Earnings intelligence

The institutional method for trading earnings.

EarningSpy turns institutional and academic strategy into a clear method: When to enter, when to exit, and how much to risk. All built around post-earnings drift — a market anomaly documented for 50 years.

How it works

What we do

From a binary event to an asymmetric opportunity.

Earnings look like a coin flip. EarningSpy breaks them down into a measurable risk profile — and finds the cases where the potential reward clearly outweighs the risk taken.

01

01 · Entry — Is this earning worth it?

A risk-quality signal that gets ahead of the move — not a hunch.

02

02 · Exit — Hold the capital, or pull it?

If you're already in, we tell you whether to hold or exit before the print.

03

03 · Size — How much to risk?

The position size the asymmetry justifies — calculated, not guessed.

Behind each answer: Pre- and post-earnings snapshots, risk metrics calibrated to the earnings window, and machine-learning models. See the method →

What post-earnings drift (PEAD) is

After an earnings announcement, the price tends to keep drifting in the direction of the surprise — for up to 60 days. It's a market anomaly documented in academic research for five decades. EarningSpy is built to identify it and exploit it systematically.

We recalibrate the model every quarter. It only gets better with time.

From the Earnings Brief

The phenomenon, before and after the print.

We measure the anomaly before the announcement and verify the result after. That cycle is what trains the prediction.

DELL Thu · May 28 · After Close Dell Technologies Inc · Technology · 26.Q1

Historical post-earnings drift

Trim.3d30d60d
25.Q4 19.60% 37.38% 67.68%
25.Q3 4.35% -1.49% -13.16%
25.Q2 -9.08% -3.71% 18.22%
VaR hist. -4.58% CVaR -6.42% Vol. GARCH 49.64%
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The calendar

Hover a day. See what is reporting.

Click any company for its full risk and volatility profile.

MonTueWedThuFri
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20 8 rep.
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22

MAY 20 · REPORTING AFTER CLOSE

NVDA EPS +33.3%
PANW EPS −4.1%

Who we are

Born from research, built to trade.

EarningSpy began as a master's thesis: A rigorous review of whether post-earnings drift is still a live anomaly, which sectors it concentrates in, and how to detect it. What started as an academic question became a system to answer it in practice — quarter after quarter, on the real market.

The founder

Alberto José Rincones

Over ten years as a software engineer in fintech and financial infrastructure, and an active trader of his own capital. He holds an MBA and a master's in finance from Universidad Torcuato Di Tella, where his 2025 thesis is the direct origin of the EarningSpy model. Post-Earnings Announcement Drift (PEAD): A review of the anomaly and computation of NYSE abnormal returns .

EarningSpy exists to bring that rigor — institutional and academic — to the independent, sophisticated investor.

Start spying on earnings.

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