Data Analysis
Explore how macroeconomic conditions relate to cryptocurrency adoption. Below you’ll find time series, correlation analysis, driver importance, and directional accuracy—all from our research model.
Adoption vs Economic Anxiety Over Time
Monthly Adoption Index (blue) and Economic Anxiety Index (orange) from 2019 to 2025. When economic anxiety rises—driven by inflation fears, monetary expansion, or recession signals—crypto adoption tends to move in the same direction.
Correlation Analysis
0.67
< 0.0001
≈ 0.49
About 49% of adoption variance is explained by economic conditions. Points are colored by year (lighter = earlier) to show how the relationship holds over time.
What Drives Adoption?
1. M2 Money Supply
Monetary expansion (M2 growth) is the strongest predictor. When central banks expand the money supply, concerns about debasement tend to rise and adoption follows.
2. Inflation Expectations
Breakeven inflation (e.g. T5YIE, T10YIE) captures fear of rising prices. Higher inflation expectations correlate with stronger adoption.
3. Recession Fears
Yield curve and sentiment indicators reflect recession risk. When recession fears increase, adoption tends to move in step.
Top Features vs. Adoption Index Over Time
Monthly intensity of each macroeconomic volatility feature (2020–2025), with the Adoption Index shown below. Each row is independently normalized — darker color means higher intensity for that feature. Hover any cell for the exact value.
Top 3 vs. Top 5 Factor Model
We tested two model configurations. Adding more factors improves directional accuracy but reduces correlation strength — a classic bias-variance tradeoff.
Top 3 Factors
Higher r- 1Inflation Fear
- 2Monetary Debasement
- 3Recession Fear
Pearson r
0.67
Directional Acc.
~42%
Strongest correlation with crypto adoption, but directional accuracy falls below chance — smooth macro signals struggle to predict volatile crypto movements.
Top 5 Factors
Better accuracy- 1Inflation Fear
- 2Monetary Debasement
- 3Recession Fear
- 4Financial Stress
- 5Negative Real Yield
Pearson r
0.64
Directional Acc.
65%
Slightly lower correlation but meaningfully better directional accuracy. The two extra factors add useful signal for predicting the direction of crypto adoption changes.
Final model choice: Top 5 — 65% directional accuracy on out-of-sample data (2024–2025) using macro data only, with no adoption lag inputs.
Directional Accuracy
65% of the time, when the Economic Anxiety Index rises, adoption follows.
This is better than random (50%) but not a crystal ball. We report it honestly: the model captures a real signal from macro conditions to adoption, but one-third of the time the direction is wrong.