Earnings Surprise Drift in India: The Strongest PEAD in Our Global Study

India has the largest earnings surprise drift of any exchange we tested. Beat the estimate on NSE and your stock produces +3.77% cumulative abnormal return over the following 63 trading days. That's about 16x the equivalent figure for US stocks (+0.24%). The Q5-Q1 quintile spread of +6.89% is the widest across all 14 exchanges in our study. India is distinctive for its strong positive-side drift. Misses also drift modestly negative (-0.83%), but the beat side is where the signal concentrates.

Contents

1. Method
2. The Strategy
3. What We Found
4. Positive vs Negative Surprise Drift
5. Quintile Analysis at T+63
6. India's Beat Rate Is Below 50%
7. How India Compares Globally
8. When It Works and When It Struggles
9. Run It Yourself
10. Limitations
11. Part of a Series
12. References

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

Method

The Strategy

Post-Earnings Announcement Drift (PEAD) is a documented market anomaly dating to Ball and Brown (1968). The mechanism: markets underreact to earnings news on announcement day, then gradually incorporate the signal over weeks. Bernard and Thomas (1989) showed the drift persists for up to 60 trading days in US markets.

We extended this analysis globally. Each exchange gets its own event study using local benchmark returns. India's results stand out from every other market in the dataset.

What We Found

Positive vs Negative Surprise Drift

India's positive drift builds the entire way to T+63. This isn't a T+1 pop that fades. It's genuine drift that compounds over three months: +0.56% at T+1, +1.00% at T+5, +1.86% at T+21, +3.77% at T+63.

The negative surprise drift is moderate at T+63 (-0.83%). Misses drift down, but not severely. The main story is the beat side outperformance, not the miss side collapse. India's PEAD is fundamentally about what happens after a genuine positive earnings surprise.

Quintile Analysis at T+63

The Q5-Q1 spread is +6.89%, the largest in our global study. Q5 beats produce +5.39% over 63 trading days. Q1 misses produce -1.50%. The distribution skews strongly upward.

Q5's t-stat of 11.8 reflects a statistically robust finding across 1,546 events. Q1's t-stat of -3.4 confirms the miss-side drift is real, though smaller in magnitude.

India's Beat Rate Is Below 50%

India's beat rate is 47.3%. More companies miss estimates than beat them. This is the inverse of the US pattern (61.9% beats). The sub-50% beat rate reflects analyst estimates that aren't systematically conservative. Companies aren't managing guidance to guarantee beats.

In the US, beating estimates is the norm, so the signal is diluted. In India, a genuine beat is rarer and the market reacts more strongly. The T+1 gap (+0.56%) is slightly below the US, but India's drift compounds all the way to T+63 (+3.77%) rather than fading.

How India Compares Globally

India ranks first in Q5-Q1 spread across all 14 exchanges tested at +6.89%. The next closest are Taiwan (+6.25%) and Hong Kong (+5.49%). US ranks 8th at +3.72%. Sweden ranks last at +1.12%.

India has the strongest positive-side drift globally. No other exchange produces +3.77% positive surprise drift at T+63. Q5 beats reach +5.39%, more than double any other exchange's Q5 figure.

When It Works and When It Struggles

India's PEAD is primarily a positive-side story. Running a long-only strategy on Q4+Q5 beats is the natural implementation. Q4 produces +3.50% and Q5 produces +5.39% at T+63. The miss side (-0.83% average, -1.50% for Q1) is real but smaller — shorting Q1 provides meaningful but not dominant alpha.

The drift builds gradually. T+1 is +0.56%, T+5 is +1.00%, T+21 is +1.86%, T+63 is +3.77%. The Indian market is slower to price in positive news than Western markets. The capture window is wide.

Indian markets have lower liquidity for smaller-cap stocks. Implementing a PEAD strategy that requires quick execution at T+1 close faces more slippage on NSE than on NYSE or NASDAQ.

Run It Yourself

-- Recent large positive earnings surprises on BSE+NSE
WITH deduped AS (
  SELECT
    es.symbol,
    es.date,
    es.epsActual,
    es.epsEstimated,
    (es.epsActual - es.epsEstimated) / NULLIF(ABS(es.epsEstimated), 0) AS std_surprise,
    ROW_NUMBER() OVER (PARTITION BY es.symbol, es.date ORDER BY es.lastUpdated DESC) AS rn
  FROM earnings_surprises es
  JOIN profile p ON es.symbol = p.symbol
  WHERE p.exchange = 'NSE'
    AND p.marketCap >= 100000000
    AND p.isActivelyTrading = true
    AND es.date >= CURRENT_DATE - INTERVAL '90 days'
    AND ABS(es.epsEstimated) > 0.01
)
SELECT
  symbol,
  date,
  epsActual,
  epsEstimated,
  ROUND(std_surprise * 100, 1) AS surprise_pct
FROM deduped
WHERE rn = 1
  AND std_surprise > 0.10
ORDER BY date DESC, std_surprise DESC
LIMIT 50

Run this query on Ceta Research →

Limitations

7,743 events across 26 years is a smaller sample than the US study (170,150 events). The NSE-only universe avoids dual-listing duplication that would inflate event counts when combining BSE and NSE. Early years have sparse coverage, so results from 2000–2005 carry wider confidence intervals. The statistical significance of Q5 (t-stat 11.8) is strong, but individual-year results will vary.

Analyst coverage in India is thinner than in the US. Consensus estimates for small and mid-cap Indian stocks come from fewer analysts, which makes the standardized surprise noisier. Our market cap filter helps here but doesn't eliminate the issue.

Execution in India requires attention to settlement cycles and trading hours. The T+1 CAR in this study uses closing prices. Real-world slippage on announcement-day trades will reduce the captured edge.

Part of a Series

• PEAD Across 14 Global Exchanges: The Drift Is Universal
• Earnings Surprise Drift on US Stocks: 170,000 Events, 26 Years

References

• Ball, R. & Brown, P. (1968). An empirical evaluation of accounting income numbers. Journal of Accounting Research.
• Bernard, V. & Thomas, J. (1989). Post-earnings-announcement drift: Delayed price response or risk premium? Journal of Accounting Research.
• Foster, G., Olsen, C. & Shevlin, T. (1984). Earnings releases, anomalies, and the behavior of security returns. The Accounting Review.

Data: Ceta Research, FMP financial data warehouse