Earnings Surprise Drift in Japan: 17,000 Events, Miss-Heavy PEAD

Japan has the second-highest beat rate of any exchange we tested: 57.1% of earnings announcements come in above estimates. The drift is real in both directions vs the Nikkei 225. Biggest beats produce +2.09% cumulative abnormal return at T+63. Biggest misses fall -2.84%. The Q5-Q1 spread of +4.93% puts Japan among the stronger PEAD markets globally. Against the local Nikkei benchmark, the miss side dominates: negative drift is significantly larger than positive drift.

Contents

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

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

Method

The Strategy

Post-Earnings Announcement Drift (PEAD) is one of the most replicated anomalies in finance. Ball and Brown (1968) first documented that stocks continue drifting in the direction of their earnings surprise for weeks after announcement. Bernard and Thomas (1989) showed the effect persists for up to 60 trading days. Foster, Olsen, and Shevlin (1984) confirmed the pattern across different earnings windows.

The mechanism is behavioral: markets underreact to earnings news on announcement day, then gradually price in the information over the following weeks. We tested whether this holds for Japanese equities over a 26-year sample.

What We Found

Positive vs Negative Surprise Drift

Japan's PEAD is asymmetric vs the Nikkei 225. Beats drift up modestly (+0.91% at T+63). Misses drift down persistently and keep building through all four windows, reaching -2.43% at T+63. The miss side is nearly 3x larger in magnitude than the beat side.

The negative drift accelerates over time: -1.57% at T+1, -1.84% at T+5, -2.00% at T+21, -2.43% at T+63. Japanese markets react sharply to bad news on announcement day, then continue pricing it in over the following three months.

Quintile Analysis at T+63

The Q5-Q1 spread is +4.93% at T+63. Q5 has a t-stat of 8.3 and a 53.6% hit rate. Q1 has a t-stat of -11.3. Both sides are statistically robust, with the miss side significantly stronger.

Q3 (near-consensus) drifts -0.88% at T+63 vs Nikkei. Japan's benchmark-relative performance for "meeting expectations" is negative — consistent with a market where beating is the norm (57.1%) and simply meeting estimates doesn't satisfy.

Japan's Beat Rate Context

Japan's 57.1% beat rate is the second-highest globally after the US (61.9%). Japanese analyst estimates are moderately conservative, though less systematically so than in the US. The event distribution is reasonably balanced: 9,775 positive events vs 7,358 negative events.

Against the Nikkei 225, Japan's drift is miss-weighted. Both sides are actionable, but the short-the-miss trade has historically been the larger opportunity. Q1 (-2.84%) is significantly more negative than Q5 (+2.09%) is positive.

When It Works and When It Struggles

The T+1 reaction on the negative side is sharp (-1.57%). The drift then keeps building through T+5 (-1.84%), T+21 (-2.00%), and T+63 (-2.43%). Japanese markets don't fully price in bad news on announcement day. The miss drift compounds over the full three months.

Positive surprises show a more modest trajectory. The drift from T+1 (+1.08%) to T+63 (+0.91%) is relatively flat. Most of the beat drift is captured early, with limited continuation beyond T+21.

Japan's market structure may contribute to this pattern. Institutional ownership is high, but sell-side coverage is concentrated in large-cap names. Smaller and mid-cap stocks in the JPX universe have thinner analyst coverage, which can create wider initial mispricing when surprises occur.

Run It Yourself

python3 earnings-surprise/screen.py --preset japan

-- Recent large earnings surprises on JPX
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 = 'JPX'
    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

17,133 events over 26 years is a solid sample. Coverage is thinner in the early 2000s, when fewer Japanese companies had systematic consensus estimates in our FMP warehouse. Results from 2000–2004 carry wider confidence intervals.

Japanese earnings calendars differ from Western norms. Many Japanese companies announce annual results in May, creating seasonality in event density. Quarterly reporting is less standardized than in the US, which means T+63 windows can span across subsequent earnings announcements for some companies.

Currency effects aren't controlled. The CAR computation uses JPY-denominated returns against a JPY benchmark, so FX doesn't introduce distortion within the study, but investors converting results to other currencies will face additional variance.

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