Why Intermarket Analysis Matters
John Murphy, the technical analyst who formalised intermarket analysis in his 2004 book Intermarket Analysis: Profiting from Global Market Relationships, put it bluntly: "The old idea of studying one market in isolation is no longer valid. All markets are interrelated." That statement is arguably more true today than when he wrote it.
Four asset classes interact in a continuous feedback loop: currencies, commodities, bonds, and stocks. A move in one ripples through the others. Traders who watch only their chart miss the context that determines whether a setup has a tailwind or a headwind. Intermarket analysis doesn't give you entries — it gives you bias. And bias, applied consistently, is where edge compounds.
The US Dollar Index (DXY)
DXY is a trade-weighted basket of the dollar against six major currencies: roughly 58% EUR, 14% JPY, 12% GBP, 9% CAD, 4% SEK, and 4% CHF (ICE weights unchanged since 1973). Despite being heavily euro-weighted, DXY remains the reference for global dollar strength.
DXY vs Commodities
The inverse relationship between DXY and commodities is the most reliable correlation in macro. Dollar-denominated commodities become cheaper for foreign buyers when the dollar weakens, and more expensive when it strengthens. The 20-year rolling correlation between gold and DXY typically sits between −0.6 and −0.9. Oil, copper, and agricultural commodities show similar (though noisier) inverse patterns.
DXY vs Equities
The relationship here is more nuanced. Roughly 40% of S&P 500 revenue comes from overseas, so a strong dollar compresses multinational earnings when translated back to USD. Goldman Sachs research estimates that every 10% rise in the trade-weighted dollar cuts S&P 500 EPS by approximately 2-3%. This is why tech earnings often disappoint during sharp DXY rallies — Apple, Microsoft, and Google derive half their revenue abroad.
DXY vs EM and Crypto
A strong dollar equals tighter global liquidity, which is historically bearish for emerging markets and crypto. Bitcoin's correlation with DXY turned sharply negative post-2020 as BTC matured into a macro risk asset. When DXY rallies, EM equities and crypto tend to sell off together — it's a liquidity trade, not a fundamentals trade.
Treasury Yields: The Discount Rate for Everything
The 10-year Treasury yield is the discount rate for every future cash flow in the economy. When yields rise, the present value of distant earnings falls — which is why rising rates crush growth stocks harder than value. The NDX drawdown of -33% in 2022 coincided almost perfectly with the 10Y moving from 1.5% to 4.2%. That wasn't a coincidence; it was math.
The Yield Curve (2s10s)
The spread between the 2-year and 10-year Treasury is the most watched recession indicator in finance. Every US recession since 1955 has been preceded by an inversion of the 2s10s curve, as documented by Estrella and Mishkin at the New York Fed. When short-term yields exceed long-term yields, it signals the market expects the Fed to eventually cut rates — usually because growth is slowing.
Growth vs Value Rotation
Rising real yields (nominal yields minus inflation expectations) favour value sectors — banks profit from wider net interest margins, energy benefits from inflation pass-through. Falling real yields favour growth — tech, biotech, and anything with distant cash flows. The Russell 1000 Growth/Value ratio closely tracks the inverse of the 10Y real yield. If you're trading QQQ, you're implicitly trading real yields.
The 2022 Correlation Flip
For two decades (2000-2021), stocks and bonds were negatively correlated — bonds hedged equities during drawdowns. This was the foundation of the 60/40 portfolio. Then 2022 happened. Inflation dominated, the Fed hiked aggressively, and both asset classes fell in lockstep. The 60/40 portfolio posted its worst year since 1937 at -17%. The stock-bond correlation flipped positive and has remained unstable since. This is a warning that historical correlations are regime-dependent, not laws of nature.
Indices and Sector Leadership
The three major US indices tell different stories. SPX represents broad market sentiment. NDX is growth and duration-sensitive — when NDX leads, you're in a risk-on, low-volatility regime. DJIA is cyclical and industrial-heavy. Russell 2000 (small caps) leading typically signals early-cycle expansion.
Sector rotation follows the business cycle. The Fidelity/Stovall framework maps it:
- Early cycle: Financials and consumer discretionary lead as rates bottom and credit eases.
- Mid cycle: Technology and industrials outperform as earnings growth accelerates.
- Late cycle: Energy and materials lead as inflation and commodity demand peak.
- Recession: Staples, healthcare, and utilities are defensive safe havens.
When the market is ambiguous, look at what's leading. If XLF and XLY are making new highs while XLU lags, you're early-cycle. If XLE and XLB are leading, you're late-cycle and should be thinking about defensive positioning.
Commodities as Economic Signals
Gold vs real yields: Gold traditionally trades inversely to real yields (TIPS yields). Rising real yields are usually bearish gold because the opportunity cost of holding a non-yielding asset goes up. This correlation decoupled in 2023-2025 as central bank buying (PBoC, RBI) overwhelmed the TIPS signal — another example of correlations breaking under unusual flows.
Oil and inflation: Crude oil feeds directly into CPI through energy and transportation costs. Every $10 move in WTI adds roughly 0.2 percentage points to headline CPI. Watching oil is watching inflation with a lag.
Copper — "Dr. Copper": Copper is a leading indicator of global industrial activity because it's used in construction, manufacturing, and electrification. The copper/gold ratio correlates tightly with the 10Y yield — when copper rises relative to gold, growth expectations are rising, and yields typically follow. Jeff Gundlach popularised this ratio as a leading indicator.
Risk-On vs Risk-Off Regimes
In normal markets, assets have distinct correlations. In a crisis, correlations converge toward 1 — everything sells off except dollars, yen, Swiss francs, Treasuries, and gold. This "correlation breakdown" has been documented by the BIS and IMF during the 2008 GFC, March 2020 COVID crash, and the 2022 rate shock.
Tells for a risk-off shift:
- VIX above 25 — volatility is no longer quiet.
- HYG/LQD ratio falling — high-yield credit is underperforming investment grade, signalling stress.
- AUD/JPY falling — the classic "risk proxy" pair; AUD is commodity-linked risk, JPY is funding currency safety.
- 2Y yields falling faster than 10Y — the market is pricing rate cuts, usually because growth is slowing.
Famous Correlations That Broke
Intermarket analysis isn't a rulebook — it's a framework that works until the regime changes. Some famous breakdowns:
- Stock-bond correlation (2022): Inflation destroyed the 20-year negative correlation. 60/40 portfolios cratered.
- Oil vs equities (2014-2016): The oil crash was supply-driven (US shale), not demand-driven, so cheap oil was bullish consumers instead of bearish stocks.
- BTC vs NDX (post-2024): Tight correlation from 2021-2023, loosened after the 2024 halving as institutional flows dominated retail sentiment.
- Yen carry unwind (August 2024): The BoJ rate hike broke the USDJPY/NDX correlation violently within days, triggering a global deleveraging.
The lesson: always ask why the correlation exists. If the underlying driver changes, the correlation will too.
How to Use Intermarket Signals in Practice
Intermarket analysis works best for bias, not timing. Use it as a top-down filter before looking at structure and entries:
- DXY breaking down + falling real yields: Tailwind for gold, BTC, and EM equities. Look for long setups.
- Copper/gold ratio rising: Growth expectations improving. Favour cyclicals and shorter-duration stocks.
- Credit spreads widening while SPX makes highs: Classic bearish divergence. The 2007 and 2018 tops both showed this.
- AUD/JPY breaking down intraday: Equity futures often follow within hours — useful as a risk filter for US open trades.
- 2s10s steepening after inversion: Historically the actual recession trigger. When the curve re-steepens from inversion, growth fears become real.
The point isn't to trade the macro directly — it's to know whether your setup has the wind at its back or in its face. A bullish structure break on NDX with DXY rolling over and real yields falling is a completely different trade than the same structure break with DXY ripping higher and yields spiking. Same chart, different context, different expected value.
Final Thought
Murphy's framework is 20 years old and still holds because it's built on economic fundamentals, not technical patterns. Markets change regimes, correlations break, and new asset classes (like crypto) integrate into the web — but the underlying principle stands: nothing moves in isolation. The traders who consistently make money understand the context their chart is sitting in. Everyone else is reading one page of a book and trying to guess the plot.
Sources & Further Reading
- John J. Murphy, Intermarket Analysis: Profiting from Global Market Relationships (Wiley, 2nd edition 2013) — the foundational text on cross-market relationships.
- Arturo Estrella & Frederic Mishkin, "Predicting US Recessions: Financial Variables as Leading Indicators," Review of Economics and Statistics (1998) — the definitive academic paper on the yield curve as a recession predictor.
- CME Group Education, "Understanding Intermarket Relationships" — practical primer from the world's largest derivatives exchange.
- Bank for International Settlements, Quarterly Review — ongoing research on cross-asset correlations and liquidity regimes.
- Sam Stovall, The Seven Rules of Wall Street (2009) — origin of the sector rotation framework still used by Fidelity and others.