The Dollar Index — DXY, sometimes USDX — is the thermometer of US dollar strength: a single number that rises when the dollar strengthens against the major currencies and falls when it weakens. Unlike individual currency pairs such as EUR/USD or USD/JPY, which show the dollar against one counterpart, the DXY shows it against a basket of six currencies at once, giving a snapshot of global dollar strength.
That makes it an essential tool for reading macro dollar trends, trading FX correlations — if the DXY rises, EUR/USD typically falls — anticipating moves in commodities, since gold and oil are inversely correlated with the dollar, and positioning around risk-off events, where flight to dollar safety pushes the index higher. This article covers how it is calculated, why the euro dominates the index with a 57.6% weight, and the limitations that a great many traders overlook entirely.
How the DXY Is Calculated
The DXY is a weighted geometric mean of six currency pairs. The components and their weights are: EUR 57.6%, JPY 13.6%, GBP 11.9%, CAD 9.1%, SEK 4.2% and CHF 3.6%. The formula is involved but the concept is simple: if the euro falls against the dollar, the DXY rises, because the euro is 57.6% of the index. If the yen falls against the dollar, the DXY also rises, but with far less impact — only 13.6%.
The base value is 100, set in March 1973 when the index was launched in the post-Bretton Woods period. A DXY of 110 today means the dollar is 10% stronger than its 1973 baseline against that basket. A DXY of 90 means it is 10% weaker. The historical extremes: the high was 164.72 in February 1985, during the Volcker Fed era with rates at extraordinary levels and remarkable dollar strength, and the low was 70.698 in March 2008, during the financial crisis before quantitative easing began.
The typical modern range has been roughly 90 to 105 over the 2010 to 2024 period. A breakout above 105 indicates extreme dollar strength — last seen during the aggressive Fed hiking cycle of 2022 and 2023. A breakdown below 90 indicates extreme dollar weakness, as in 2008, 2011 and the pre-recovery phase of 2020.
Why the Euro Weighs 57.6%: History and Distortion
The DXY was created in March 1973 with ten original currencies: the German mark, French franc, Italian lira, Dutch guilder and Belgian franc, plus the yen, sterling, Canadian dollar, Swedish krona and Swiss franc. The weights were based on US trade flows as they stood in 1973 — the commercial importance of each partner. Europe accounted for roughly 60% of US trade at the time, so European currencies dominated the index.
In 1999 the euro replaced the mark, the French franc, the lira, the guilder and the Belgian franc. The euro's weight simply became the sum of the weights of the currencies it absorbed: 57.6%. That creates a structural bias, because EUR/USD performance now dominates the entire index. If the euro rises 5% and every other currency is flat, the DXY falls by roughly 2.9% — that is 57.6% of 5%.
The modern criticism is straightforward: the basket does not reflect today's trade flows. China is among the largest trading partners of the United States, and the yuan is absent. Mexico is a top-three partner, and the peso is absent. The eurozone accounts for a far smaller share of US trade now than it did in 1973. Some economists argue for modernising the DXY to include the CNY, MXN and KRW, but ICE — the exchange that publishes the index — maintains the original basket for historical continuity.
DXY Versus EUR/USD: An Inverse Correlation Near -0.95
Because the euro is 57.6% of the index, EUR/USD movement drives the DXY in the opposite direction with a correlation close to -1.0. The mechanics: EUR/USD rises, meaning euro strength, so the DXY falls, because dollar weakness against the euro dominates. EUR/USD falls and the DXY rises. Historically the correlation has run between -0.92 and -0.97 — very nearly a perfect inverse.
The trading implication is useful. If you want to trade dollar strength but your broker does not offer the DXY, you can short EUR/USD, which is functionally close to being long the DXY. If you expect a bullish DXY breakout, watch EUR/USD for a confirming bearish breakdown.
Divergences are rare but informative. If the DXY rises while EUR/USD does not fall proportionally, it means the other currencies — the yen, sterling — are weakening faster than the euro. That signals not generalised dollar strength but relative euro strength against the other majors, which is a different trade entirely.
The DXY, Gold and Commodities
Gold and the DXY have a structural negative correlation, and the reason is partly mechanical: gold is priced in dollars, so when the dollar strengthens, gold becomes more expensive for non-dollar holders and demand falls. Gold also functions as an anti-dollar hedge — investors buy it as protection against dollar debasement, and when the dollar is strong that protection is less in demand. The historical correlation between XAU/USD and the DXY runs between -0.75 and -0.85.
There are exceptions during crises. In the COVID panic of March 2020, both the DXY and gold rose simultaneously, because both were functioning as safe havens in a flight to quality. The same happened in the early phase of the 2008 crisis. For trading purposes: if the DXY breaks out bullishly and gold does not fall, treat that as a warning sign that the correlation is breaking down. If the DXY breaks down bearishly and gold rallies strongly, you have confirmation.
Dollar-priced commodities are affected directly: a high DXY makes them more expensive for non-dollar buyers, demand falls, prices fall. Crude oil, both WTI and Brent, has a correlation with the DXY of roughly -0.40 to -0.60. Copper runs around -0.50 to -0.70. Agricultural commodities such as wheat and corn are weaker at roughly -0.30 to -0.50, because supply shocks dominate currency effects. Our guide to intermarket correlations covers these relationships in depth, and you can monitor the live figures on our forex correlation matrix.
Trading the DXY: Instruments and Strategies
Several instruments give exposure. ICE futures under the ticker DX have a contract size of $1,000 times the index value, and are liquid enough for hedging or speculation. CFDs on the DXY are offered by a number of FX brokers, typically with leverage of 20:1 to 30:1 and spreads of 2 to 5 points. ETFs provide a simpler route: UUP for long dollar exposure, UDN for the inverse. And as noted, shorting EUR/USD is an approximate proxy for a long DXY position.
A trend-following approach suits the index well, because the DXY tends to make multi-month and multi-year trends rather than choppy ones. The setup: identify the trend using the 50 and 200-period moving averages on the daily chart, then trade in that direction using pullbacks. For example, with the DXY in an uptrend, a pullback to the 50-period MA offers a long entry on the bounce, with the stop below the MA and the target a multiple of that risk. Our comparison of SMA, EMA and WMA covers which average suits this timeframe.
A second approach uses the DXY against the S&P 500, where the correlation varies by regime. In risk-on conditions the DXY falls while equities rise, with a correlation around -0.50 to -0.70. In risk-off conditions the DXY rises while equities fall, with a stronger correlation of -0.70 to -0.90. The setup: if the DXY breaks above 105 while the S&P is still near its highs, that divergence is a warning. The typical resolution is that equities follow the dollar lower as risk appetite deteriorates.
The DXY as a Leading Indicator of Fed Policy
Fed policy drives the DXY over the long run: a hawkish Fed raising rates produces a DXY rally, since higher yields attract capital, while a dovish Fed cutting rates or easing produces a decline. But the relationship also runs the other way. If the DXY rallies persistently while the Fed is still neutral, the market is pricing future tightening before the Fed has announced it.
The 2022 cycle illustrates this well. The DXY bottomed near 89 in January while the Fed was still describing inflation as transitory. The index rallied to around 95 by February, 100 by April and 105 by June — the market front-running a hawkish shift. The Fed then delivered 75 basis point hikes from June 2022, confirming what the dollar had been signalling for months.
The Limitations of the DXY
The basket is outdated. The weights reflect 1973 trade patterns rather than current ones, with China and Mexico entirely absent, and the euro overweighted at 57.6% relative to its real importance. There is a geographic bias: more than 75% of the weight sits on Europe and Japan, materially underrepresenting emerging Asia. It is not genuinely a global dollar index.
Alternatives exist. The Fed's broad dollar index is trade-weighted and includes the yuan and emerging market currencies, making it considerably more representative. The Bloomberg Dollar Index uses a more modern weighting. Sophisticated traders cross-check multiple dollar indices rather than over-relying on the single DXY number.
There is also a non-linearity worth understanding. Because the index is a geometric mean, large moves in one component have disproportionate impact. A 20% fall in EUR/USD moves the DXY by roughly 12 to 15%, whereas a 20% rise in USD/JPY moves it by only 2 to 3%. The euro's weight dominates everything else.
Why the DXY Still Matters
The DXY is a shortcut for answering the question is the dollar strong or weak? without monitoring six pairs separately. Its correlations with gold, commodities and equities make it useful across asset classes. And it functions as a leading indicator both of Fed policy and of global risk sentiment. Its limitations are real: the basket is outdated and it is not a perfect proxy for global dollar strength.
The practical approach is to use the DXY as a macro filter — establishing whether the dollar trend is bullish or bearish — then confirm with EUR/USD and cross-check the related correlations in gold and equities. It is not a holy grail, but for any serious FX trader it is close to indispensable. For the wider picture of how the dollar interacts with risk sentiment, our article on safe haven currencies covers the flows behind the moves.
