FINANCIAL STRESS VS. BITCOIN
Is the U.S. financial system under strain, and does that reach Bitcoin?
The financial stress index of the Federal Reserve Bank of St. Louis, which aggregates 18 measures including credit spreads, set against Bitcoin.
Financial Stress Index (St. Louis Fed)
-0.811
Bitcoin (USD)
US$ 80,241
Source: Coinbase Exchange
Loading the chart…
CorrelationA statistical measure of how much two series move together, ranging from -1 to +1.Why it matters: It allows relationships that look real to the naked eye to be compared objectively.How to read it: Close to +1: strong co-movement. Close to 0: little linear relationship. Close to -1: strong inverse movement.Common mistake: Calculating correlation on price levels instead of returns. Two series that only rise over the long run will produce a high correlation even with no real relationship — the classic spurious correlation.
-0.01
Little linear relationship between the two series over the observed period.
- Method
- Pearson
- Basis
- Returns
- Rolling window
- 180 days
- Effective frequency
- weekly
- Sample size
- 26 observations
- Historical mean
- -0.06
- Séries com frequências diferentes; a comparação foi feita na frequência mais baixa (semanal).
Near +1: strong co-movement. Near 0: little linear relationship. Near −1: strong inverse co-movement. In every case, correlation describes co-movement and does not establish cause and effect.
Lead-lagA technique of shifting one series in time to test whether it tends to move before the other.Why it matters: It helps distinguish which variable leads and which one reacts.How to read it: Look at the shape of the correlation-by-lag curve, not just the peak. An isolated peak surrounded by low values is usually noise.Common mistake: Testing dozens of lags and reporting only the best one. The more combinations you test, the higher the chance of finding one that looks good by pure chance.
Correlation recomputed with the first series shifted in time. Read the shape of the whole curve: an isolated peak surrounded by low values is almost always noise.
The highest correlation in absolute value appears at a lag of 8 weeks (0.66). The data suggests the first series moves ahead, but does not confirm it: testing many lags raises the chance of finding a high value by coincidence.
WHAT THE DATA SHOWS NOW
Sentences generated by deterministic rules over the numbers computed on this page. None of them is written by a language model. Open any item to see the formula and the values used.
The 180-day correlation between Stress and BTC stands at -0.01, a very weak association in opposite directions, measured on returns at weekly frequency with 26 observations. Correlation measures co-movement and does not establish that one series determines the other.
- Series:
- us-financial-stress, btc-usd
- Period:
- 09/03/2021 to 08/21/2026
- Formula:
- correlação de pearson sobre returns, janela de 180 dias
- Values:
- coeficiente=-0.0080 · amostra=26.0000 · metodo=pearson
Over the last 90 days the two series moved in opposite directions: Stress fell and BTC rose. Divergences of this kind are common and do not, on their own, indicate that either series is wrong.
- Series:
- us-financial-stress, btc-usd
- Period:
- 09/03/2021 to 08/21/2026
- Formula:
- sinal da variação de 90 dias de cada série
- Values:
- variacao_a=-0.0531 · variacao_b=6470.6100
Financial Stress Index (St. Louis Fed) stands at -0.8107 Index (0 = normal conditions) on 08/21/2026, a change of +7.01% from 05/22/2026.
- Series:
- us-financial-stress
- Period:
- 09/03/2021 to 08/21/2026
- Formula:
- (valor atual ÷ valor de ~90 dias atrás) − 1
- Values:
- atual=-0.8107 · data_atual=2026-08-21 · anterior=-0.7576 · data_anterior=2026-05-22
Bitcoin (USD) stands at 80,241.3000 US$ on 08/28/2026, a change of +8.77% from 05/30/2026.
- Series:
- btc-usd
- Period:
- 08/28/2021 to 08/28/2026
- Formula:
- (valor atual ÷ valor de ~90 dias atrás) − 1
- Values:
- atual=80241.3000 · data_atual=2026-08-28 · anterior=73770.6900 · data_anterior=2026-05-30
What this chart measures
A composite measure of strain in the U.S. financial system, built from interest rates, credit spreads and volatility indicators.
Why this relationship matters
It is the public-domain version of the credit stress question, and it covers more dimensions than any single spread. Zero represents normal conditions.
How to read it
Values above zero indicate stress above the historical average. Rapid moves matter more than the level.
When this relationship tends to hold
During banking crises and episodes of liquidity tightening, when the index rises quickly and broadly.
When it can break down
It is a weekly, composite index, and therefore slow. It is not suited to short-term reading of the market.
Limitations
Composite indices hide which component is driving the move. For diagnosis, you have to open up the subcomponents.
SOURCE AND METHODOLOGY
FRED series STLFSI4, weekly, with Friday data. Correlation on the first difference of the index and on the logarithmic return of Bitcoin, at weekly frequency.
- Financial Stress Index (St. Louis Fed)
- Federal Reserve Bank of St. Louis via FRED · Index (0 = normal conditions) · weekly
Licence: Domínio público (dado do governo dos EUA)
View at the original source - Bitcoin (USD)
- Coinbase Exchange · USD · daily
Licence: Dados públicos de mercado da Coinbase Exchange
View at the original source
CorrelationA statistical measure of how much two series move together, ranging from -1 to +1.Why it matters: It allows relationships that look real to the naked eye to be compared objectively.How to read it: Close to +1: strong co-movement. Close to 0: little linear relationship. Close to -1: strong inverse movement.Common mistake: Calculating correlation on price levels instead of returns. Two series that only rise over the long run will produce a high correlation even with no real relationship — the classic spurious correlation. measures co-movement and does not establish CausalityA relationship in which one variable actually brings about the change in another.Why it matters: It is what most people actually want to know, and it is what correlation does NOT answer.How to read it: Establishing causality requires theory, experiment, or statistical identification — it is not enough to observe two lines rising together.Common mistake: Concluding that A causes B because the correlation is high. Often a third factor moves both, or the relationship is a coincidence of the chosen period.. The relationship shown depends on the macroeconomic regime and may weaken or disappear.