How to Import cTrader Trades into PipJournal

Manually re-entering trades from cTrader wastes time and introduces transcription errors that corrupt your analytics. This guide walks you through exporting your complete cTrader trade history and importing it into PipJournal so you can start analysing your performance within minutes. It assumes no prior experience with PipJournal — if you have already completed your account setup, go straight to Step 1.

Step 1: Export Your Trade History from cTrader

Open the cTrader desktop platform or web terminal and click the History tab at the bottom of the screen. Set the date range to cover the period you want to analyse — for most traders, the past 90 days is a useful starting point, though you can export your full account history in one pass.

Click the export icon (a downward arrow or “Export” button depending on your platform version) and choose CSV. Save the file somewhere easy to find, such as your Downloads folder. The filename defaults to something like History_2026-01-01_2026-05-03.csv.

cTrader includes all closed positions in this export: entry price, exit price, lot size, symbol, open time, close time, swap, commission, and net P&L in your account currency. Each row is one closed trade.

Step 2: Review and Clean the CSV

Open the CSV in a spreadsheet application. Confirm the following columns are present:

Column	Example Value
Position ID	123456789
Symbol	EURUSD
Direction	Buy / Sell
Volume (lots)	0.10
Open Time	2026-04-15 09:32:11
Close Time	2026-04-15 14:07:44
Open Price	1.08432
Close Price	1.08611
Net P&L	17.90

Delete any summary rows at the top or bottom of the file — cTrader sometimes appends an account-total row that is not a trade. Save the file as CSV (not XLSX) before importing.

If you are importing from a prop firm account running on cTrader (common with FTMO and MyFundedFX), the column headers may differ slightly. Check that the Position ID, Symbol, and P&L columns are clearly identifiable.

Step 3: Import the CSV into PipJournal

Log in to PipJournal and navigate to Settings → Import Trades. Select cTrader as the platform. Drag and drop your CSV file into the upload area, or click to browse.

PipJournal will display a column mapping screen. Most cTrader columns auto-map correctly. Verify the following mappings before confirming:

• Open Time → Entry Date/Time
• Close Time → Exit Date/Time
• Volume (lots) → Lot Size
• Net P&L → Realised P&L

If your CSV is in a currency other than USD (e.g. GBP or EUR account), set the account currency in the dropdown so PipJournal applies the correct conversion for cross-currency P&L display.

Click Import. A progress bar shows how many trades are being processed. For 500 trades, expect under 10 seconds.

Step 4: Verify Imported Trades

After import, open the Trade Log and sort by open date. Pick five trades at random and compare them against the same trades in cTrader’s History tab. Check:

1. Entry and exit prices match to the pip level (e.g. 1.08432, not 1.0843)
2. Lot sizes are correct — a 0.10 lot trade should not appear as 1.0 lots
3. P&L figures match the net values in cTrader (after commission and swap)
4. Symbols resolved correctly — ensure EURUSD did not import as EUR/USD or EURUSDm

If you spot discrepancies in lot size, the most common cause is a volume unit mismatch. cTrader exports volume in lots; some prop firm platforms export in units (100,000 units = 1 standard lot). If needed, correct the lot size multiplier in Settings → Import Preferences and re-import.

Step 5: Tag and Annotate Your Trades

Raw imported data gives you P&L totals but limited insight. Tagging unlocks filtered analytics and session performance tracking.

For each trade, or in bulk using PipJournal’s multi-select, apply:

• Session tag: London, New York, Asia, or overlap
• Setup tag: breakout, reversion, trend continuation, news fade
• Pair tag: auto-populated from symbol, but confirm for exotic pairs

Once tagged, your weekly trade review gains real granularity — you can filter for “London session breakouts on GBPUSD” and see a win rate, average R:R, and average hold time for that specific subset.

Pro Tips

• Export in smaller 30-day batches if importing more than 2,000 trades — large files occasionally time out on slow connections.
• Set your account currency at import time, not after. Changing it retroactively requires re-mapping historical P&L.
• If you trade on a broker that appends a suffix (e.g. EURUSDm or EURUSD.raw), create a symbol alias in PipJournal Settings so all variants map to the same pair for analytics.
• Import your entire history before setting goals. Looking at 6-12 months of real data first helps you set realistic trading goals based on your actual baseline, not estimates.
• After import, run the edge measurement guide on your dataset — imported historical trades provide enough sample size to get statistically meaningful results immediately.

Common Mistakes to Avoid

1. Importing the XLSX version instead of CSV. cTrader’s export menu offers both formats. PipJournal’s importer requires CSV — XLSX files will fail or produce garbled data. Always export as CSV.

2. Ignoring commission and swap in P&L verification. The “Gross P&L” and “Net P&L” columns differ by commission and overnight swap. PipJournal uses Net P&L by default; importing Gross P&L will overstate performance on trades held overnight or on accounts with high spreads.

3. Importing without setting the account currency. If your cTrader account is denominated in GBP and you leave the currency as USD, every P&L figure will be numerically correct but labelled in the wrong currency, skewing your position size calculations.

4. Skipping the verification step. A lot-size mismatch at 10x scale (units vs. lots) will make your analytics look like you are risking far more than you are. Verify five trades manually — it takes two minutes and catches the most common import errors.

5. Not tagging before running analytics. Untagged trades report correctly on overall P&L but cannot be sliced by setup, session, or market condition. Spend 15-20 minutes bulk-tagging your import before drawing any conclusions from the analytics dashboard.

How PipJournal Helps

PipJournal’s import engine is built specifically for forex platforms, so cTrader’s column structure maps cleanly without manual field editing in most cases. Once your trades are in, the analytics dashboard breaks down performance by pair, session, day of week, and setup type — analysis that would take hours to recreate manually in a spreadsheet. The psychology tracking module lets you attach mood and confidence scores to individual imported trades retroactively, giving context to historical performance patterns. PipJournal’s one-time $179 lifetime pricing means you can import your full history and analyse it indefinitely without a recurring subscription cost.