macro-stress

name	macro-stress
description	Macro stress-test: simulate how a portfolio reacts to central bank rate changes, inflation shocks, currency devaluations or commodity price shifts. Claude builds the sensitivity model from the portfolio's own data — no hardcoded assumptions. Step-by-step impact reasoning is written into the output so it stays auditable.

Macro Stress Test

What Claude does here: Claude reasons step-by-step through each asset's exposure to a macro shock — correlations, FX pass-through, sector sensitivities — rather than applying a flat percentage. The reasoning is written into the report itself so results are auditable (internal thinking is not visible to the reader).

Trigger phrases

• "USD %20 yükselirse portföyüme etkisi ne?"
• "Fed 100bps artırırsa ne olur?"
• "Enflasyon %60'a çıkarsa portföy analizi"
• "Stress test: BIST %30 düşüş"
• "Run a macro stress test: oil +50%"

Supported shock types

Shock	Parameter	Example
FX devaluation	ccy, change_pct	TRY -20%
FX appreciation	ccy, change_pct	USD +15%
Central bank rate	rate_change_bps	+100bps
Inflation	inflation_pct	60%
Equity index	market, change_pct	BIST -30%
Commodity	commodity, change_pct	GOLD +25%
Custom basket	array of above	multiple shocks simultaneously

Phases

Phase 1 — Portfolio read

Read data/portfolio.json (or output/latest.json if available for current values). Classify each holding by:

• FX exposure: which currency does its price move in?
• Macro sensitivity: equity (market beta), commodity (commodity price), cash (rate sensitive), crypto (high vol, low macro correlation)
• Sector (if equity): energy, financials, tech, defense, consumer — each has different rate/inflation sensitivity

Phase 2 — Shock parameterization

Parse the user's stress scenario. Convert natural language to parameters:

• "USD yüzde yirmi yükselir" → {shock: "fx", ccy: "USD", vs: "TRY", change_pct: +20}
• "Fed 100bp" → {shock: "rate", change_bps: +100, market: "US"}
• "Türkiye enflasyonu yüzde altmış" → {shock: "inflation", pct: 60, market: "TR"}

If the user specifies multiple shocks, model them simultaneously (additive first-order).

Phase 3 — Impact model (step-by-step, written out)

For each holding, reason through:

holding: NVDA (equity, USD, tech)
shock: USD/TRY +20%
  → NVDA price in USD: no direct FX effect on USD price
  → NVDA value in TRY: +20% (FX gain — USD asset held in TRY base)
  → Rate sensitivity: tech stocks inverse to rates (+100bps → P/E compression ~-10%)
  → Net effect: +20% FX * (1 - 0.10 rate compression) = +18%

Sensitivities to use (when not derivable from data):

• Equity / BIST: β ≈ 1.0 vs BIST100 (energy/defense β ≈ 0.8, tech β ≈ 1.2)
• Gold: negative real rate correlation; inflation +10% → gold +5–8%
• USD cash: direct 1:1 FX gain vs TRY
• Tech equity (USD): rate +100bps → P/E compression ~8–12%
• Energy equity: oil +10% → energy stocks +6–8%

State all assumed sensitivities explicitly.

Phase 4 — Portfolio-level summary

Base net-worth:         ₺X
Post-shock net-worth:   ₺Y
Change:                 ₺Z (±N%)

Winners:  [list with individual impact]
Losers:   [list with individual impact]

Largest single-holding impact: X
Most concentrated risk: Y

Phase 5 — Hedging suggestions

For each major negative impact, suggest one practical hedge:

• FX loss on USD assets → TRY-denominated bonds / VIOP USD futures
• Rate-sensitive equities → defensive rotation (utilities, dividend stocks)
• Gold underperformance in disinflation → reduce allocation, rotate to equities

Phase 6 — Output

Write output/stress-<scenario>-<YYYYMMDD>.md:

# Macro Stress Test: <Scenario> (<Date>)

## Scenario Parameters
## Holdings Impact Table
## Portfolio Summary (before / after)
## Key Risk Concentrations
## Hedging Suggestions
## Assumptions & Caveats

Disclaimer: Sensitivities are estimates. Actual market reactions depend on timing, liquidity and correlation breakdown during crises. Not investment advice.