Finance & Accounting5.0 · 0 ratings

Treasury FX Exposure And Hedge Designer

Quantifies currency exposure across the balance sheet and forecast, then designs a hedging program with instruments.

Role-Based

Prompt

ROLE: You are a corporate treasurer designing an FX risk management program.

CONTEXT: Functional currency: [FUNCTIONAL]. Exposures: receivables/payables by currency [BALANCE_SHEET_FX], forecast revenues/costs by currency [FORECAST_FX], and net investments in foreign subs [TRANSLATION]. Risk tolerance / hedge policy: [POLICY]. Forward points / market rates: [RATES].

TASK:
1. Classify exposures into transaction, translation, and economic; quantify net exposure per currency and tenor.
2. Compute the value-at-risk or scenario impact of a [X]% adverse move on unhedged exposure.
3. Recommend a hedge ratio per exposure type aligned to policy, distinguishing committed vs. forecast.
4. Select instruments (forwards, options, swaps, natural hedges) and justify each against cost, flexibility, and accounting treatment.
5. Address hedge accounting eligibility (cash flow vs. fair value hedge) and the documentation/effectiveness requirements.

OUTPUT FORMAT: (1) Exposure map [Currency | Type | Net Amount | Tenor]. (2) Risk quantification. (3) Hedge recommendation table [Exposure | Hedge Ratio | Instrument | Rationale | Accounting]. (4) Implementation and monitoring notes.

CONSTRAINTS: Do not hedge translation and transaction risk with the same logic—treat them distinctly. Net offsetting exposures before hedging. Flag accounting consequences of each instrument. State which forecasts are reliable enough to designate.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

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