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Intermarket Correlations

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Summary

Intermarket correlations are the relationships between price movements across different asset classes, sectors, or instruments. PSE uses these correlations as a diagnostic framework: rather than analysing each market in isolation, Anderson reads the concurrent or lagged movement across asset pairs to infer underlying liquidity conditions, cycle positioning, and near-term turning points. The key pairs PSE tracks include the US Dollar vs. commodities/gold, Bitcoin vs. software stocks, the S&P 500 vs. oil, and mega-cap indices vs. equal-weight indices. Intermarket analysis is complementary to cycle analysis — it provides real-time confirmation or contradiction of the broader cycle thesis without requiring cycle timing to resolve.

Core Claims

  • 2026-06-30-gann-20-intermarket-breadth-cmg-stop (2026-06-30): “Chart analysis can also be an advantage when it comes to understanding intermarket relationships, or how price movements in one sector could be reflected in another.” Anderson systematises intermarket correlations as a named analytical approach, identifying four key pairs: USD/commodities, S&P/oil, Bitcoin/software, and MAGS/RSP (mega-cap vs. equal-weight). — confidence: high
  • 2026-06-30-gann-20-intermarket-breadth-cmg-stop (2026-06-30): “Movements in the U.S. dollar play a major role in commodity prices. Since commodities are mostly priced and traded in dollars, a weaker dollar that boosts the purchasing power of non-U.S. buyers tends to boost commodities and precious metals. The peak in the U.S. Dollar Index during the second half of the real estate cycle tends to help drive commodities higher, along with gold and silver.” — confidence: high
  • 2026-06-30-gann-20-intermarket-breadth-cmg-stop (2026-06-30): “Bitcoin has also done a good job at tipping key turning points in software stocks.” Bitcoin often turns just before moves in the iShares Expanded Tech-Software Sector ETF (IGV). With Bitcoin near 350 support becomes a correlated watch. “You might not think Bitcoin has anything to do with MSFT’s price action, but I would keep an eye on both.” — confidence: high
  • 2026-06-30-gann-20-intermarket-breadth-cmg-stop (2026-06-30): “Other intermarket relationships will often see their correlations ebb and flow. A recent one in play has been the strong negative correlation between the S&P 500 and oil prices.” — confidence: high

Mechanism / How It Works

Intermarket analysis rests on the observation that asset prices are linked through shared macroeconomic drivers — liquidity, the dollar, interest rates, and the business cycle. Correlations are not fixed; they strengthen and weaken as the macro regime shifts. PSE’s approach treats these correlation changes as signals:

  1. Identify the structural relationship. USD ↔ commodities is structural (commodities are dollar-denominated). Bitcoin ↔ liquidity is structural (BTC is the purest liquidity proxy). S&P ↔ oil and mega-cap ↔ equal-weight are more cyclical — they strengthen or invert depending on the cycle phase.

  2. Watch for correlation breaks or leads/lags. When Bitcoin turns before software stocks, the lead is the signal — software is likely to follow. When the Mag 7 diverges from the equal-weight S&P, the divergence reveals whether breadth is widening or narrowing underneath the index print.

  3. Read the combined message. No single correlation is conclusive. PSE reads them in conjunction with cycle positioning: USD weakness in the second half of the cycle supports the commodity/gold/silver thesis; Bitcoin breakdown from $60K would be a liquidity warning that also pressures software; Mag 7 pulling back while the average stock rallies is a breadth-improvement signal that supports the bullish Roadmap scenario.

  4. Use as confirmation, not trigger. Intermarket correlations refine the read on cycle timing but do not replace the Roadmap or Gann dates. They are the real-time overlay on the structural framework.

Key Evidence

  • USD → commodities (structural, confirmed across cycles): The peak in the US Dollar Index during the second half of the real estate cycle drives commodities, gold, and silver higher. This is the mechanism behind PSE’s commodity-supercycle thesis for the current cycle stage. Anderson has been tracking the DXY testing $100 resistance since Gann #17 (June 16) and confirmed the break above 100 in Gann #18 (June 22). [Source: [[2026-06-30-gann-20-intermarket-breadth-cmg-stop|Gann #20]], 2026-06-30; reinforced by [[2026-06-22-gann-18-portfolio-update|Gann #18]]]
  • Bitcoin → software stocks (leading indicator): The Bitcoin/IGV overlay shows Bitcoin often turning just before moves in the broader software sector. As of June 30, Bitcoin is bouncing around 60,000 — the same level flagged as critical in Gann #14, #16, #18. A Bitcoin breakdown would also pressure MSFT (support at 350) and other software names. [Source: [[2026-06-30-gann-20-intermarket-breadth-cmg-stop|Gann #20]], 2026-06-30]
  • MAGS vs RSP (breadth signal): The Mag 7 ETF and the Invesco S&P 500 Equal Weight ETF (RSP) have moved in opposite directions at key junctures. From late 2025 into February, RSP rallied as MAGS pulled back. Since early June 2026, the pattern has repeated — Mag 7 pulling back while the average S&P stock moves to new highs. This is the inverse of the narrow-leadership pattern that dominated April–May and signals breadth improvement. [Source: [[2026-06-30-gann-20-intermarket-breadth-cmg-stop|Gann #20]], 2026-06-30]
  • S&P 500 ↔ oil (recently active): A strong negative correlation between the S&P 500 and oil prices has been “in play” recently (as of June 30). Anderson notes this as a correlation that “ebbs and flows” rather than being structural. [Source: [[2026-06-30-gann-20-intermarket-breadth-cmg-stop|Gann #20]], 2026-06-30]

Applications

  • Cycle-phase confirmation: USD weakness in the second half of the cycle confirms the commodity/gold/silver thesis. DXY behavior near $100 is a real-time test of the rotation trigger.
  • Liquidity monitoring: Bitcoin’s correlation with software stocks makes BTC a leading indicator for the tech sector. A Bitcoin breakdown from $60K would be a liquidity warning with cross-sector implications.
  • Breadth assessment: The MAGS vs RSP relationship reveals whether index gains are narrow (Mag 7 leading) or broad (average stock rallying). The recent shift toward RSP outperformance is a breadth-improvement signal.
  • Trade selection: Anderson’s watch on MSFT $350 support is directly derived from the Bitcoin/IGV correlation — a cross-sector trade setup that would not be visible from single-stock analysis alone.
  • Roadmap scenario weighting: The breadth improvement (RSP making new highs) is what shifts Anderson’s emphasis toward the red-line (bullish) Roadmap scenario. Intermarket reads feed back into cycle-timing views.

Evolution Over Time

  • Pre-June 2026 (piecemeal): Intermarket relationships appeared throughout earlier Gann emails — USD/commodities in Gann #17–18, Bitcoin/liquidity in Gann #14–16 — but were discussed individually rather than as a named framework.
  • June 30, 2026 (Gann #20): Anderson systematises intermarket correlations as a named analytical approach for the first time, identifying four key pairs and their diagnostic roles. [Source: PSE Gann #20, 2026-06-30]
  • July 8, 2026 (Gann #21): The USD/commodities correlation plays out in real time: DXY rallies into the June 22 solstice following a trend change around the May 4 midpoint, then reverses lower. Anderson frames the dollar reversal as a cycle-positioning signal: “Watching for a move in international equities is another way we can track and confirm our place in the cycle.” The 30-year Treasury yield also reverses higher on the seasonal date after pulling back from a false breakout above 5% — demonstrating that seasonal Gann dates drive intermarket direction changes across asset classes. [Source: PSE Gann #21, 2026-07-08]
  • June 30, 2026 (Gann #20): Anderson systematises intermarket correlations as a distinct analytical approach for the first time, presenting four key pairs in a single email. This may reflect the portfolio’s shift to cash (zero active positions) freeing attention from single-stock management toward broader cross-market reads. The timing is significant: with the portfolio fully in cash, intermarket analysis becomes the primary tool for identifying the next wave of setups. [Source: [[2026-06-30-gann-20-intermarket-breadth-cmg-stop|Gann #20]], 2026-06-30]

Contradictions & Open Questions

  • Correlation stability: Anderson acknowledges that “correlations ebb and flow” — the S&P/oil negative correlation is recently active but not structural. How reliable are cyclical correlations for trade decisions vs. structural ones (USD/commodities)?
  • Bitcoin as leading indicator: The claim that Bitcoin “often turns just before a move in the broader software sector” is based on overlay observation. Is this a stable structural lead, or a coincidence of the current cycle where both are liquidity-driven?
  • Breadth improvement vs. cycle-peak thesis: The breadth improvement (RSP making new highs, Mag 7 pulling back) is a bullish signal in the short term, but PSE’s structural thesis calls for a cycle peak within “months, maybe even a year.” How does breadth improvement reconcile with the late-cycle positioning? Anderson’s answer: “breadth tends to lag into major market peaks” — meaning breadth can improve even as the cycle approaches its top, and the divergence pattern of April–May may have been a mid-cycle correction rather than the cycle-peak signal it appeared to be.
  • Bitcoin Cycle — Bitcoin as liquidity proxy and leading indicator for software/tech
  • Liquidity Cycle — the macro driver behind most intermarket correlations
  • Market Breadth Divergence — the MAGS vs RSP relationship is a breadth signal; recent shift toward RSP outperformance may mark the end of the April–June divergence pattern
  • Sector Rotation — intermarket correlations drive sector rotation patterns
  • US Dollar Hegemony — USD as the structural anchor for commodity/gold/silver correlations
  • Financial Timetable — intermarket reads feed back into Roadmap scenario weighting
  • Mex Pete Trading Style — intermarket analysis complements pattern-based trade selection

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