Macro Scenario Monitoring

Vol. 1 | Before, during, and after the U.S.-Iran war

Decision, Risk and AI

Macro Scenario Monitoring

Vol. 1 studies one live geopolitical event through a sell-side macro lens. The organizing question is simple: how do we turn a before-war baseline, a live war shock, and post-war outcomes into a structured decision process using public data, explicit scenarios, and market confirmation signals?

This hub is intentionally simple. It introduces the event, the decision structure, and the two research branches. The detailed model, signal design, and index lists live inside each branch page.

Vol. 1 frame

One event, three phases

Phase 1

Pre-war baseline

The benchmark world before the shock: growth, inflation, rates, and cross-asset pricing under a lower geopolitical premium.

Phase 2

Current war transmission

The live shock: energy, shipping, food, inflation compensation, credit, and risk appetite are checked against explicit lagged market responses.

Phase 3

Post-war outcomes

The two main paths after the conflict: relief and normalization, or persistent fragmentation with longer-lived inflation and risk premia.

Research structure

Two branches from the same scenario engine

Branch A

Commodity

Energy and food are treated as physical markets first, then as macro transmission channels. This branch focuses on supply, storage, logistics, inventories, export flows, weather, and geopolitical risk premium.

Goal: show how a commodity shock becomes an inflation, growth, FX, and country-risk story.

  • Energy-centered decision model for oil, gas, products, and food spillovers.
  • Scenario design around pre-war, current war, relief, and persistent fragmentation.
  • Desk-style reading of EIA, IEA, OPEC, USDA, FAO, futures curves, and positioning.

Open commodity branch

Branch B

Investment

This branch translates the same scenarios into sell-side macro forecasting and market interpretation. It follows the daily discipline of revising the growth, inflation, Fed, rates, FX, credit, and equity story for clients and internal desk partners.

Goal: show how a macro economist updates scenarios, interprets signals, and turns them into a publishable desk note.

  • Live scenario scoring using public signals and explicit lag logic.
  • Indicator playbook covering PMI, claims, payrolls, CPI/PCE, the yield curve, spreads, financial conditions, and GDP nowcasts.
  • Sell-side framing for forecast revision, sales/trading briefings, and client updates.

Open investment branch

Decision model

How the project is organized

Scenario

Each phase is translated into a base case and alternative scenarios with explicit reasoning, not only narrative judgment.

Signals and indices

Commodity reports, macro releases, and market signals are linked to each scenario through expected direction, lag, and transmission channel.

Desk output

The final output is a sell-side style research surface: what changed, what confirms it, what could invalidate it, and what clients should watch next.