    ROUND((e.epsActual - e.epsEstimated)
        / ABS(NULLIF(e.epsEstimated, 0)) * 100, 1) AS surprise_pct
FROM earnings_surprises e
JOIN profile p ON e.symbol = p.symbol
WHERE CAST(e.date AS DATE) >= CURRENT_DATE - INTERVAL '30' DAY
  AND e.epsEstimated IS NOT NULL
  AND ABS(e.epsEstimated) > 0.01
  AND e.epsActual > e.epsEstimated
  AND p.exchange IN ('NSE', 'HKSE', 'SHZ', 'SHH', 'TSX', 'TSXV', 'TAI', 'TWO')
ORDER BY surprise_pct DESC
LIMIT 50

Run this screen live →

Limitations

MOC execution. Entering at next-day close removes the announcement-day reaction. This is realistic (you can't trade before seeing the announcement) but produces smaller numbers than traditional event studies that include the initial price jump.

Different start dates. India and Canada data starts from 2000. China data has thinner coverage before 2014. Shorter history for some exchanges means the results are less stable across market cycles.

Local index benchmarks. Sensex for India, Nikkei for Japan, FTSE for UK, OMXS30 for Sweden, SMI for Switzerland, SET for Thailand, OSEAX for Norway, KOSPI for Korea, TAIEX for Taiwan, SSE Composite for China, Hang Seng for Hong Kong, TSX Composite for Canada, DAX for Germany. These indices capture local market movement better than US-listed ETFs and avoid the currency effects that distorted the previous version of this study.

Event study vs portfolio backtest. These aren't portfolio returns. We don't account for position sizing, capacity constraints, or portfolio-level transaction costs. A real implementation would look different.

Currency. All returns are in local currency. Cross-border investors face additional FX risk not captured here.

Takeaway

PEAD is a global phenomenon with nearly universal structure (positive Q5-Q1 on 13 of 14 exchanges) but the tradeable signal depends heavily on where you're trading. With MOC execution and local benchmarks, Asia-Pacific (India +2.93%, HKSE +2.55%, China +1.75%, Taiwan +0.85%) and smaller developed markets (Canada +1.28%, Switzerland +0.82%, UK +0.73%) show real post-entry beat drift. Major developed markets (US -0.32%, Japan -0.30%, Korea -0.14%) don't.

The announcement-day reaction accounts for most of what traditional PEAD studies measure. Once removed, the beat-side signal only survives in markets with slower information diffusion. Taiwan has the widest quintile spread (Q5-Q1 = +4.55pp), driven by miss-side underperformance. India has the strongest beat-side drift (+2.93%) and the most balanced quintile gradient.

Norway's thin dataset (1,613 events) produces an unreliable negative Q5-Q1 spread, the only such case. The cleaner takeaway: PEAD survives MOC execution wherever analyst coverage is thinner and information diffuses more slowly.

Data: Ceta Research (FMP financial data warehouse). 14 exchanges, 2000-2025 (date ranges vary by exchange). Exchange-specific market cap filters. MOC execution (next-day close entry). Abnormal returns vs local currency index benchmarks. 1st/99th percentile winsorization. Surprise cap 200%. Single-period return cap 200%. Min entry price $1. Price oscillation cleanup applied. ASX, SAO, SGX excluded for known fatal data quality issues. Past performance does not guarantee future results. Educational content only, not investment advice.

References

• Ball, R. & Brown, P. (1968). "An Empirical Evaluation of Accounting Income Numbers." Journal of Accounting Research, 6(2), 159-178.
• Bernard, V. & Thomas, J. (1989). "Post-Earnings-Announcement Drift: Delayed Price Response or Risk Premium?" Journal of Accounting Research, 27(Supplement), 1-36.
• Bernard, V. & Thomas, J. (1990). "Evidence that Stock Prices Do Not Fully Reflect the Implications of Current Earnings for Future Earnings." Journal of Accounting and Economics, 13(4), 305-340.