Built for traders who want signal instead of hype, structure instead of noise,
and a workflow that can actually compound.
Most traders approach earnings like coin flips. But earnings aren’t random.
Week after week, the same patterns appear in volatility, in price behavior, and in the way
certain names react to expectations. The edge has been there for decades — consistent,
measurable, and repeatable — but hidden behind fragmented research, scattered tools,
and ad-hoc decisions.
We exist to make that edge simple.
EarningsWatcher is built on 10+ years of earnings data and cutting-edge modeling. It turns that
history into clear, research-backed setups, shows when IV and price behavior are actually meaningful,
and gives you tools that you won’t find anywhere else.
We launched 3 years ago, and we are now a community of more than 1,000 traders, grown entirely
through word of mouth. A small, focused team builds for people who want signal instead of hype,
structure instead of noise, and a process that compounds.
If you’re new, you’ll find a straightforward path without guesswork. If you’re experienced,
you’ll get cleaner inputs, tighter context, and a workflow that respects the discipline
you’ve built.
Order over noise. Process over prediction. Discipline over drama.
Are you ready to trade earnings with a repeatable statistical edge?
Amin
Founder & CEO
Amin is a data scientist trained at Ecole Centrale Paris, one of France’s top engineering schools.
He began his career in ad-tech, developing algorithms for real-time bidding, before spending three
years at Palantir, working across technical and client-facing functions and guiding teams through
complex data projects. Today he leads the company’s vision, product strategy, and research —
refining the statistical edge behind earnings trading and making it accessible to retail traders.
Cassandra
Social Media & Marketing
Cassandra is a creative and strategic marketing professional with a strong background in business
and digital communication. She understands how to translate complex trading concepts into content
that feels clear, engaging, and accessible. She brings energy, clarity, and consistency to how
we show up across platforms and communicate with traders every day.
Paul
Software Developer
Paul is a full-stack developer focused on building clean, reliable, and intuitive product experiences.
With a solid foundation across both frontend and backend technologies, he turns complex datasets and
models into fast, user-friendly features traders can trust. He shapes the platform’s technical
backbone to ensure performance, stability, and a smooth experience as new tools roll out.
Yale
Strategic Advisor
Yale is a successful entrepreneur with multiple startup exits and deep experience in building and
scaling companies. With a strong background in trading and market structure, he knows how to combine
data, discipline, and execution into real, repeatable edge. As a strategic advisor, he helps guide
product direction, long-term strategy, and how EarningsWatcher best serves traders as it grows.
Jiang
Data & Modeling
Jiang is a data scientist fueled by a passion for quantitative finance and market data clarity.
He builds and optimizes the robust data pipelines that underpin EarningsWatcher’s analysis — focusing
on data quality, statistical integrity, and reliable metric generation so traders can confidently
trust the numbers behind every setup.
Dan
Trader
Dan is a seasoned trader specializing in earnings and volatility strategies. He has refined his
approach through countless cycles and iterations, turning it into a clear, repeatable framework
grounded in real market experience. He contributes research, strategy refinements, and practical
insights to help members apply the edge in live market conditions.
