AI Research JPMmacro:treasury_10y

JPM daily returns vs 10-year Treasury yield changes (last ~3 years)

The simple textbook claim — that banks “win” on days the 10‑year yield rises — doesn’t hold up cleanly for JPM when you look at daily moves over the past ~3 years. I compared JPM’s close-to-close returns on days the 10‑year rose versus fell and found average returns of +0.1568% on yield-up days versus +0.0644% on yield-down days; that raw gap is small and not statistically robust.

A linear fit and correlation tests show a positive but vanishingly weak relationship that explains almost none of daily return variance; one metric nudges toward significance while others are essentially null. Below you’ll find the full methodology, charts, and statistics that unpack why this is at best a negligible, inconsistent rate signal for JPM on a day-to-day basis.

The research question

For JPM over the past ~3 years, do trading days when the 10-year Treasury yield rises actually deliver stronger returns than days the yield falls — the textbook 'banks win when rates climb' belief? Thesis: JPM's daily returns show essentially no reliable link to the direction or magnitude of daily 10-year yield moves, debunking the idea that the stock is a clean bet on higher rates.

How this was measured

Resampled JPM minute bars to daily close-to-close returns. Reindexed the Treasury 10-year yield onto JPM's trading-day calendar with forward-fill and computed daily yield changes in basis points. Compared JPM returns on yield-up vs yield-down days (Welch two-sample t-test) and quantified linear association via OLS slope and Pearson/Spearman correlations. Flat (0 bp) days were excluded from the up/down buckets but counted for overall coverage.

The key numbers

Trading days analyzed
724
339 yield-up, 341 yield-down, 44 flat (0 bp)
Mean JPM return — yield-up days
0.1568%
N=339
Mean JPM return — yield-down days
0.0644%
N=341
Mean difference (up − down)
0.0924%
Two-sided; p=0.4159 ≥ 0.05 → no statistically-clear mean difference
Welch t-stat (up vs down)
0.814
Positive favors yield-up days
Pearson r (ret vs Δ10y bp)
0.093
|r|=0.093 ≤ 0.3 → weak association
Pearson p-value
0.0121
Two-sided
Slope: return per +10 bp Δ10y
0.2412%
OLS on daily data; sign>0 implies higher rates → higher JPM return
R² (linear fit)
0.0087
Explained variance by Δ10y(bp)
Spearman ρ (rank)
0.005
Rank correlation; robust to outliers
Spearman p-value
0.8894
Two-sided

Reading the numbers

Across 724 trading days (339 up, 341 down), JPM averaged 0.001568 on yield-up days vs 0.000644 on yield-down days — a tiny mean gap of 0.0009236 that is not statistically clear (two-sided p=0.4159).

The charts

JPM daily returns by 10y-yield direction
What this chart says

The box plot shows large overlap between the return distributions on yield-up (n=339) and yield-down (n=341) days: means are 0.0016 versus 0.0006 and the central clouds clearly intersect. Note the extreme positive outlier on yield-up days (max 0.1047) and the deeper negative tail on yield-down days (min -0.0732), but those are isolated. The small difference in the group means is not backed up by a clear statistical separation (see p=0.4159), so the plot supports the idea that direction alone doesn't deliver a reliable payoff.

JPM daily return vs change in 10y Treasury yield (bp)
What this chart says

The scatter covers Δ10y from -19 to +19 bp with JPM returns spread vertically and no tight line: Pearson r ≈ 0.093 indicates a very weak linear link, even though the p-value is 0.012. The OLS slope is 0.0024125 per +10 bp (roughly a +0.24 percentage-point change in return for a 10 bp rise), but R² is only 0.0087, meaning the yield move explains under 1% of return variability. A rank check (Spearman ρ ≈ 0.005, p=0.889) further shows no robust monotonic relationship once outliers and ordering are considered.

Mean JPM return on yield-up vs yield-down days
What this chart says

This bar chart simply highlights the tiny mean gap: mean return 0.0016 on yield-up days versus 0.0006 on yield-down days. The raw difference (0.0009236) is visible here but small in absolute terms and, as the tests show, not statistically clear (two-sided p=0.4159). So the visual mean advantage on up days is real in number but not reliable enough to support a clean ‘‘banks win when rates climb’’ claim.

Directional return summary (JPM on yield-up vs yield-down days)

directionNmeanmedianstd
Yield up3390.00160.00170.0145
Yield down3410.00060.00180.0151

The takeaway

No — over the past ~3 years JPM does not show a reliable day-to-day win when the 10-year yield rises. On average JPM returned +0.16% on yield-up days (N=339) versus +0.06% on yield-down days (N=341), a raw mean difference of +0.092% that is not statistically significant (two-sided p ≈ 0.416). A simple linear fit gives a positive slope (~+0.241% per +10 bp) and Pearson r = 0.093 (Pearson p ≈ 0.012), but that relationship explains under 1% of daily return variance (R² ≈ 0.0087) and the rank test is essentially null (Spearman ρ ≈ 0.005, p ≈ 0.889). Put plainly: one test (Pearson) flags a tiny correlation that large sample size can make “statistically significant,” while other tests and the mean-difference t-test do not support a meaningful effect. This is at best a very weak, practically negligible signal, not a clean or actionable rate-driven payoff for JPM on a daily basis. In short: don’t treat JPM as a simple long-on-rates trade based on daily 10y moves — other factors dominate.

The fine print