Trading Journal Examples: Grading a +569.5% Range Against Your Actual Fill

TLDR

• A useful trading journal entry puts what the stock offered next to what you took. Session prices, volume, max favorable excursion (MFE) and filing status go in the same row as your entry, exit and stop. Without them, you grade yourself against nothing.
• Three worked examples from recent tape: OMH on Nov 4 (+569.5% MFE on 93.4M shares), CHSN on Nov 3 (+320.0% MFE on 90.9M shares, no catalyst identified in press releases) and EDSA on Nov 9 (+95.5% MFE, then a -28.0% close).
• Red closes teach the most. RAYA closed -25.3% on Nov 6 after offering +231.1% from low to high. Your entry and the timestamps decide whether that day was a loss or a win.
• The best trading journal format for small caps has four blocks: context, setup, execution and review. Filing status and session (pre-market, regular, after-hours) are required fields, not optional notes.
• Measure capture ratio over 50+ trades, not one. AI Insights in the SNACS trading journal tracks your MFE capture rate and the times of day where you lose money.

What Does a Good Trading Journal Example Look Like?

A good trading journal example is one record that shows the trade's context, the plan you wrote before entry, the execution, and a review that compares your result to the stock's full-day range. If any of those four blocks is missing, the entry tells you what happened but not why, so you can't repeat the trade or fix it.

Most journals I see from active small-cap traders are really P&L ledgers: ticker, shares, entry, exit, dollars. That's a broker statement with extra steps. It tells you that you made $640 on a runner. It doesn't tell you the runner offered +320.0% from low to high and you caught a sliver. It doesn't tell you that you bought a stock with under 3 months of cash runway, or that the macro call was Risk-Off that day.

Structure fixes this. After years of reviewing my own entries and other traders' sheets, the format that holds up has four blocks:

1. Context - date, session, market backdrop, catalyst, filing status, float and cash runway tier. Write it before you click buy, or at least before you look at the result.
2. Setup - the pattern tag (first green day, pre-market high break, red-to-green, liquidity test reclaim), the trigger level, the invalidation level and the planned size.
3. Execution - actual entry, exit, stop, size, timestamps, and max adverse excursion (how far the trade went against you before it worked).
4. Review - the day's MFE, your captured percentage, the capture ratio, a mindset note, and a one-line grade on process, not outcome.

The review block is where a small-cap journal pays off. Low-float runners print ranges that make large-cap moves look flat. On a stock that ran +569.5% from low to high, catching 40% of the move is a strong trade, even though it feels like you left money on the table. On a stock that offered +95.5% and closed -28.0%, a breakeven scratch can be the best-executed trade of your week. Without the MFE column, both entries just say 'small win' or 'scratch' and teach you nothing.

Here is the field set I use, and why each field matters in small caps:

Fill in the macro field with real numbers. As of this writing, the macro call is Risk-Off / Consolidation. The Russell 2000 (IWM) is at $282.51, -7.4% from its 52-week high of $305.18 and up +1.7% over 20 days. The Nasdaq 100 (QQQ) is at $679.35, -10.9% from its 52-week high. Say you review 60 trades later and find your breakout entries underperformed. That column tells you whether the problem was you or the tape.

For more on the review habit itself, the complete small-cap journaling framework covers review cadence and the weekly batch review. If you'd rather build your own sheet, the Notion trading journal template sets up these fields as database properties.

Worked Example #1: OMH on November 4 - Journaling the Range You Did Not Take

OMH shows why every journal entry needs a day-MFE column. The stock offered +569.5% from low to high on Nov 4 last week, and any gain you took has to be judged against that number. Without the column, a trader who took +60% logs a great day and never looks at the 500 percentage points left behind.

The session data from Nov 4 (last week):

• Pre-market range: $2.82 to $2.95
• Regular session: open $2.99, high $18.23, low $2.92, close $15.55
• After-hours close: $14.00
• Volume: 93.4M shares
• Regular-session close: up 420.1%
• Full-session MFE: +569.5%

A $10,000 position capturing the full MFE would have grown to $66,950 (+569.5%). Nobody captures all of that. The journal's job is to show how much of it your style could realistically take.

This is how I'd write the entry for a trader who bought the open and sold into the first big flush:

Date: Nov 4 | Session: Regular | Backdrop: Risk-Off tape
Catalyst: none identified in press releases that day
Filing status: ATM on file | Runway: 12+ months
Setup: Opening range break above pre-market high $2.95
Trigger: $2.99 open, held above $2.92 regular-session low
Plan: Stop under $2.92, scale out 1/3 at each +50% leg
Execution: Entry $2.99 | Exit: time + price
Day MFE: +569.5% | My capture: %
Capture ratio: my capture / 569.5
Mindset: was the exit planned or fear-driven?
Process grade: A / B / C

Look at what the template forces you to write down. The pre-market range was tight, $2.82 to $2.95, so there was no clear pre-market tell. The regular-session low of $2.92 sat just under the $2.99 open, which gives you a tight, logical stop. That structure is a repeatable setup: tight pre-market, open above the pre-market high, stop under the opening low. Log it 30 times and you have a playbook.

The filing field matters even with 12+ months of runway. The forensic filing breakdown of OMH's run documents the 2M float and the $40M ATM behind the move. A 6-K filing followed on Nov 9. If you held OMH into later sessions, record that you held a name with an ATM on file. The next time you hold a similar setup and it fades, you'll want that row to compare against.

The multi-day picture adds a second lesson. Across the five sessions from Nov 3 through Nov 9, OMH went from $2.89 to $25.84 (split-adjusted close-to-close), +794.1% on 147,554,989 total shares. A trader who sold at the Nov 4 close of $15.55 and wrote 'sold too early' needs a hold-rule field: what was the rule, and did you follow it? The outcome is noise. Whether you followed the rule is the data.

How could you have caught it before it ran? An RVOL sort with a float filter under 5M shares brings names like this to the top as volume arrives. The pre-market range gave no signal; the open did. Log the time of the scanner alert next to your entry time. That gap is a leak you can measure and fix.

Worked Example #2: CHSN on November 3 - The Entry With No Headline

CHSN is the example for tape-driven trades. It offered +320.0% from low to high on Nov 3 last week on 90.9M shares, and the specific catalyst was not identified in available press releases. That means the catalyst field reads 'none identified', which becomes a useful label once you've collected enough of them.

Nov 3 session data:

• Pre-market range: $1.00 to $1.07
• Regular session: open $1.08, high $4.15, low $1.05, close $3.38
• After-hours close: $3.59
• Volume: 90.9M shares
• Regular-session close: up 213.0%
• Full-session MFE: +320.0%

Capturing the full range would have turned the $10,000 base into $42,000 (+320.0%). CHSN was the top mover that Tuesday, and the top mover across the last four Tuesdays averaged a 104.8% gain.

Here's the lesson most traders miss. The after-hours close of $3.59 is above the regular close of $3.38. If you log 'close $3.59', you've mixed sessions, and every percentage you compute from it later is wrong. In your journal, a bare 'close' must mean the 4:00 p.m. regular-session close. Log after-hours prices in their own field.

The second lesson is the multi-day fade field. Over the five sessions from Nov 3 through Nov 9, CHSN went from $1.08 to $2.71 (+150.9%) on 151,463,813 total shares. The Nov 3 close was $3.38, so a swing trader who held from that close into the next week finished the window below their entry. A P&L-only journal just shows a loss. A journal with context fields shows a runner with no identified catalyst, 12+ months of runway and a stretched first-day range. With that, you can test whether the same combination fades for you across 20 examples.

Use tags, not narration. 'No catalyst / first-day range +320% / held overnight / gave back' is a row you can sort. Three paragraphs of feelings aren't.

The bullish reversal candlestick patterns article covers the CHSN candle structure and pairs well with the setup block of your entries.

Worked Example #3: EDSA and RAYA - Journaling the Red Close

Red-close days are where a journal teaches the most: the stock offered real range, but the close punished late entries. EDSA printed +95.5% MFE on Nov 9 and closed -28.0%. RAYA printed +231.1% MFE on Nov 6 and closed -25.3%. On a daily chart both are losers. In an intraday journal both were opportunities.

EDSA, Nov 9 (earlier this week). The catalyst was an agreement to develop and commercialize paridiprubart in Japan, released alongside an 8-K filing. The tape:

• Pre-market high: $3.57
• Regular session: open $3.46, high $3.93, low $2.37, close $2.49
• Full-day range: $2.01 to $3.93
• Volume: 84.6M shares, 1971.0x its 50-day average
• Day MFE: +95.5%; regular close: -28.0%

Capturing the full range on the $10,000 base gives $19,550 (+95.5%). But MFE is measured low-to-high across all sessions and says nothing about which came first. Your journal must record the time of the high and the time of the low. If the high printed first and the low came later, the low-to-high number was never a long trade. That's the exact trap covered in How to Backtest a Trading Strategy: The +897.1% MFE That Was Never Tradable.

For a trader who bought the $3.46 open on the headline, the entry reads: 'News chase / entry at open / regular low $2.37 / no stop defined.' The max adverse excursion field shows the problem in one number.

RAYA, Nov 6 (last week). The catalyst was a press release saying the Ruike facility had entered its final acceptance phase. The tape:

• Pre-market high: $1.39
• Regular session: open $1.13, high $2.12, low $0.64, close $0.84
• Volume: 73.9M shares, 842.1x its 50-day average
• Day MFE: +231.1%; regular close: -25.3%
• Cash runway tier: under 3 months

Full-range capture was $33,110 (+231.1%). The field that matters most here is runway. With under 3 months of cash, the company has a reason to sell shares into strength. The RAYA breakdown walks through the ATM behind the move. Write 'runway under 3 months + ATM on file' in the context block and afternoon fades on this setup stop surprising you.

Dilution cuts both ways, and the journal should record both. Companies with active ATMs and shelves often see the price pushed higher before shares are sold, and fast traders ride that pre-offering run. The same supply caps the move once selling starts. If you log filing status, you can measure which side of that you've been on.

Here is the full comparison across the case studies (open, high and close are regular-session values):

Three notes on that table. SDA's catalyst was a share repurchase program announced Nov 6 alongside a 6-K filing. A buyback is a different kind of catalyst from a partnership headline, so tag it separately. WCT's 1-for-10 reverse split took effect Nov 9 (announced alongside a 6-K filing on Nov 5), so comparing the $4.47 close to pre-split prices means nothing without the adjustment. CKX traded 4356.9x its 50-day average on news that Brad Jacobs would lead a $1 billion equity investment (8-K filing), and still closed -6.3%.

Common Trading Journal Mistakes Small-Cap Traders Make

The most common mistake is journaling outcomes instead of decisions, which turns the journal into a scoreboard instead of a feedback loop. Here are the mistakes I see most often, with the fix for each.

1. Logging P&L without the day's range. A +$400 day on OMH Nov 4 and a +$400 day on EDSA Nov 9 are completely different trades. One caught a fraction of +569.5%; the other caught a real chunk of +95.5%. Add the MFE column.

2. Only journaling winners. The losers carry the information. RAYA closing -25.3% after a +231.1% range teaches more about chasing entries than any green day.

3. Mixing session prices. OMH: regular close $15.55, after-hours close $14.00. CHSN: regular close $3.38, after-hours close $3.59. If you log the after-hours number as the close, every return you calculate from it later is wrong.

4. Skipping the macro field. Last week produced 40 runners of 50% or more, against a 4-week baseline of ~9.0 per week. That's a runner-heavy tape under a Risk-Off / Consolidation macro call. A strategy that works in runner-heavy weeks and fails in steady weeks looks random unless the journal records which kind of week it was.

5. Ignoring corporate actions. After WCT's reverse split on Nov 9, its $4.47 close can't be compared to pre-split prices. Record the split ratio and date.

6. Drawing conclusions from one trade. One CHSN-style overnight hold that fades proves nothing. Twenty with the same tags is a pattern. Review in batches, sorted by tag.

7. Writing feelings instead of tags. 'I was nervous' can't be sorted. 'Mindset: chasing' can, and after 50 trades it shows you exactly what chasing costs in dollars.

How to Apply This: The Best Trading Journal Format for Small Caps

The best trading journal format for small caps is a tagged, sortable record. Every trade carries context, setup, execution and review fields, and the review compares your capture to the day's MFE. Here's how to set that workflow up in SNACS.

Step 1 - Remove manual entry. The SNACS trading journal auto-syncs fills from 8 supported brokers, so entry, exit, size and timestamps fill in on their own. Your time goes into the fields your broker doesn't know: setup tag, catalyst, filing status and mindset.

Step 2 - Tag every trade with a setup. Use the same names every time: 'opening range break', 'pre-market high break', 'first green day', 'liquidity test reclaim', 'news chase'. Per-trade review supports setup tags plus mindset and emotion logging, and Mindset IQ tracks how your state lines up with your results.

Step 3 - Let AI Insights find the patterns. AI Insights analyzes your trade history to find your best setups, your worst time of day and your MFE capture rate. It delivers them in the app and by email. It's the batch review from mistake #6, done for you.

Step 4 - Review the dashboard by session and price range. The dashboard breaks down P&L by day, hour, session and price range, along with profit factor. If your sub-$1 trades (SDA and RAYA territory) and your $10+ trades (CKX territory) produce opposite results, you'll see it on one screen.

Step 5 - Turn proven tags into a playbook. Once a tag shows a consistent edge, build it in the AI Playbook Builder with historical context, setup, trigger, entry and exit steps. Live matching then puts a star on scanner tickers that fit, so your journal feeds your next trade alert.

Metrics to track every month:

How to Find These Setups Before You Journal Them

You find setups worth journaling with three tools: the scanner for volume and float, the ticker details page for filings and dilution, and SEC research for the full dilution picture. Here's the filter logic behind the case studies above.

Scanner filters. In the SNACS scanner, sort by RVOL descending, set a float filter under 5M shares and a price range that fits your size. EDSA at 1971.0x and RAYA at 842.1x their 50-day averages are the kind of names that land at the top of that sort. Add the Cash Runway and Dilution Alerts columns so your journal's context fields are on screen before you enter. Save the filter set as a named scan, then link it to a Dynamic Watchlist so matching tickers appear in real time.

Ticker details page. Click any ticker to open its details page: chart, dilution risk panel with active shelf, ATM and warrant facilities, recent news and SEC filings. That fills in your context block in ten seconds.

SEC research. For names you plan to hold, the Dilution Snapshot in SEC research shows active facility counts, shares at risk and the lowest exercise price. The small-cap universe carries ~6,300 active warrant facilities, ~3,300 active shelves and ~2,200 active ATM programs. In the past 3 days, 5 companies filed 424B5 pricing supplements and 7 S-3 filings came in from 6 unique tickers. That's new supply, and it belongs in the filing-status field.

Pattern context. The past 7 days produced 154 scanner patterns against a 90-day weekly average of 151.0. That includes 42 stocks with 100%+ gains, 28 stocks that traded 100M+ shares, and 84 liquidity tests where market makers probed price levels before a move. Record which pattern type each trade came from, and over time you'll learn which ones you actually trade well.

For the bigger picture on grading trades by range instead of close, see trade the range, not the close.

What to Watch Next: Turning Last Week Into Better Entries

The next step is to journal every trade this week with the full field set, then review them as a batch against last week's runner-heavy tape. Last week's 40 runners of 50% or more came against a 4-week baseline of ~9.0. Weeks like that inflate confidence, and your journal is what tells you whether the edge was yours or the tape's.

Watch three things. First, the macro call is still Risk-Off / Consolidation, with the Russell 2000 (IWM) up +1.2% over 5 days and +1.7% over 20 days. Log it on every entry. Second, EDSA, CKX and WCT all printed big ranges on Nov 9 with very different closes. Attach the Nov 9 context to any follow-up trades you take in them. Third, check the week-arc data: over the last 7 weeks, the most common arc was a steady Monday followed by a steady Friday. Record each Monday's tone in your journal and see whether your Friday trades behave differently after a steady start.

The journal won't find setups for you; the scanner does that. What the journal does is turn every OMH, CHSN, EDSA and RAYA you trade into data you can sort.

FAQ

What are some good trading journal examples for day traders?

A good day trading journal example records four blocks: context (date, session, backdrop, catalyst, filing status), setup (pattern tag, trigger, invalidation), execution (entry, exit, stop, timestamps) and review (day MFE, your capture, capture ratio, mindset). For example, an OMH entry for Nov 4 would show the +569.5% day MFE next to the trader's actual gain, so the grade reflects skill rather than luck.

What is the best trading journal format?

The best trading journal format is a sortable table where every trade has the same fields and is tagged rather than described in paragraphs. Tags like 'news chase', 'opening range break' or 'runway under 3 months' let you filter 50+ trades and see which setups make money, which is impossible with free-text notes.

Why should I journal losing trades and red-close days?

Losing trades and red-close days show where your entries and stops break down. RAYA closed -25.3% on Nov 6 after offering +231.1% from low to high, and EDSA closed -28.0% on Nov 9 after a +95.5% range. Logging your entry and the timestamps on days like these shows whether the loss came from chasing or from the setup itself.

What is MFE capture ratio in a trading journal?

MFE capture ratio is your percentage gain on a trade divided by the stock's max favorable excursion for the day. If a stock offered +320.0% and you captured +64%, your capture ratio is 20%. Tracked over many trades, it measures how well you exit momentum runners.

How do I journal pre-market and after-hours trades?

Log pre-market and after-hours trades in separate session fields and never mix their prices with the regular-session open and close. CHSN's regular close on Nov 3 was $3.38 but its after-hours close was $3.59. Mixing those two numbers corrupts every return you calculate later.

How often should I review my trading journal?

Review individual trades the same day, and review by tag once a week in batches of at least 20 trades. Single-trade conclusions are noise. Batch reviews by setup tag, session and runway tier show patterns you can act on.

Should I use a spreadsheet or an automated trading journal?

An automated trading journal saves the manual entry, which is why most traders keep journaling with one. The SNACS trading journal auto-syncs fills from 8 supported brokers and adds AI Insights for best setups, worst time of day and MFE capture rate, so your effort goes into tags and review instead of typing fills.

How does a trading journal improve a penny stock strategy?

A trading journal improves a penny stock strategy by linking your results to the factors that move small caps: float, filing status, cash runway and session. Once you can sort your trades by those fields, you find out whether names with under 3 months of runway or an active ATM are costing you money, and you can adjust your size accordingly.