Earnings Intelligence: From Filings to Forecasts
Combine historical surprises, forward estimates, revision trends, and granular 8-K tables. The complete earnings dataset for quant strategies, fundamental analysis, and event-driven trading.
Complete earnings data - actuals, surprises, forward estimates, and quarterly report detail. Backtest earnings strategies, track estimate revisions, and benchmark individual names against index-level expectations.
from axion import Axion, utils, visualize
client = Axion(api_key="your_api_key")
tickers = ["AAPL", "MSFT", "NVDA", "META"]
def fetch_history(row):
t = row["ticker"]
return (t, [
{"ticker": t, "quarter": q["quarter"], "surprise": q["epsDifference"]}
for q in client.earnings.history(t)
])
history_map = {}
utils.work(utils.df([{"ticker": t} for t in tickers]), fetch_history, history_map)
all_rows = [row for rows in history_map.values() for row in rows]
df_hist = utils.df(all_rows)
beat_rate = (
df_hist.groupby("ticker")
.apply(lambda x: (x["surprise"] > 0).mean())
.reset_index(name="beat_rate")
)
visualize.barh(beat_rate, x="beat_rate", y="ticker")




Quarterly actuals vs. consensus estimates. Track EPS surprise percentage, absolute difference, and fiscal quarter end dates for the last 4-8 quarters.
Current & next quarter EPS/revenue estimates: average, low, high, analyst count, and year-over-year growth. Plus long-term growth (LTG).
Up/down revision counts over 7 and 30 days. EPS trend over 90 days to see momentum shifts before the print.
Structured financial tables (balance sheet, cash flow, income) extracted directly from earnings releases. Scale multipliers and column headers preserved.
S&P 500 earnings growth estimates for the same periods - benchmark company estimates against the broader market.
Number of analysts covering the stock, consensus trend, and surprise histories to gauge market expectations.
Global Earnings Coverage
Quarterly and annual earnings history, forward estimates, and 8-K filings from SEC, SEDAR, and global regulators. One API for earnings intelligence across US, Canada, UK, EU, and Asia-Pacific.
Combine historical surprises, forward estimates, revision trends, and granular 8-K tables. The complete earnings dataset for quant strategies, fundamental analysis, and event-driven trading.
Every endpoint returns data sourced directly from analyst consensus and SEC filings - no mock data, no placeholders. Here's exactly what you get back for Apple.
Access historical and forward earnings data for 60,000+ public companies worldwide. Get quarterly actuals vs estimates, surprise percentages, analyst revision trends, and parsed 8-K tables—all through a single, normalized API. Built for earnings backtesting, event-driven trading, and fundamental analysis.
Access NowConsensus EPS estimates
MSFT
Today · After close
Est. EPS
$3.12GOOGL
Jan 28 · After close
Est. EPS
$2.09META
Jan 29 · After close
Est. EPS
$6.72Latest reported vs consensus
82%
beat rate this seasonAAPL
+4.2%
AMZN
+11.8%
TSLA
-6.1%
You can access historical and forward earnings data for public companies worldwide.
90-DAY ANALYST TREND
FY26 EPS
$4.18
FY26 revenue
$198B
Gross margin
74.8%
You can analyze actuals, estimates, and surprise percentages across decades of earnings data.
NVDA · AUG 27
Consensus EPS
$0.94
Whisper EPS
$1.01
You can backtest earnings strategies and model earnings reactions across full market cycles.
FUNDAMENTAL COMPOSITE
Cash conversion
112%
FCF / net income
Accrual ratio
-4.2%
Lower is better
You get comprehensive consensus estimates and revision trends for deeper earnings analysis.
QUARTERLY EBITDA
Prior
Volume
Price
Cost
FX
Current
Margin
28.4%
YoY expansion
+180bp
You receive structured earnings data within a day of SEC filing for timely analysis.
Institutional-grade earnings data trusted by quant funds, fundamental investors, and fintech platforms.
Flexible plans for developers, startups, and enterprises. Access comprehensive financial data through a single, reliable API.
Join thousands of developers using Axion to power their financial applications. Start with our free tier and scale as you grow.
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