Macro & intermarket analysis is the study of how the broad economic backdrop and the relationships between asset classes drive equity prices — the top-down lens, as opposed to the bottom-up study of a single company. "Macro" is the exogenous layer: growth, inflation, interest rates, central-bank policy, fiscal flows, liquidity, currencies, and geopolitics. "Intermarket" is the relational layer: how stocks, bonds, commodities, and currencies move relative to one another and what those relationships imply about the stage of the cycle. The two are inseparable in practice — macro variables are precisely the forces that link the four markets. The core tension running through the whole domain is that these drivers are unambiguously powerful (they reprice every security at once, which is why they show up as systematic, undiversifiable risk) yet notoriously hard to trade: the relationships are real but regime-dependent and unstable, forecasts are unreliable, and the market's reaction to a known event is frequently the opposite of intuition.

What this section covers

This is a broad domain organized as a top-down stack — from the economy, through policy and the plumbing that transmits it, to the cross-asset relationships and the per-stock sensitivities they produce. The fifteen child branches map to that flow:

• Economic cycles & indicators (001) — the raw inputs: GDP, inflation (CPI/PCE), employment, and the leading-vs-lagging distinction (PMI, etc.) that lets you place where in the cycle you are.
• Monetary policy & central banks (002) — the Fed, rates, QE/QT, and the yield curve (normal vs inverted, the recession signal, real vs nominal yields). The single most important macro driver of multiples.
• Fiscal policy & government spending (003) — the other policy lever: deficits, stimulus, and their growth/inflation effects.
• Intermarket analysis: stocks/bonds/commodities/FX (004) — Murphy's relational core: stocks↔bonds, commodities↔inflation, the dollar↔equities, and credit spreads as a risk gauge.
• Sector rotation & the business cycle (005) — how leadership rotates through early-, mid-, late-cycle, and recession-defensive sectors.
• Global macro & geopolitics (006) — the cross-asset strategy layer and the measured (usually short-lived) impact of geopolitical shocks.
• Inflation & deflation regimes (007) — the regime that sets the sign of most intermarket relationships.
• Currencies & FX impact on equities (008) — translation effects, multinational earnings, and the dollar's role.
• Macro→equity transmission (009) — the explicit "how X affects stocks" channels: rates→duration, dollar, oil, credit spreads, inflation→value-vs-growth, liquidity.
• Fed plumbing & net liquidity (010) — the post-2019 mechanics: reverse repo, the Treasury General Account, QT, bank reserves, FOMC drift.
• Market seasonality & calendar effects (011) — Sell-in-May, Santa Claus rally, turn-of-month, the election cycle, tax-loss season; the most folklore-prone branch.
• International & emerging markets (012) — diversification, country/political risk, hedged vs unhedged, ADRs.
• Economic-data calendar & high-impact events (013) — the release calendar (NFP, CPI, FOMC, ISM, etc.), the surprise/reaction mechanics, the Fed reaction function, "good news is bad news."
• Tracking & monitoring macro (014) — the toolkit: economic calendars, surprise indices (Citi CESI), nowcasts (GDPNow), FedWatch rate odds, the dot plot, breakevens, financial-conditions indices, positioning surveys, FRED.
• Macro factor sensitivity & elasticity (015) — the quant bridge: estimating per-stock macro betas (rate beta, DXY beta, oil, credit), why they're unstable, and how to apply them.

The core organizing ideas

Three threads recur across the children. First, systematic risk is real and priced. The academic foundation is Arbitrage Pricing Theory (Ross, 1976); its canonical empirical test, Chen, Roll & Ross (1986, Journal of Business 59:383–403), found that innovations in a handful of macro variables — industrial production, unexpected and changing inflation, the term-structure spread (long minus short rates), and the credit-risk premium (high- minus low-grade bond spread) — are significantly priced sources of common variation in equities. Macro is not noise; it is the systematic component of return. (Note that subsequent literature has questioned the robustness and out-of-sample stability of macro-factor pricing, so treat this as foundational rather than settled.)

Second, the relationships are regime-dependent, and the inflation regime usually sets the sign. Murphy's intermarket framework describes stocks, bonds, commodities, and the dollar rotating in a recognizable sequence around the cycle (StockCharts ChartSchool), but the direction of the stock–bond link flips with the inflation backdrop: negative (bonds hedge stocks) in a stable-inflation, growth-shock world, positive (both fall together) in an inflation/rates shock — 2022 being the textbook breakdown. The deepest analytical content of this section is which regime you are in.

Third, the transmission channel is the discount rate and the cycle stage. Most macro variables reach equities through one of two doors: they change the rate at which future cash flows are discounted (rates, real yields, credit spreads → multiples and equity duration), or they signal where in the business cycle the economy sits (employment, PMI, the yield curve → which sectors lead). Branch 009 makes these channels explicit.

When it matters — and when it doesn't

Macro dominates at turning points and during shocks: regime changes, recessions, central-bank pivots, inflation surprises, liquidity events. In those windows correlations rise toward 1, dispersion across stocks collapses, and stock-specific work is overwhelmed — "everything trades on the Fed." In calm, trending, mid-cycle regimes the opposite holds: idiosyncratic and bottom-up factors reassert, macro fades to backdrop, and over-trading the macro tape is a way to lose money to whipsaws and false signals. A second honest limitation runs through the whole domain: forecasting macro is hard and the market often front-runs the obvious, so the practitioner's edge is rarely in predicting the data — it is in correctly reading the current regime and knowing each asset's conditional sensitivity to it.

Sources

• John J. Murphy — Intermarket Analysis: Profiting from Global Market Relationships (Wiley); Trading with Intermarket Analysis
• StockCharts ChartSchool — Intermarket Analysis
• Chen, N-F., Roll, R. & Ross, S. (1986) — Economic Forces and the Stock Market, Journal of Business 59:383–403 (empirical macro-factor test of Ross's 1976 Arbitrage Pricing Theory)
• MSCI — Foundations of Factor Investing (macroeconomic vs style factors)
• Sibling child nodes within this section (001–015) for branch-level depth

Flag: the intermarket relationships are well-documented but unstable; the seasonality branch (011) is the most folklore-prone and is treated more skeptically in its children. This overview points to the children rather than restating their measured base rates.