Macro Workspace
Build your own chart stack, switch transforms, and share the exact view by URL without locking in one interpretation.
Build Your Stack
Add series by country or indicator, then change transforms until the comparison reads the way you want.
Examples: US CPI, Japan policy rate, S&P 500
Comparison Chart
Auto Notes
A mechanical read on the latest moves and how the selected series are lining up.
- United States / S&P 500 Index on a 100=base basis moved from 334.0 in 2026/02 to 327.2 in 2026/03, roughly flat.
- United States / Consumer Price Index (US) on a YoY % basis moved from +2.7% in 2025/12 to +2.4% in 2026/01, tilted lower.
- United States / Federal Funds Rate on a level basis moved from 3.64 in 2026/01 to 3.64 in 2026/02, roughly flat.
How The Pairing Reads
Use only the shared window and check which combinations line up most cleanly.
Across the shared 1954/07-2026/01 window, the pair is moving together with a correlation of +0.71. The cleanest alignment comes from best aligned with no lag.
Across the shared 2016/03-2026/02 window, the pair is moving together with a correlation of +0.63. The cleanest alignment comes from United States / Federal Funds Rate leading by 3 months.
Across the shared 2016/03-2026/01 window, the pair is leaning together with a correlation of +0.31. The cleanest alignment comes from United States / S&P 500 Index leading by 3 months.
Next Print Guide
A mechanical guide rail built from the latest five points. Use it to judge how far the next update deviates from trend.
Using the latest 5 observations, the mechanical read for the next print (2026/04) is around 329.9, with a roughly flat bias versus the latest print.
Using the latest 5 observations, the mechanical read for the next print (2026/02) is around +2.3%, with a roughly flat bias versus the latest print.
Using the latest 5 observations, the mechanical read for the next print (2026/03) is around 3.45, with a tilted lower bias versus the latest print.
The chart does not force a conclusion. Share the exact setup by URL, and try a transform before reading too much into raw annual levels.