Mapping Global Opportunities

Run this prompt against current market conditions:

Act as a professional global macro investor with a 3–7 year horizon.

Task: Identify which regions and asset classes currently offer the
highest probability of attractive risk-adjusted returns in public markets.

Constraints:
- Focus only on liquid public markets (equities, listed credit,
  commodities, ETFs)
- Ignore short-term trading signals
- Do not list individual companies
- Be explicit about cycle positioning

For each region or asset class:
1. State the dominant macro drivers
2. Identify the key valuation tension (cheap vs expensive relative to history)
3. Highlight the main structural tailwind and the main structural risk
4. Conclude with a clear verdict: "attractive," "neutral," or "avoid"

Output format: Clear prose, no bullet points, no filler, no generic optimism.

Review output, then use the Workflow below to stress-test and refine.

Progress:

• Step 1: Define the universe (regions + asset classes to screen)
• Step 2: Generate the macro map using the Quick Start prompt
• Step 3: Cross-check each verdict against a contrarian counter-argument
• Step 4: Rank verdicts by conviction, not alphabetically
• Step 5: Flag which "avoid" calls are cycle-timing vs structural
• Step 6: Narrow "attractive" list to 2-4 regions for deeper dive

Step 1 — Define the universe. Standard screen covers: US equities, Europe equities, Japan equities, China/EM Asia equities, broader EM equities, EM/DM listed credit, commodities (energy, industrial metals, precious metals), and rates/duration proxies. Add or remove based on mandate.

Step 2 — Generate the map. Run the prompt verbatim. Resist editing constraints — the "no bullet points, no filler" rule forces the model to commit to actual reasoning chains rather than hedge with lists.

Step 3 — Cross-check. For every "attractive" verdict, ask: "What would make this wrong in 18 months?" For every "avoid," ask: "What catalyst would flip this?" This catches recency bias baked into the first pass.

Step 4 — Rank by conviction. Not all "attractive" calls are equal. Sort by how structurally durable the tailwind is versus how cyclically dependent the call is on a single variable (e.g., one central bank decision).

Step 5 — Separate cycle-timing from structural avoids. A region can be "avoid" purely on valuation/cycle (temporary) or "avoid" on structural grounds (demographics, institutional decay, currency regime). Mark which is which — cycle-timing avoids need re-checking quarterly, structural avoids don't.

Step 6 — Narrow the list. Take the top 2-4 "attractive" calls forward into asset-class-specific or country-specific due diligence. This skill is explicitly a filter, not a stock-picker.

Example 1: Input: "Map opportunities as of a late-cycle US tightening environment, with China mid-stimulus, and energy markets structurally undersupplied."

Output:

US equities sit late in a tightening cycle where earnings growth has been propped up by a narrow set of mega-cap beneficiaries of capital-expenditure cycles rather than broad margin expansion. Valuations relative to trailing-decade history sit in the upper quartile, and the tension is that multiple compression risk is offset only if rate cuts arrive faster than the labor market deteriorates. The structural tailwind is capital markets depth and reserve-currency flows that keep allocators structurally overweight by default; the structural risk is fiscal deficits colliding with an aging buyer base for sovereign debt, which eventually competes with equity multiples for capital. Verdict: neutral.

China equities trade at multi-year lows relative to book value, reflecting a valuation tension between genuinely impaired property-sector balance sheets and an oversold reaction in sectors with limited property exposure. The dominant macro driver is a government-directed stimulus cycle attempting to replace property-led growth with manufacturing and domestic consumption, with success still unproven. The structural tailwind is policy capacity: the state can direct capital in ways democracies cannot. The structural risk is capital account controls and governance opacity, which cap the multiple foreign allocators are willing to pay regardless of earnings recovery. Verdict: attractive, sized for volatility.

Energy commodities benefit from a multi-year underinvestment cycle in upstream capacity colliding with persistent demand resilience, meaning the valuation tension is inverted from equities: the asset class is arguably cheap relative to the replacement cost of new supply. The structural tailwind is capital discipline among producers who were punished by public markets for growth-at-all-costs drilling in the prior decade. The structural risk is accelerated demand destruction from efficiency gains and electrification outpacing the supply constraint. Verdict: attractive.

Example 2: Input: "Map opportunities during a period of synchronized global disinflation and falling real rates."

Output: Should identify long-duration assets (government bonds, high-multiple growth equities) as beneficiaries, explicitly separate EM local-currency debt (benefits from falling US real rates via currency effects) from EM hard-currency debt (benefits less), and flag commodities as the probable "avoid" given disinflation's direct conflict with commodity demand/pricing narratives — rather than defaulting to generic "diversify across everything" advice.