Forex Data Quality Checklist: What to Look For

Most traders spend all their time looking for the "perfect" indicator, but they never stop to check if the data they are feeding that indicator is accurate. If you are using low-quality data, your indicators are lying to you. Professional traders know that forex data quality is the most important part of the entire trading stack. Whether you are building a bot or trading manually, you need to be sure your source is reliable.

So, how do you verify a dataset? At historicalforexprices.com, we provide 25 years of data across 66 currency pairs that have been cleaned and verified. But if you are looking elsewhere, here is the checklist you should follow.

1. Missing Gaps and "Ghost" Candles

The biggest red flag in forex data quality is missing time. Check your M1 data for gaps during active market hours. While the market closes on weekends, it should be continuous from Sunday afternoon to Friday evening. If you see chunks of 15 or 30 minutes missing on a Tuesday, the dataset is garbage. Your backtester will "jump" over those gaps, giving you a completely unrealistic result.

2. Price Spikes and Bad Prints

Sometimes, a data feed will record a price that never actually happened - a "bad print." If you see a candle with a tail that is 500 pips long in a pair that usually moves 50 pips, that's a data error. A high-quality source like historicalforexprices.com filters these out to ensure your stop-loss simulations aren't triggered by non-existent price movements.

3. Consistency Across Multiple Pairs

If you are analyzing 66 currency pairs, the time stamps must align perfectly. If EUR/USD says it's 12:01 and GBP/USD says it's 12:02, your correlation analysis will be broken. Professional datasets ensure that all pairs are synced to a single master clock (usually GMT or New York Close).

4. The "New York Close" Standard

Speaking of clocks, the industry standard for daily bars is the New York Close (5 PM EST). If your data provider uses a different midnight, you will have "Sunday candles" that distort your moving averages and RSI levels. Always ensure your data follows the New York Close to match the charts used by the world's biggest banks.

Summary Checklist

Are there missing minutes during the week?
Are there unrealistic price spikes?
Does it use 5-digit pricing (fractional pips)?
Is it 25 years of data or just a few years?
Is the GMT offset consistent?

By using a trusted source like historicalforexprices.com, you can skip the cleaning process and get straight to the trading. Quality data is an investment, not an expense.