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Market2000 Earnings Surprise Pattern Analyzer
x402
Market2000 Earnings Surprise Pattern Analyzer is a paid API for AI agents from market2000.xyz, paid per call via x402, $0.02/call, status unknown (last checked 2026-09-15).
Analyzes historical earnings surprise patterns for a stock ticker, returning beat/miss history, EPS estimates vs actuals, and post-earnings price reaction signals.
Price / call$0.02
Success—
StatusUnknown
How this service works
An origin the crawlers already index. We count what AI agents try to buy, what they are refused, and what the AI companies take without sending anyone back. Sold per call in USDC.
Output
Returns a JSON object with: the ticker symbol, a list of historical quarterly earnings records (date, beat/miss result, EPS estimate, EPS reported, price reaction %), a summary (beat rate %, avg EPS surprise %, avg price reaction on beat and miss), total periods analyzed, and trading signals (consistent_beater, buy_dip_after_miss, high_volatility_event booleans).
Example use cases
Screen consistent earnings beaters
“I'm building a watchlist of stocks that reliably beat earnings estimates — can you check whether NVDA qualifies as a consistent beater, and tell me its beat rate, average EPS surprise, and how the stock tends to move after a beat?”
Buy the dip after earnings miss
“TSLA just missed earnings and the stock is down — before I buy the dip, can you pull its historical earnings miss data and tell me whether it typically recovers after a miss and what the average price reaction looks like?”
Gauge earnings volatility before options trade
“I'm thinking about buying options around AMZN's upcoming earnings announcement — can you analyze its historical post-earnings price swings so I know how volatile it tends to get and whether the moves are bigger on beats or misses?”
Technical details
Endpoint
GEThttps://market2000.xyz/earnings_surpriseWhen to prefer
Use this endpoint when you need a quantitative, pattern-based summary of a stock's historical earnings surprise behavior — especially when you want signals like consistent-beater status or post-earnings drift tendencies. Prefer this over raw earnings data sources when you need pre-computed signals ready for trading or screening decisions. Best for stocks with enough quarterly history (4+ periods) to generate meaningful patterns.
Side effects
- Unknown or invalid ticker symbol returns an error or empty history
- Insufficient historical data for requested periods returns fewer records than requested
- Payment failure via x402 on Base results in 402 response with no data
- Rate limiting or overload may return 429 or 503 errors
- Delisted or OTC stocks may have incomplete EPS data
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
Schema · Response
{
"type": "json",
"example": {
"signal": {
"consistent_beater": true,
"buy_dip_after_miss": false,
"high_volatility_event": false
},
"ticker": "AAPL",
"history": [
{
"date": "2025-10-30",
"beat_miss": "beat",
"eps_estimate": 1.54,
"eps_reported": 1.64,
"price_reaction_pct": 1.8
}
],
"summary": {
"beat_rate_pct": 87.5,
"avg_eps_surprise_pct": 4.2,
"avg_beat_reaction_pct": 2.1,
"avg_miss_reaction_pct": -3.8
},
"periods_analyzed": 8
}
}Tags
x402
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