Sample forex data
audit report
This example shows the kind of report a paid dataset audit can produce: a practical score, file-level checks, gap samples, and repair actions a trader or developer can use before trusting a backtest. For the full failure pattern, read why forex backtests fail.
Example Result
Backtest-readiness score from a deliberately flawed EURUSD M1 fixture.
Executive findings
The audit is designed to surface issues that can distort strategy results: duplicated bars, bad candles, timestamp ordering, and hidden missing intervals.
1 duplicate timestamp.
1 out-of-order timestamp.
2 invalid OHLC rows.
1 non-positive price row.
1 negative volume value.
1 unexpected M1 gap.
1 large close-to-close jump.
1 large candle range.
File-level audit
| Symbol | EURUSD |
|---|---|
| Timeframe | M1 |
| Date range | 2024-01-01 00:00 to 2024-01-01 00:07 UTC |
| Duplicate timestamps | 1 |
| Invalid OHLC rows | 2 |
| Unexpected gaps | 1 |
Gap sample
EURUSD M1
Approximate missing bars: 2. A real customer report would include more samples and a repair recommendation tied to the source and session model.
Recommended actions
A useful audit does more than say the file is bad. It tells the buyer what must be cleaned, what must be sourced, and what assumptions still need human confirmation.
Create a cleaned copy with canonical columns: timestamp, open, high, low, close, volume.
Dedupe timestamps using a documented source-precedence rule.
Normalize timestamp ordering before calculating gaps or candle features.
Repair or quarantine invalid OHLC rows before running strategy tests.
Preserve the raw file and a repair log so every change can be reproduced.
Need this for your own data?
Start with scope or buy the starter audit. We review the symbols, range, source, and intended use before requesting raw files.