A pre-built Notion template with 4 linked databases, 13 macro catalysts, and 5 scenario frameworks. Stop improvising your trading log 鈥?start with a structure designed by practitioners who trade the ISM PMI every month.
A macro trading journal template is a pre-structured workspace for recording every macro economic catalyst you trade, the scenario you classified it into, the positions you took in response, and the outcomes you reviewed later. It is the systematic trader's equivalent of a lab notebook 鈥?without one, you are running uncontrolled experiments on your account balance.
The problem most traders hit is not a lack of data, but a lack of structure. A blank Notion page or a fresh Google Sheet gives you infinite freedom, which means you reinvent the schema every release. By release number four, you have four incompatible log formats and no way to compute a win rate. A template fixes this: it hands you the schema on day one, pre-linked and pre-populated, so you start logging correctly from the very first entry.
The Macro Catalyst Trading Journal is one such template. It ships as a Notion page with four linked databases and thirteen pre-loaded catalyst entries. After a one-time $7 purchase, you click Duplicate and the entire structure copies into your workspace in about 30 seconds. From there, every macro release is a new row 鈥?not a new schema.
There is a well-known pattern among retail macro traders: they nail the first few PMI prints, then slowly bleed out over six months without ever understanding why. The cause is almost always the same 鈥?no review loop. Without a journal, you cannot answer the only question that matters: which scenarios am I actually profitable in?
A proper macro trading journal lets you compute, after 12 releases:
This is the difference between a trader and a gambler. The gambler remembers the wins and forgets the losses. The journaler has the data.
Whether you use this template or build your own, your macro trading journal must capture these five fields per release. Anything less and you lose the ability to compute edge:
The Macro Edge template has dedicated properties for all five, plus a free-text "Notes" field for the qualitative read (e.g., "Fed Powell hawkish 2 days later, scaled out early").
Every catalyst entry in the journal links to one of five scenario frameworks. These are the same scenarios the ISM PMI trading strategy engine classifies 鈥?the journal and the engine share a vocabulary, so the data flows cleanly between them:
Growth above 52, prices contained (below 72). The sweet spot for risk assets.
RISK-ONSolid growth, mildly elevated prices. Constructive but selective.
RISK-ON (selective)Growth cooling toward 50, prices easing. The Fed's target path.
NEUTRALSub-50 headline, falling new orders. Defensive posture.
RISK-OFFMixed signals. Low confidence. Stand aside.
WAITEach scenario in the template has its own page with the classification rules, the default action set across SPY / US10Y / BTC / CRDO, and a notes section for your own tweaks. You link a Trade to a Scenario with a Notion relation 鈥?one click, no copy-paste.
Of the five scenarios, Goldilocks deserves a dedicated section because it is where the journal pays for itself fastest. Goldilocks economy trading is the regime where growth is firmly above 52 and prices are contained below 72 鈥?the Fed is on hold, real rates are stable, and risk assets have tailwinds from both earnings growth and multiple expansion.
In the Macro Edge engine, a clean Goldilocks print scores 85-95% confidence. The August 2026 ISM Mfg PMI (55.6 / 54.2 / 71.1) classified as Goldilocks at 85% 鈥?and the journal is where you verify that this 85% confidence actually translated into a winning trade. Over a year of Goldilocks entries, you build a personal distribution of outcomes that tells you exactly how aggressively to size the next one.
The journal's Scenario database has a pre-built Goldilocks page with the default action set (long SPY high priority, short US10Y high priority, long BTC and CRDO medium priority) and a notes field where you record what you actually did. The delta between the default and your execution is where the learning lives.
The template is not a single table 鈥?it is four Notion databases, linked by relations so a change in one propagates to the others. This is what makes it a journal rather than a log: you can navigate from a Catalyst to its Scenario to the Trades you placed to the Reviews you wrote, in any direction, without leaving Notion.
The macro events you trade. Each has a date, source, and the input triple.
13 pre-loadedThe 5 classification frameworks with rules, biases, and default action sets.
5 pre-loadedIndividual positions: direction, instrument, size, entry, exit, P/L in bps.
schema onlyPost-mortems at 1-week and 1-month horizons. The loop that creates edge.
schema onlyThe Catalysts database ships with the major US macro events already entered, so you do not have to look up release cadence or typical ranges:
Each catalyst entry has fields for the consensus forecast, the actual print, the surprise (beat/miss/in-line), and a relation to the Scenario it produced. When a new month's print lands, you duplicate the catalyst row, update the numbers, and the rest of the workflow follows.
That is the entire setup. There is no fifth step, no integration to configure, no API key to paste. The template is a static Notion structure 鈥?it works offline, syncs across devices, and never expires. The $7 is a one-time payment; Gumroad handles a 30-day refund if the structure doesn't fit your workflow.
Here is what a complete journal entry looks like for a real release. The ISM Manufacturing PMI printed on Aug 4, 2026 at 10:00 AM ET:
# Catalyst entry
Name: ISM Mfg PMI 路 Aug 2026
Date: 2026-08-04 10:00 ET
Source: Institute for Supply Management
Consensus: 53.2 / 53.0 / 72.5
Actual: 55.6 / 54.2 / 71.1 (headline / new_orders / prices_paid)
Surprise: BEAT on all three
# Linked Scenario (auto-classified via the engine)
Scenario: 馃嵂 GOLDILOCKS
Bias: RISK-ON
Confidence: 85%
# Linked Trades
1. LONG SPY @ 551.20 size 4.2% priority high
2. SHORT US10Y @ 99.85 size 3.5% priority high
3. LONG BTC @ 61200 size 1.5% priority medium
4. LONG CRDO @ 78.40 size 1.0% priority medium
# Linked Review (added 1 week later)
1-week: SPY +1.8%, US10Y -0.9%, BTC +4.1%, CRDO +2.2%
Realized: +118 bps on the basket
Note: Clean print, no Fed speakers in the window. Held full size.
The whole entry takes about 90 seconds to write if you have the engine's output in front of you 鈥?and the live demo gives you that output for free. The journal turns those 90 seconds into a permanent, queryable record.
You could build this in Google Sheets or a paper notebook. Here is the honest comparison, so you can decide what fits your workflow:
| Feature | Macro Edge Template | DIY Spreadsheet | Paper Notebook |
|---|---|---|---|
| Setup time | 30 seconds | 2-4 hours | ~1 hour |
| Linked relations | Yes (4 DBs) | Manual VLOOKUP | Impossible |
| Win-rate by scenario | 1-click filter | Pivot table | Manual tally |
| Mobile logging | Native app | Sheets app | No |
| Pre-loaded catalysts | 13 | 0 | 0 |
| Cost | $7 once | Free | Free |
If you enjoy building spreadsheets and have a free weekend, the DIY route is legitimate. The template is for traders who would rather spend that weekend reviewing last month's trades than re-deriving a schema.
If you trade systematically, you can skip the manual classification step entirely. The Macro Scenario Analysis API returns the scenario, bias, confidence, and action set as JSON 鈥?which you can pipe straight into a Notion API call to create the Catalyst entry automatically:
# Classify the print, then auto-log to Notion
import requests, datetime
# 1. Classify via the live engine
r = requests.post(
"https://macro-scenario-api.onrender.com/classify_scenario",
json={"headline": 55.6, "new_orders": 54.2, "prices_paid": 71.1}
)
result = r.json() # 鈫?{"scenario":"GOLDILOCKS","bias":"RISK-ON","confidence":85,...}
# 2. Create the Notion Catalyst entry with these fields
# (use the Notion API + your integration token)
The API has a 100-call/month free tier on RapidAPI 鈥?more than enough for one call per macro release per month. The complete bundle includes the Python report generator that does the classification and formats the markdown report for you, so the only manual step is pasting the result into Notion (or automating that too).
No. The template works on Notion's free plan. The free plan allows unlimited blocks for personal pages, and the four databases fit comfortably within the free tier's limits. You only need a paid plan if you share the workspace with a team.
Yes 鈥?completely. Once duplicated, the template is an ordinary Notion page in your workspace. You can add properties, rename databases, change views, add automation rules, or delete anything you don't use. The pre-loaded structure is a starting point, not a constraint.
Generic trading journals are built around technical setups (chart patterns, indicators, entries/exits). A macro trading journal is built around scheduled economic catalysts and the scenarios they produce. The fields, the relations, and the pre-loaded entries are all specific to macro trading 鈥?ISM PMI triples, FOMC dot plots, CPI surprise vs. consensus. A generic template cannot compute your win rate in the Goldilocks scenario because it has no concept of a scenario.
The Trades database is asset-agnostic. The default action set in each Scenario page uses SPY/US10Y/BTC/CRDO as examples, but you can edit those to whatever you actually trade 鈥?ES futures, TLT, ETH, GLD, anything. The scenario classification logic is independent of the instruments; the instruments are just the execution layer.
Yes. All sales go through Gumroad, which offers a 30-day refund window on digital products. If the template structure doesn't fit your workflow, contact Gumroad support for a full refund 鈥?no questions, no friction.
4 linked Notion databases 路 13 pre-loaded catalysts 路 5 scenario frameworks 路 $7 one-time 路 30-day refund
Get the Template ($7) Preview LiveTemplate + live API + Pine Script indicator + HTML dashboard + Python report generator 鈥?$14.99 one-time, zero subscriptions.
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