How to Import HFM (HotForex) Trades into PipJournal

HFM (formerly HotForex) is one of the most widely used forex brokers globally, particularly across Africa, the Middle East, and Southeast Asia. If your trades are sitting in an HFM account with no structured analysis, this guide shows you how to get that history into PipJournal in under 10 minutes.

This guide is written for beginner to intermediate traders who are setting up their journal for the first time or migrating from a spreadsheet.

Step 1: Export Your Trade History from HFM

HFM offers two export paths depending on your preference: the MyHFM client portal or the MetaTrader platform itself.

Via MyHFM Client Portal:

1. Log in at myhfm.com and navigate to My Accounts.
2. Select the account you want to export, then go to Trade History or Account Statement.
3. Set your date range — for a full history, set the start date to your account opening date.
4. Download the statement. The portal exports an HTML file formatted as a MetaTrader detailed statement.

Via MetaTrader 4 or MT5:

1. Open MT4 or MT5 and go to View > Terminal (or press Ctrl+T).
2. Click the Account History tab.
3. Right-click anywhere in the history panel and select Save as Detailed Report.
4. Save the file as HTML to your desktop.

Both methods produce an MT4/MT5-compatible HTML statement that PipJournal can read directly. If your account runs MT5, the column structure differs slightly — PipJournal handles both formats automatically.

Step 2: Format the Statement for Import

Before uploading, do a quick check to confirm the file is usable:

• Open the HTML file in a browser. You should see a table with columns including Time, Type, Size, Item, Price, S/L, T/P, Profit, and Balance.
• If the table is empty or shows only open positions, you exported a snapshot rather than a history. Repeat Step 1 and ensure you selected Detailed report, not Summary.
• Check that the file size is reasonable — a 6-month history for an active trader typically runs 200–800 KB. A near-empty file (under 10 KB) usually means the date range was too narrow.

No manual reformatting is required. PipJournal’s parser reads the raw MetaTrader HTML output and extracts all closed trades, including entry time, exit time, lot size, instrument, commission, swap, and net P&L.

Step 3: Import the File into PipJournal

1. Log in to your PipJournal account and navigate to Import Trades.
2. Select HFM / HotForex from the broker dropdown, or choose MetaTrader 4 or MetaTrader 5 if your specific account type isn’t listed — the format is identical.
3. Upload the HTML statement file.
4. PipJournal will display a preview showing the number of trades detected, the date range, and a sample of the first five trades. Verify these match your expectations — for example, if you ran 120 trades in the last quarter, the preview should show roughly 120 records.
5. If the count looks correct, click Confirm Import. Duplicate detection runs automatically, so re-importing an overlapping date range won’t create duplicate entries.

Typical import time is under 30 seconds for files covering up to 2 years of history.

Step 4: Tag and Categorize Imported Trades

Raw imported trades contain execution data (entry, exit, P&L) but no context. To get value from PipJournal’s analytics, add at least two layers of metadata:

Strategy tags — label each trade with the setup you used (e.g., London breakout, supply-demand, news fade). This enables tag-filtered performance breakdowns so you can see which setups are profitable and which are net-negative.

Session tags — mark trades as London, New York, or Asian session. If you’ve ever wondered whether your losing trades cluster in a specific session, this is how you find out. Many HFM traders operating from Africa or Asia find their worst P&L comes from holding positions through the New York close — this only becomes visible once trades are tagged.

Risk notes — if you know your risk per trade (e.g., 1% of $5,000 = $50), add it to the trade record. PipJournal calculates your R-multiple automatically once risk is defined, turning raw pip values into a standardized performance metric.

For a structured approach to reviewing your data after import, see the weekly trade review process.

Pro Tips

• If you trade multiple HFM account types (Standard, Premium, Zero Spread), import each as a separate PipJournal account. Mixing account types in one import distorts your commission-adjusted P&L analysis.
• HFM’s swap charges appear as separate line items in the MT4 statement. PipJournal includes these in net P&L automatically — don’t subtract them manually before importing.
• For accounts with more than 3 years of history, split the export into two date ranges and import sequentially. Very large HTML files (above 5 MB) occasionally time out on upload.
• HFM labels gold as XAUUSD and oil as USOIL — both are recognized natively by PipJournal without remapping.
• After import, run the equity curve report first. It gives you an immediate visual of whether your account has been growing consistently or recovering from periodic drawdowns.

Common Mistakes to Avoid

1. Exporting a Summary instead of a Detailed report. The Summary view shows aggregate P&L but doesn’t include individual trades. PipJournal needs the Detailed report with one row per closed position.

2. Using the wrong date range. Setting the end date to “today” but the start date to only 30 days ago means you’ll miss historical data. Export your full account history on first import, then use incremental exports (last 30 days) for ongoing updates.

3. Importing open trades. MT4/MT5 detailed reports may include open positions at the bottom of the file. PipJournal filters these out, but verify your import count matches only your closed trade count to avoid confusion.

4. Skipping the tagging step. Imported trades without tags produce generic reports. The real value — identifying your best setup, your worst session, or your overtrading patterns — only surfaces when trades are categorized. Even rough tags applied in bulk are better than none.

5. Not verifying pip values after import. HFM uses standard lot sizes (1 lot = 100,000 units). If your lot sizes look unusual after import (e.g., 0.0001 instead of 0.01), check whether you exported from a micro or cent account, which scales position sizes differently.

How PipJournal Helps

PipJournal was built for forex traders using brokers like HFM, so the MetaTrader import process is optimized for zero manual reformatting. Once your trades are in, the analytics dashboard automatically calculates your expectancy, win rate, average R:R, and drawdown — metrics that are impossible to track reliably in a spreadsheet across hundreds of trades. The tag filtering system lets you isolate performance by setup, session, or instrument, so you can stop guessing which part of your trading is working and start acting on data. For traders managing multiple HFM accounts — for example, a personal account alongside a prop firm evaluation — PipJournal’s multi-account view keeps everything in one place without mixing the data.