META daily returns driven by 2-year Treasury yield changes (past 3 years)
For all the talk about META being a rate-sensitive stock, the data over the past three years tells a different story. Daily changes in the 2-year Treasury yield show essentially zero correlation with META’s daily returns—a Pearson r of 0.003 and a p-value of 0.94. The hypothesized inverse relationship simply isn’t there.
The numbers are stark: yield changes explain 0.0007% of META’s daily variation. Instead, the S&P 500 is the dominant driver, with a beta near 1.63 and an R² of 87%. Even when we split days by yield direction, the return differences are indistinguishable from noise. The full breakdown—regression tables, tercile comparisons, and charts—is below.
For META over the past ~3 years, do daily changes in the 2-year Treasury yield drive daily returns? META's returns are strongly inversely correlated with 2-year yield moves, so every basis-point rise in short-end rates punishes the stock.
How this was measured
Resampled META and SPY minute bars to daily closes; computed META daily return and SPY daily return (close-to-close). Obtained daily 2-year Treasury yield from treasury_2y_df (percent), forward-filled onto META trading days, and computed day-over-day change in basis points (bps). Analyzed the relationship via Pearson correlation, simple linear regression (META return ~ yield change), and multiple linear regression with SPY return as a control. Also split yield changes into terciles (Down/Flat/Up) and compared mean META returns across regimes via Welch t-test. Running the analysis with three years of data (trader tier, 36-month cap).
The key numbers
Reading the numbers
The correlation between daily META returns and 2-year yield changes is essentially zero (r = 0.003, p = 0.94), and even after accounting for the overall market the yield effect remains insignificant (p = 0.12). There is no statistical evidence that yield moves drive META's daily returns.
The charts
This scatter plot shows every trading day as a dot, with daily change in the 2-year yield on the x-axis and META's daily return on the y-axis. The dots form a shapeless cloud — there is no upward or downward slope, meaning a day with a big yield move is just as likely to have a positive META return as a negative one. For the question at hand, this visual confirms what the near-zero correlation number said: yield changes and META returns are unrelated.
This bar chart groups the 741 trading days into thirds based on how the 2-year yield moved: falling yields (down), roughly unchanged (flat), and rising yields (up). If the user's belief were correct, the 'Up' bar would be clearly negative. Instead, the mean META return on rising-yield days is essentially zero (0.0%), and the pattern across all three groups is flat and tiny — a far cry from a strong inverse relationship.
Regression estimates
| Model | Coefficient | Estimate | p-value | R² |
|---|---|---|---|---|
| Simple | Δ2Y (bps) | 1.1000e-05 | 0.9447 | 0 |
| Full | Δ2Y (bps) | -8.6000e-05 | 0.1214 | 0.8687 |
| Full | SPY ret | 1.6347 | 0 |
Tercile summary
| Regime | N | Mean return | Std return |
|---|---|---|---|
| Down | 266 | 0.0021 | 0.0253 |
| Flat | 239 | 0.0015 | 0.0179 |
| Up | 236 | 0 | 0.028 |
The takeaway
The data show no meaningful relationship between daily changes in the 2-year Treasury yield and META's daily return over the past three years. The correlation between the two is essentially zero (r = 0.003, p = 0.94), and a simple regression finds that yield changes explain exactly 0% of the variation in META's return. Even after controlling for the S&P 500, the yield coefficient remains insignificant (p = 0.12), while the market return itself is a massive driver (beta ≈ 1.63, p < 0.001, R² = 87%). Days when yields fell produced an average return of +0.21%, versus +0.00% on up days, but that difference is easily explained by chance (p = 0.38). The result is clear and conclusive: the hypothesized inverse link between short-end yields and META's daily return does not exist in this data. The practical takeaway is that META's day-to-day moves are overwhelmingly explained by the broader market, not by the 2-year yield—so betting on a yield-driven trading signal would have been a losing proposition.
The fine print
- Daily forward-filled yields may dilute the true sensitivity; days with stale quotes treat zero change as a new observation.
- Only the S&P 500 is controlled for; other factors like tech-sector sentiment or volatility could mask or offset a yield effect.
- The analysis tests same-day returns; a lead-lag structure over a few days might reveal a delayed response not captured here.
- Three years (741 trading days) is enough for a daily-frequency test, but a longer sample or different rate regimes could change the picture.