“My morning trades earn more.”
Track P&L, win rate, expectancy, and drawdown. Break results down to find a pattern worth investigating.
The question: What happened?
Your results tell a story.
Test the patterns behind it.
A better win rate is an observation. A trading edge needs evidence. EarlySignal connects detailed performance tracking with statistical research, so you can see which patterns your trade history actually supports.
Your trades. Transparent methods. Evidence you can inspect.
Do I trade better
before 11:00?
Outcome: expectancy Baseline: remaining trades
Before 11:00$142.60120 eligible trades
Rest of population$56.20180 eligible trades
Observed difference+$86.40 per trade
−$50$0+$100+$200
A positive difference, with uncertainty shown.
Evidence
for an association—not a promise of future returns.
Execution-level trade historyCustom performance workspacesStatistical hypothesis testingOngoing pattern monitoring
Knowing what happened
is only half the work.
Headline metrics can hide meaningful differences between setups, times, and behaviors. EarlySignal helps you separate the observation from the strength of the evidence behind it.
“How well does the evidence support that?”
Compare morning trades with the rest of your history. Inspect the difference, sample size, uncertainty, and evidence strength before changing your process.
The next question: How convincing is it?
EarlySignal combines both: a detailed journal and a statistical research workspace.
Track. Investigate. Keep learning.
Move from daily review to a reproducible study, then follow the evidence as new trades come in.
Your trading process,
in full context.
Go deeper than a single dashboard. Organize trades into buckets, review individual executions, and shape your performance workspace around the way you trade.
- Custom dashboards, charts, tables, scorecards, and calendars
- Filters and breakdowns by setup, timing, account, and more
- Trade and day reviews, setup tags, mistakes, and screenshots
Net P&L+$8,420
Win rate56.8%
Expectancy$70.17
Cumulative P&L120 closed trades
Setup breakdownExpectancy
Opening drive+$112
Pullback+$84
Range break+$38
A promising pattern
deserves a real test.
Ask a question in plain language or build a study yourself. Define your trade population, choose a condition and outcome, and compare it with the rest of the eligible trades.
- Sample sizes, effect sizes, and 95% confidence intervals
- Evidence ratings from insufficient through strong
- False-discovery adjustment for multiple comparisons
- Saved studies you can revisit as your history grows
Built for questions like yours
What changes my outcomes?
- 01How do I perform after two consecutive losses?
- 02Which setups have higher expectancy?
- 03Does position size change my average return?
- 04How do trades with rule violations compare?
“Inconclusive” is a useful answer. A small sample or weak signal should prompt more investigation, not a stronger claim.
More context.
Better questions. Clearer evidence.
Bring your records, your trading rules, and your research into the same environment.
Start with the fills.
Import supported broker execution files, connect a supported brokerage, or log trades manually. Review imports before applying them, with partial fills, fees, and trade reconstruction accounted for.
Find questions you missed.
Pattern Discovery scans relationships across timing, setups, behavior, sizing, and other available fields. Findings must clear sample-size, effect-size, and false-discovery safeguards.
Follow the evidence.
Weekly and monthly briefs connect performance review with research findings. Pattern monitoring evaluates new observations and can flag establishment, weakening, or recovery as evidence develops.
Put decisions in context.
Pair trade records with setup and mistake tags, discipline reviews, notes, and screenshots. Review individual trades and entire days to connect outcomes with your actual decisions.
Make the view your own.
Configure widgets, layouts, filters, and groupings. Use buckets to organize strategies or accounts, and focus your analytics and research on the trading history that matters.
Review with your community.
Choose which buckets to share with a community. Community owners can review shared performance and trades, giving a coach or group a common foundation for discussion.
Begin with the trades
you’ve already taken.
-
01
Bring in your history
Import an execution file, connect a supported broker, or enter trades yourself.
-
02
Review your performance
Organize your trades, add context, and find differences worth investigating.
-
03
Test the pattern
Build a study, inspect the evidence, and revisit it as new observations arrive.
Good questions.
Clear answers.
Talk to EarlySignal
How is this different from a trading journal?
A journal records trades and describes performance. EarlySignal also tests relationships in that history: a defined condition versus a baseline, with effect size, uncertainty, sample size, and evidence strength. You can investigate a pattern instead of relying on its headline metric alone.
Does statistical validation guarantee an edge?
No. Results describe associations in your historical trades. They do not establish causation or predict future returns. Research Lab makes uncertainty and data limitations visible; Briefs can monitor whether a discovered relationship holds up in later observations.
How much trade history do I need?
You can begin tracking with your first trade. Research comparisons require at least eight eligible trades in each group to calculate a result, and evidence ratings use stricter sample-size criteria. Pattern Discovery begins at 30 closed trades; that threshold alone does not guarantee a finding.
How do I bring my trades into EarlySignal?
Use manual entry, supported broker connections, or execution-file imports. CSV and other supported text exports are reviewed before import. Compatibility depends on the report’s fields and format; date-only records cannot support precise time-of-day or duration analysis.
What can Research Lab test?
Study outcomes such as expectancy, median P&L, win rate, average return, hold time, and fees. Compare available conditions including setups, entry timing, side, position size, prior outcomes, rule violations, and accounts. A study uses one comparison condition, with additional filters to define its population.
Your P&L isn't proof.
Build a case with your data.
Understand your performance. Test your assumptions.
Keep
learning as the evidence develops.