What is the Pearson correlation coefficient?

It is a number between -1 and +1 that measures the linear relationship between two data series. +1 means perfect positive correlation, -1 means perfect inverse correlation, and 0 means no linear relationship.

How many data points do I need?

At least 5 are required for a meaningful result. Statisticians typically recommend 20–30 or more for reliable forex correlation estimates. The tool accepts up to 500 values per series.

Should I use price levels or returns?

Both are acceptable inputs. Price levels often show high correlation simply because both series trend together, while log-returns reveal whether the day-to-day movements are correlated — which is usually more useful for trading.

What counts as a strong correlation?

A common rule of thumb: |r| ≥ 0.8 is strong, 0.5–0.8 is moderate, 0.3–0.5 is weak, and below 0.3 is negligible. These thresholds are guidelines — context and sample size matter.

Does this tool store my data?

No. All computation happens in your browser. No data is sent to any server.

Can I use bid prices, mid prices, or ask prices?

Yes — use whichever price is consistent across both series. Mid or close prices from the same broker feed are most common for correlation studies.

Currency Correlation Helper

Name: Currency Correlation Helper
Availability: InStock
Author: Nham Vu

Paste two forex price series and instantly see their Pearson correlation coefficient to gauge how closely the pairs move together.

Price Series Input

Pair A label (optional)

Pair A prices (one number per line)

Pair B label (optional)

Pair B prices (one number per line)

Enter price series for both pairs and click Calculate.

EUR/USD vs GBP/USD

—

Pearson correlation coefficient (r)

-10+1

Descriptive Statistics

Metric	Pair A	Pair B

Scatter Plot

Copied!

Summary

Paste two forex price series and instantly see their Pearson correlation coefficient to gauge how closely the pairs move together.

How it works

Enter one closing price per line for Pair A (e.g. EUR/USD daily closes).
Enter the matching price series for Pair B — same number of values, same time order.
Click "Calculate Correlation" to compute the Pearson r coefficient.
Read the coefficient and the plain-English interpretation shown below the result.
Adjust your series, remove outliers, or swap pairs and recalculate instantly.

Use cases

Identify highly correlated pairs to avoid doubling risk on the same directional trade.
Find negatively correlated pairs to construct simple hedges.
Compare correlation across different timeframes (daily vs weekly closes).
Screen pairs before building a multi-currency portfolio to ensure diversification.
Verify that a safe-haven pair (e.g. USD/CHF) truly offsets a risk-on pair in your book.
Back-test whether a historical correlation has held stable over recent sessions.

Frequently Asked Questions

Last updated: 2026-06-09 · Reviewed by Nham Vu