Borders and distance mean little when it comes to how stock markets react.
A rough day on Wall Street can echo in Europe the next morning and ripple into Asia by the evening. This chain reaction isn’t random, it’s called correlation, and it explains why traders keep one eye on global headlines even when trading a local stock.
Let’s explore how the US, Europe, and Asia move together.
When traders talk about correlation, they’re describing how closely two markets move in relation to each other. If two stock indices rise and fall together most of the time, they have a positive correlation. If one tends to go up when the other goes down, that’s a negative correlation. And if their movements seem unrelated, the correlation is close to zero.
To put numbers on it, it is measured on a scale between –1 and +1:
In practice, you’ll rarely see perfect matches. For example, the S&P 500 and the Nasdaq 100 usually present a strong positive correlation, but not every single move is identical. On the other hand, US tech stocks and gold often show weaker or even negative correlation because investors treat them very differently depending on whether they feel like taking risk or avoiding it.
The key point is this relationship cannot be defined with a math formula. Better we dive into types of correlation to explain how they work in practice.
Covariance tells you whether two markets tend to move together or apart, but it keeps the units of the data. That means a high covariance between the S&P 500 and DAX can partly reflect their volatility and price scales, not just the strength of their relationship.
Pearson correlation standardizes covariance, giving a unitless number between −1 and +1. Traders prefer it because you can compare relationships across very different assets. Keep in mind both measures are sensitive to outliers and big volatility spikes, so check your data range before drawing conclusions.
Static correlation measures the relationship between two assets over a fixed period, like last year. It is simple and clean, yet it can hide regime changes. Two indices might look tightly linked on a one-year average even if they diverged for months at a time.
Rolling correlation measures the relationship over a moving window, such as 20, 60, or 120 trading days. It helps you see when markets tighten up during stress or loosen during calm periods. Pick a window that matches your trading horizon, and remember shorter windows react faster but can be noisy, while longer windows are smoother but slower to warn you of shifts.
Markets might move closely together for months, then suddenly break apart. So, it’s never fixed. To avoid false assumptions and adapt your strategies in time, you should accept this reality.
Interest rates, inflation, and the strength of the US dollar are some of the biggest forces behind correlation changes. For example, when global central banks tighten policy at the same time, stock markets across regions often fall in sync.
In calmer markets, local drivers like company earnings or sector news tend to set the tone. When volatility picks up and the VIX spikes, stock indices across regions often move in the same direction.
In the US, a handful of mega-cap tech firms dominate the S&P 500, so their earnings can drive the entire index. Europe’s indices, on the other hand, lean more on banks and industrials.
Because each market has a different sector mix, their movements can shift depending on what drives prices at the time. For example, a surge in oil might lift European energy companies while putting pressure on US consumer stocks.
Shocks like financial crises, new tariffs, or geopolitical conflicts can push correlations unexpectedly higher. Investors worldwide may sell risk assets together, regardless of region, in a “flight to safety.” But contagion isn’t always permanent. Once the shock fades, markets often diverge once again as regional themes regain importance.
A recent example is the 2025 Trump tariffs, which sent a shockwave through equities from Asia to Europe as worries over global trade spread quickly. Markets moved lower in unison at first, but later started to show differences again as regional policies and sector drivers took over.
Stock markets are interconnected. Since trading sessions roll from Asia to Europe to the US and back again, price action often “hands off” from one region to the next. This follow-the-sun effect is why traders wake up to futures already in motion before their local market opens.
If US stocks finish sharply lower, European markets often open weaker, and Asian markets later absorb that sentiment. The same happens in reverse when Asia experiences a shock; Europe and the US take notice in their next sessions.
The busiest overlaps are when London and New York trade at the same time. That four-hour window typically sees the highest liquidity and the strongest cross-market reactions. In equities, U.S. futures can influence European indices before Wall Street opens, while moves in currency and bond markets add further momentum.
On August 5, 2025, the Nasdaq 100 dropped nearly 3% after renewed tariff announcements targeted Asian tech imports. When Tokyo opened the following day, the Nikkei 225 fell more than 2%, with heavy selling in chipmakers like Tokyo Electron and Advantest. Later in the morning, the weakness spilled into Europe’s STOXX 600 technology sector, which slid about 1.5%.
This shows how a single US event can cascade across Asia and then into Europe within a 24-hour cycle.
Markets react to more than just headlines, they also move with the overall mood of investors. Traders often call this risk-on or risk-off. These shifts can make global equities move more closely together or drift apart.
In a risk-on mood, investors feel confident about growth, earnings, or central bank support. Equities usually rise together, and correlations across regions climb as capital flows into stock markets broadly. Tech stocks, small caps, and emerging markets often benefit the most.
In a risk-off phase, uncertainty takes over. Investors may worry about tariffs, political instability, or weak data, and they start cutting equity exposure worldwide. This is when you’ll often see the S&P 500, DAX, and Nikkei all drop in sync, while demand shifts into safer assets.
Classic safe havens include the US dollar, Japanese yen, Swiss franc, US Treasuries, and gold. For instance, in July 2025, when tariff headlines triggered another wave of selling, the S&P 500 lost about 1.8% in a day, while gold futures climbed nearly 2% and USD/JPY dropped from 158 to 155 as traders rushed into the yen.
Moves like this prove how equity correlations tighten under stress and how capital simultaneously seeks safety elsewhere.
Different stock markets often move in different ways because each region has its own structure and its own drivers on prices.
The US often sets the tone for global equities. The S&P 500 is heavily influenced by mega-cap tech companies like Apple, Microsoft, and Nvidia, so earnings or policy shifts in that sector can ripple worldwide.
Federal Reserve decisions also carry global weight when the Fed hints at cutting or raising rates, you’ll see equity futures across Europe and Asia react within minutes.
European indices such as the DAX and STOXX 600 are more exposed to industrials, autos, and banks. This means they can react differently to moves in commodities, energy prices, or European Central Bank policy.
For example, when oil surged in early 2025, European energy companies helped the STOXX 600 outperform US peers for a short period.
Asia’s markets, including the Nikkei 225, Hang Seng, and CSI 300, are closely tied to currency flows and global trade. Japanese stocks often move in the opposite direction of the yen: when USD/JPY falls sharply, exporters in Tokyo usually drop as well.
Meanwhile, Chinese equities are sensitive to government policy shifts and trade relations. In 2025, new US tariffs on Chinese tech goods led to double-digit weekly losses in some Shenzhen-listed chipmakers, which in turn weighed on Hong Kong’s Hang Seng Index.
In August 2025, renewed tariff measures from the Trump administration triggered a sharp global selloff. The Nasdaq 100 fell nearly 3% in a single day, and the move echoed across Asia with the Nikkei 225 dropping over 2% and the Hang Seng losing 1.8%. Europe followed with the DAX sliding 2.1% the next morning.
During that week, rolling correlations between the S&P 500 and major Asian indices climbed above 0.8, showing how quickly global equities can move in lockstep under stress.
In contrast, the global AI boom earlier in 2025 showed how positive sentiment can also tighten correlations. Strong earnings from Nvidia and Microsoft lifted the Nasdaq to record highs, while demand for semiconductors spread into Taiwan’s TSMC and Japan’s Tokyo Electron, both posting double-digit monthly gains.
Europe’s ASML surged as well, pulling the STOXX 600 technology sector higher. In this case, optimism about artificial intelligence linked equity markets across regions in a synchronized rally.
You don’t need advanced software to check correlations. With basic tools like Excel, Google Sheets, or a trading platform that supports data exports, you can calculate it.
Step-by-step process
Things to keep in mind
Knowing that markets move together (or apart) is useful, but the real edge comes from turning those insights into strategies.
Trader “William Butcher” is watching tech stocks in the US and Europe. He notices a strong rally in the Nasdaq-100 after the Fed cut rates by 25 basis points and renewed optimism around semiconductors and AI.
Reuters reported that European tech stocks also rose ~2.1% on that same day, leading the STOXX 600 tech sector higher after a stretch of losses.
William’s observation: when Nasdaq leads strongly, European tech follows with a certain delay. He picks one European tech stock for his trade: ASML (ASML-NL), which recently posted strong quotes and bookings and jumped ~11.2% on earnings, helping the STOXX 600 tech sector to its record highs in late January 2025.
|
Parameter |
Value |
|---|---|
| Trader | William Butcher |
| Base account balance | USD 50,000 |
| Instrument | Long position on ASML (European tech stock) via CFD or equity |
| Signal | After Nasdaq-100 rallies ~1-2% on rate-cut optimism, and STOXX 600 tech is up ~2.1% same day, indicating correlated strength. |
| Entry price | Assume ASML is trading at €700 per share (for example) |
| Expected move | Target gain of ~8-10% over 2-3 weeks (as tech momentum transfers) |
| Stop loss | ~4% below entry (to limit downside if correlation breaks) |
| Position size | Uses 10:1 leverage (so his total exposure is 10× used capital) |
| Used equity for position | $5,000 margin, giving exposure of $50,000 equivalent in ASML shares |
Before trade: Account balance = $50,000
William opens leveraged long on ASML, margin used $5,000 with 10:1 leverage; exposure = $50,000.
If ASML drops 4% (stop loss) → he loses ~4% × exposure = $2,000. With margin he loses that amount from used capital; new balance ~ $48,000.
What Makes This Trade Work
Correlation is a useful guide, but it’s not a crystal ball. Traders often get caught by assuming relationships are fixed, when they shift with sentiment, policy, and events. Keep these common pitfalls in mind:
What does a correlation of +1 mean?
It means two markets move in the same direction at the same time.
Can correlation tell me which stock will go up next?
No, correlation shows how markets move together, not which one will lead.
Why should I care about global correlations if I only trade US stocks?
Because overseas events often move US futures before Wall Street even opens.
Do correlations stay the same all year?
No, they change with interest rates, earnings, and risk sentiment. That’s why rolling correlation is more useful than a single snapshot.
What is a rolling correlation?
It’s calculated over a moving window (like 60 days) so you can see how relationships strengthen or weaken over time.
What’s the difference between correlation and beta?
Correlation measures the direction of movement, while beta measures sensitivity to market moves. A stock can have high correlation but a different beta.
How do correlations behave during crises?
They usually spike toward 1.0 as investors sell risk assets together and pile into safe havens like USD, JPY, Treasuries, and gold.
How can I trade a correlation breakdown?
Pairs trading is common: go long one asset and short another when their relationship diverges, expecting a reversion.
Can correlations help with hedging a portfolio?
Yes. For example, if your portfolio is heavy in US tech, you could hedge with short Nasdaq futures or even use FX (USD/JPY) if yen tends to move opposite your risk assets.
Sign up in seconds for free, access your platform, and start trading with ease.
Introduction to cTrader: The Quick Setup Every Trader Should Know
Let's turn the default cTrader view into a workspace that matches how you trade with practical watchlists, default chart templates, and order ticket settings.
Detail
Choosing a Broker for Gold Trading
What to Consider When Choosing a Broker for Gold? In this guide, we will look at the decision-making process from a trader’s eyes.
Detail
Historical Movements of Gold: What to expect in 2026?
Will gold continue rising in 2026? Explore key drivers, past trends, and three realistic scenarios shaping next year’s gold outlook.
DetailThen Join Our Telegram Channel and Subscribe Our Trading Signals Newsletter for Free!
Join Us On Telegram!
