How to Import TradeLocker Trades into PipJournal

TradeLocker is a web-based trading platform increasingly used by prop firms and retail brokers. If your trades live in TradeLocker but your analysis doesn’t, you’re flying blind. This guide walks beginners through the full process of exporting your trade history from TradeLocker and importing it into PipJournal — from raw CSV to tagged, analyzable data.

Step 1: Export Your Trade History from TradeLocker

Log into your TradeLocker account and navigate to the History tab in the bottom panel. By default, this shows your closed positions.

To export:

1. Set the date range to cover the period you want to analyze. For a first import, select the maximum available range (up to 90 days on most accounts, or the full account history if your broker allows it).
2. Click the Download or Export icon in the top-right corner of the History panel. TradeLocker exports as a .csv file.
3. Save the file with a recognizable name, such as tradelocker-history-2026-Q2.csv.

The exported file will include columns for: Order ID, Symbol, Type (buy/sell), Volume (lots), Open Price, Close Price, Open Time, Close Time, Commission, Swap, and Profit.

Step 2: Format the CSV for PipJournal

Open the downloaded CSV in a spreadsheet application (Excel, Google Sheets, or LibreOffice Calc) and check these three things:

1. Date format — TradeLocker exports timestamps as YYYY-MM-DD HH:MM:SS. PipJournal accepts this format natively, so no changes are needed.
2. Symbol format — Symbols appear as EURUSD, GBPJPY, etc. These match PipJournal’s pair format. If your broker uses non-standard suffixes (e.g., EURUSD.m), remove the suffix from the Symbol column using a find-and-replace.
3. Volume units — TradeLocker records volume in lots (e.g., 0.10 for a mini lot). Confirm this matches what you expect. A 10-pip move on 0.10 lots EURUSD should show roughly $10 in the Profit column.

Do not remove or reorder columns before importing. PipJournal’s column mapper handles the alignment automatically.

Step 3: Import the File into PipJournal

Inside PipJournal, go to Accounts and select the account you want to populate, or create a new one for this broker.

1. Click Import Trades and select CSV / Manual Import.
2. Upload your formatted TradeLocker CSV.
3. The column mapper will display a preview. Map each column to the corresponding PipJournal field:
   • Order ID → Trade ID
   • Symbol → Pair
   • Type → Direction
   • Volume → Lots
   • Open Price / Close Price → Entry / Exit
   • Open Time / Close Time → Entry Date / Exit Date
   • Commission + Swap → Fees (or map separately if you want to track them individually)
   • Profit → P&L
4. Click Confirm Import.

PipJournal will process the file and display a summary: number of trades imported, total pip gain/loss, and any rows skipped due to missing data.

Step 4: Verify the Imported Trades

Before you start analyzing, spend 2 minutes cross-checking the import. In TradeLocker, note:

• Total number of closed trades in the selected period
• Net profit/loss in account currency

Compare these against the summary shown in PipJournal after import. If the trade count matches but the P&L differs by more than 1%, the likely cause is commission or swap mapping. Check that both fee columns were included — excluding a $3–$6 round-trip commission per trade adds up quickly on high-frequency accounts.

If any trades are missing, check whether they fall outside the date range you exported.

Step 5: Tag and Categorize Your Trades

Raw imported trades have no context. Add it now so your analytics are useful from day one.

PipJournal’s bulk tag feature lets you apply tags to multiple trades at once. Prioritize these three dimensions:

• Setup type — e.g., breakout, pullback, range, news
• Session — london, new-york, asia, overlap
• Strategy — your specific system name or approach

Even if you only tag 80% of your trades, you’ll have enough data to run setup performance analysis within a week. Filtered analytics require at least 20–30 tagged trades per category to produce statistically meaningful win rates.

Pro Tips

• Export weekly rather than monthly. Smaller files are faster to review and easier to spot formatting issues before they compound.
• If your broker adds a suffix to symbol names (e.g., EURUSD.raw), create a find-and-replace rule in your spreadsheet and save it as a macro — you’ll use it every time.
• Map Commission and Swap as separate fields, not combined. This lets PipJournal show your gross P&L vs. net P&L, which is useful for evaluating whether spread costs are eating into a strategy’s edge.
• For prop firm accounts, create a separate PipJournal account per challenge phase. Mixing evaluation and funded phase data distorts your long-term statistics.
• After your first import, set a recurring reminder to export and import every Sunday. Staying current means your weekly trade review always has fresh data to work with.

Common Mistakes to Avoid

1. Importing only profitable months. Cherry-picking your history gives you flattering but useless analytics. Import your full account history, losses included, to get an honest baseline of your actual trading expectancy.

2. Skipping fee columns. Leaving out commission and swap understates your true cost per trade. On a 0.10 lot EURUSD trade with a $6 round-trip commission, a 6-pip win is actually breakeven. Map all fee fields.

3. Not verifying after import. Assuming the import is correct without checking trade counts and P&L against your broker statement is a common shortcut that leads to decisions based on bad data.

4. Using one account for multiple strategies. If you trade different systems on the same TradeLocker account, create separate PipJournal accounts or use strategy tags consistently — otherwise filtering by strategy becomes meaningless.

5. Delaying tagging. The longer you wait to add setup and session tags, the harder it becomes to remember why you took each trade. Tag on the same day you import.

How PipJournal Helps

PipJournal’s import wizard is built to handle real broker exports without manual reformatting for the most common platforms, including TradeLocker’s CSV structure. Once trades are imported, the analytics dashboard breaks down your performance by pair, session, setup tag, and day of week — so you move from raw data to actionable patterns in minutes. The trade log lets you add notes, screenshots, and ratings to individual trades, while the equity curve view shows whether your edge is holding or degrading over time. For traders running prop firm challenges on TradeLocker, PipJournal’s drawdown tracking keeps your daily and max drawdown visible at all times.