This section is the set of transmission mechanisms by which the major macro and intermarket variables — interest rates, bond yields, the dollar, oil and commodities, inflation, credit spreads, and system liquidity — actually reach equity prices. The unifying idea is the discounted-cash-flow identity: a stock is the present value of future cash flows, so any macro force ultimately works through one of two doors — the numerator (expected earnings / cash flows) or the denominator (the discount rate = risk-free yield + equity risk premium), with a third overlay of risk appetite / financial conditions that scales how aggressively investors fund the whole structure. The core tension that runs through every child node is the same: each transmission channel is theoretically clean and economically real, yet the observed macro→equity relationship is weak, unstable, and regime-dependent — because (a) macro variables move together and partly offset each other, and (b) the same variable transmits through opposing channels at once. These mechanisms are best used as conditioning context for a regime, not as standalone directional triggers.

What this section covers (and what it defers)

This is the "mechanism" layer of the Macro & Intermarket Analysis branch — it explains why and through which channel a macro input touches stocks. It deliberately defers two neighbours: the measurement/indicator definitions (DXY, the yield curve, VIX, breadth, individual spread series) and the regime-classification machinery (how the inputs are combined into a single risk-on/risk-off state) live in adjacent material and the Delvantic regime engine. The "How X affects stocks" framing — long popularized in John Murphy's Intermarket Analysis — treats stocks, bonds, commodities, and currencies as one linked system rather than four independent markets; this section is the modern, evidence-checked version of that idea.

Map of the sub-topics

The seven children split by which macro variable does the transmitting:

1. How Interest Rates Affect Stocks (Equity Duration) — the foundational discount-rate primitive. Rates sit in the DCF denominator; equity duration measures how sensitive a stock is to that rate. Long-duration (growth) names react more than short-duration (value). The headline empirical anchor is Bernanke-Kuttner's ~1% index move per 25-bp surprise cut — though the mechanism (risk premium vs. yields) is now disputed (Nagel-Xu, 2024). 2. How Bond Yields Affect Equity Multiples — the same denominator channel viewed through the P/E lens: rising government yields tend to compress what investors pay per dollar of earnings, but why yields moved (growth optimism vs. inflation fear vs. fiscal stress) often matters more than the level. 3. How the Dollar Affects Stocks — two opposing channels: a fundamental earnings/translation channel (strong dollar = EPS haircut for multinationals) and a financial-conditions channel (the dollar as global funding/safe-haven proxy). The earnings link is solid; the index-level price correlation is weak and sign-unstable (DataTrek's ~15-year average dollar/S&P 500 correlation is about −0.26, an R² of roughly 7%). 4. How Credit Spreads Affect Risk Appetite — spreads as both a price (cost of corporate credit) and a thermometer (risk-bearing capacity). Among the most empirically validated macro indicators: Gilchrist-Zakrajšek's excess bond premium reliably leads recessions — but over quarters, not days. 5. How Inflation Affects Value vs Growth — inflation routed through the duration argument to the value/growth spread. Mechanically real some of the time (2021–23 was the showcase), but a surprisingly weak and regime-dependent relationship over long history. 6. How Oil & Commodities Affect Sectors — the cross-sectional channel: a commodity move is a tailwind for producers and a margin tax on consumers, and why it moved (supply shock vs. demand shock) flips the equity implication. Never a single market-wide signal. 7. How Liquidity Affects Risk Assets — the monetary/system-liquidity channel (central-bank reserves, funding conditions) that scales risk appetite at cycle scale. Powerful at cycle turns and in funding stress; routinely over-fitted into spurious weekly "net liquidity" trading signals.

The cross-cutting principle: same shock, opposite signs

The single most important idea for reading this whole section is that the sign of any macro→equity relationship is regime-dependent, not fixed. Rates can rise because growth is strong (lifting the earnings numerator enough to offset the discount-rate drag) or because inflation is feared (no offset). The dollar can rise with U.S. equities in a U.S.-growth-leadership regime and against them in a crisis (Jen's "dollar smile"). Stock-bond correlation itself flips between regimes — negative through the disinflationary 1995–2020 era, then positive in the 2022 inflation shock (CFA Institute / Financial Analysts Journal). This is why every child node carries the same hard caveat: do not encode a fixed coefficient for "X up → stocks down."

Adoption, debate & evidence (section level)

The intermarket/macro-transmission framework is mainstream — used by sell-side strategists, global-macro funds, and the CMT body of knowledge — and the individual mechanisms are economically uncontested. What is genuinely contested is the tradeable strength of the links. The academic literature finds macro variables predict equity returns "unevenly over time," with predictability concentrated in volatile/crisis regimes and far weaker in calm ones (ScienceDirect; LSEG). The honest hierarchy of evidence within this section: credit spreads / the excess bond premium are the strongest (Fed/academic-grade recession prediction); the discount-rate logic is theoretically airtight but empirically noisy; the dollar and inflation→value/growth links are real but weak and regime-flipping; and the "net liquidity" weekly correlation is the weakest (a spurious-trend artifact). Folklore to reject: "strong dollar = weak stocks," "oil up = bad for stocks," "rates up → stocks down," and the "0.95 net-liquidity correlation" — all overstate real but conditional effects.

Strengths & limitations

Works best as a regime classifier and cross-sectional lens — explaining which cohorts of stocks (growth vs. value, multinational vs. domestic, commodity producer vs. consumer) face a structural head- or tailwind under the prevailing macro state, and flagging when liquidity/credit stress raises the odds a normal pullback becomes a cascade. Fails as a high-frequency, mechanical timing system: the channels offset, the correlations are weak (often single-digit R²) and sign-unstable, and the relationships strengthen exactly when they are least useful (in crises, when everything correlates to 1). The #1 section-wide misuse is treating any single "How X affects stocks" rule as a deterministic, one-way directional trigger rather than one conditional input among several.

Sources

• John J. Murphy, Intermarket Analysis: Profiting from Global Market Relationships (Wiley); StockCharts ChartSchool, "Intermarket Analysis" — the four-market framework and its regime-dependence: https://chartschool.stockcharts.com/table-of-contents/market-analysis/intermarket-analysis
• CFA Institute / Financial Analysts Journal, "Empirical Evidence on the Stock–Bond Correlation" — regime flips in stock-bond correlation: https://www.tandfonline.com/doi/full/10.1080/0015198X.2024.2317333
• LSEG / FTSE Russell, "Multi-asset return correlations — a new regime, or an era of instability?" — abrupt correlation regime shifts: https://www.lseg.com/en/insights/ftse-russell/multi-asset-return-correlations-a-new-regime-or-an-era-of-instability
• ScienceDirect, "Macro variables and international stock return predictability" — uneven, regime-concentrated predictability: https://www.sciencedirect.com/science/article/abs/pii/S0169207004000512
• Bernanke & Kuttner (2005), "What Explains the Stock Market's Reaction to Federal Reserve Policy?", Journal of Finance — the ~1% index move per 25-bp policy surprise: https://www.nber.org/papers/w10402 ; revisited/disputed by Nagel & Xu (NBER, "Movements in Yields, not the Equity Premium: Bernanke-Kuttner Redux"): https://voices.uchicago.edu/stefannagel/research/
• Gilchrist & Zakrajšek (2012), "Credit Spreads and Business Cycle Fluctuations", American Economic Review / NBER — the excess bond premium as a recession predictor: https://www.nber.org/papers/w17021
• DataTrek Research, "Dollar/Stock Correlations" — the weak (~−0.26, R² ≈ 7%) dollar/S&P 500 relationship: https://datatrekresearch.com/dollar-stock-correlations-sp-margins/
• Child nodes (this section), for per-channel mechanics, magnitudes, and full sourcing: How Interest Rates Affect Stocks (Equity Duration), How Bond Yields Affect Equity Multiples, How the Dollar Affects Stocks, How Credit Spreads Affect Risk Appetite, How Inflation Affects Value vs Growth, How Oil & Commodities Affect Sectors, How Liquidity Affects Risk Assets.

Dispute flag: the macro-transmission framework is mainstream and the individual mechanisms uncontested, but the tradeable strength of every link is regime-dependent and empirically weak; credit spreads are the strongest-evidenced channel and the "net liquidity" weekly correlation the weakest. Specific magnitudes are sourced in the child nodes.