Free Tools

Binary Options Correlation Matrix Tool: See How Assets Move Together

Free correlation matrix calculator. Paste price or return series for several assets to see how closely they move together, and why correlated trades raise risk.

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Desk:Financial Research & Editorial Desk

Two trades on assets that move together are closer to one bet than two. This tool computes a correlation matrix from series you paste in, so you can see how much overlap your positions might have. You supply the data; the tool does not fetch prices.

Correlation Matrix

ABC
A1.000.96-0.97
B0.961.00-0.98
C-0.97-0.981.00

The matrix shows Pearson correlation: +1 means two series moved together, -1 opposite, 0 no linear link. The sample example above is made-up filler, not market data. Correlation changes over time and a short sample can be misleading, so use data from the same dates and a long enough window.

How to Use This Tool

  1. Paste one series per line in the form NAME: value, value, value, using the same dates for every series.
  2. Choose whether the values are prices or returns.
  3. Read the matrix: values near +1 move together, near -1 move in opposite directions, near 0 show little linear link.

How It Works

For prices the tool first converts each series to percentage changes, then calculates the Pearson correlation between every pair. Correlation changes over time, depends on the window you choose and can be distorted by a short sample. The example data shown is made-up filler to demonstrate the format. See the guide on correlation trading across assets for how traders use the idea.

Limits

This tool uses only the figures you enter. It does not know your broker, your fees or your market, and its output is not advice or a prediction. Test any plan on a demo account first, and read your platform's own terms.

Frequently Asked Questions

Where do I get the data?

From a charting platform or data source you trust. Use the same time period and interval for every series.

Does high correlation mean one will always follow the other?

No. It describes past co-movement, which can change.

Why convert prices to changes?

Prices that trend look correlated even when their moves are unrelated. Changes give a fairer comparison.