Broker review

Alpaca trade journal for traders who want cleaner review

A focused review page for Alpaca traders who want to turn raw fills into repeatable lessons.

Who this page is for

Alpaca traders who want a low-friction way to review equities or crypto execution.

Core problem

A Alpaca workflow can collect the fills, but it still needs a review layer that shows the process quality behind the P&L.

Why this matters

A journal is only useful when it separates clean decisions from lucky outcomes.

If the last loss or the last trade is the only thing you remember, the review loop is too weak.

The goal is to see the pattern before the next session starts.

What to do first

Start with the last 20 closed trades from Alpaca.

Group them by setup, time of day, and exit quality.

Mark the decision that most often turns a valid idea into a weak trade.

What to measure

P&L by setup, trade pacing, and follow-up behavior after a red trade

Trade count after the first loss or warning

Average result of late-session trades versus early-session trades

How it helps

Try the demo to see the journal layout before you connect anything.

Import CSV history if you want to validate the workflow on your own trades first.

Keep the same labels every session so the repeated mistake stays visible.

A low-friction import path for Alpaca traders who want value before wiring in a live connection.

Closed-trade review for Alpaca traders who want MAE, MFE, exit efficiency, and hold-time context.

A cleaner way for Alpaca traders to review history, track rules, and stop rebuilding the same columns by hand.

A simple first-run path for Alpaca traders who want the minimum setup that still produces useful review.