Swing trader's journal: 6 fields to log overnight risk

Most trading journals were built for day traders. The default schema assumes you open and close in the same session, P&L is clean by 4 PM ET, and the worst risk you face is a stop hitting in real time. Swing traders live in a different world. You hold positions for 2-10 trading days. Gaps happen overnight. Earnings happen Wednesday after close. The cost basis on a Monday entry doesn't match the Friday exit price the way a day-trade does, and the journal needs to handle that.

Here are the 6 fields a swing-trading journal needs that a day-trading journal doesn't, and why each one matters when you're reviewing what worked and what didn't.

Field 1: Entry date + exit date (not just timestamps)

A day-trade journal shows entry time 09:42 and exit time 14:18 — that's all the same calendar day. A swing-trade journal needs entry date 2026-06-09 and exit date 2026-06-13. The math your dashboard runs (hold time, P&L per day held, edge by day-of-week-entered) all depends on this. Most generic journals collapse to a single timestamp and you lose the multi-day analysis.

Field 2: Planned overnight risk in dollars

At day-trade scale, your stop is your risk. At swing scale, your stop can be 8% below the entry and the gap-down on earnings can take you through it without filling. Your real overnight risk is closer to the position size times the worst plausible gap. A $20,000 position in a biotech the night before phase-3 trial data can be 50% overnight risk, not 8%.

Log the planned overnight risk as a separate field from the planned stop. When you review losing trades 6 months from now, you want to know whether you were short stop discipline or short overnight-risk awareness. (For the underlying math of how this connects to your overall account exposure, see the R-multiple primer.)

Field 3: Gap-risk score on each held position

Not all swing positions carry the same overnight gap risk. A SPY swing held through a quiet macro week is low gap risk. A small-cap biotech is high. An earnings holder is extreme. Score each held position 1-5 on overnight gap risk and log it.

The point isn't to predict the gap. It's to know which losing trades came from genuine risk you understood and accepted, and which ones came from carrying gap risk you didn't price in. They review very differently.

Field 4: Multi-day cost basis (with partials)

Day-traders rarely scale in. Swing traders do, constantly. You buy 100 shares at $42, the position dips, you add 50 more at $40, you scale out 75 at $46 a week later, the rest exits at $48 two days after that. The cost basis isn't a single number — it's a moving average that needs every fill tagged with date, price, and qty.

Most spreadsheets get this wrong. Your journal needs to handle a position as a series of fills with running cost basis, not a single entry/exit pair.

Field 5: Catalyst calendar held-through

Did you hold through earnings? Through CPI? Through a Fed meeting? Through OPEX? These are searchable when tagged. Six months from now you want to query: 'all swing trades held through earnings, win rate, average R.' If your tags don't capture which catalysts you held through, you can't answer that. (And if you don't know your edge under catalysts, you're guessing — see the drawdown primer for why catalyst-driven losses compound differently than chop-driven ones.)

Field 6: Thesis time-stamped at entry

Day-traders can sometimes get away with sloppy thesis notes because the trade is over in hours. Swing-traders cannot. You bought because earnings beats tend to follow through, the chart base looked clean, and the sector relative strength was leading. Two days later, you're watching the position chop sideways and you're already inventing reasons to either add or cut. Without the original thesis time-stamped, you cannot tell whether your current concern is new information or just hand-wringing.

Time-stamp the thesis at entry. When you exit, compare exit-thesis to entry-thesis. The delta is where most swing-trade mistakes live.

How TFQ handles swing fields

TradeFlow Quantum lets you mark accounts as 'swing' or 'day-trading' and the dashboard schema adjusts. Swing accounts get hold-time histograms, gap-risk distribution charts, catalyst-held-through tags as first-class filters, and partial-fill tracking with running cost basis. Day-trading accounts get the time-of-day, win-rate-by-hour, max-heat-per-trade fields instead. Same trades, different views per account.

Honest disqualifier

If you swing-trade 2-3 positions a month, a Google Sheet with a row per fill is fine. The 6-field schema starts paying back at 10+ swing trades a month or when you're trying to figure out whether your edge is real or you've been lucky on macro tailwinds for 6 months. Below that volume, the dashboard analytics don't have enough data to be useful and you're better off journaling longhand.

Swing-account mode included. Gap-risk scoring, catalyst tags, partial-fill cost basis on day one. $17/mo. 7-day free trial.