PromptSharp › Daily briefs › Finance › August 14, 2026

Finance prompt of the day

August 14, 2026 · for Investment banking, sales & trading, equity research, FP&A. One sharp, copy-paste prompt — free, every weekday.

You are a PM's analyst running a QUARTERLY PORTFOLIO REVIEW from the data I paste (positions, weights, contribution, thesis notes). Produce:
1. An ATTRIBUTION read: the top contributors and detractors and, for each, whether the move was thesis-confirming, thesis-breaking, or noise. Use only figures I provide.
2. A THESIS-INTACT check per top position: is the original thesis still true, and what changed.
3. A DECISION LIST — this is the point: for each flagged position, a specific recommendation (add / trim / hold / exit) with the reason and a triggering condition. No 'monitor' without a defined trigger and review date.
4. The 2-3 portfolio-level risks (concentration, factor, correlation) I should act on.
[PASTE POSITIONS]

Rules: Do not invent, estimate, or extrapolate any figure — if a number is not in what I give you, write "not provided" and flag it. Mark every claim I should verify externally before relying on it. Never use, infer, or request material non-public information (MNPI) or client-confidential data.

How to run “Quarterly attribution + trim/add decision list”, step by step

The situation this prompt is built for: The quarter closed and you want a structured attribution plus a concrete trim/add decision list, not another parking-lot review. Below is exactly what to feed it and what comes back — no model-specific tricks, it runs the same in any chat AI.

What each placeholder does

Demo profile for the example fills: an equity research associate on a mid-cap sector coverage team, working in Excel, a chat AI model, and your firm's data terminal. Swap in your own context — or save it once at /profile and copied prompts arrive pre-filled.

• [PASTE POSITIONS] — this is the input the whole output quality hangs on. Demo fill: your own paste positions — one or two concrete lines beats a paragraph of vague context. Leave it vague and the model pads with boilerplate; make it concrete and every section downstream sharpens.

What the model hands back

The prompt forces a fixed deliverable shape, so you get a document, not a ramble:

1. An ATTRIBUTION read: the top contributors and detractors and, for each, whether the move was thesis-confirming, thesis-breaking, or noise. Use only figures I provide.
2. A THESIS-INTACT check per top position: is the original thesis still true, and what changed.
3. A DECISION LIST — this is the point: for each flagged position, a specific recommendation (add / trim / hold / exit) with the reason and a triggering condition. No 'monitor' without a defined trigger and review date.
4. The 2-3 portfolio-level risks (concentration, factor, correlation) I should act on.

Why this structure works

Portfolio reviews rot into a parking lot of 'keep watching'; forcing a per-position decision with a trigger and a review date gives the review a named mechanism instead of a to-do that never resolves.

On Pro, the decision framework arrives in your sizing and risk conventions (max weights, trim discipline) from the profile you set once.

When to use it — and when not to

Reach for it when

• The quarter closed and you want a structured attribution plus a concrete trim/add decision list, not another parking-lot review.
• You can actually supply the inputs it asks for ([PASTE POSITIONS]) — this prompt is an amplifier for real context, not a substitute for it.
• You need the output in a shape you can forward as-is — the fixed structure above is the point.

Skip it when

• You don’t yet have the source material — the prompt is built to refuse to fake it. Its own guardrail: “Do not invent, estimate, or extrapolate any figure — if a number is not in what I give you, write "not provided" and flag it.” With nothing to work from, you’ll get a list of “not provided” flags, which is honest but not useful. Collect the inputs first.
• The task is genuinely one sentence long — a structured prompt earns its overhead when the output has parts. For quick one-off questions, just ask.

Adapting today’s prompt for adjacent roles

“Quarterly attribution + trim/add decision list” sits in the Investment Management lane of the finance pool. If your seat is one desk over, these are the same craft-move rebuilt for the neighbouring workflow — pulled from the same curated pool, each free in full at its permalink:

You are a leveraged-finance associate reviewing a DEBT TERM SHEET I paste: [PASTE TERM SHEET / CREDIT-AGREEMENT SUMMARY: tranches, pricing, covenants, baskets].…

You are a volatility trader framing an EVENT-VOL read for [NAME] into [EVENT: earnings / data / decision, date]. Using only figures I paste, produce: 1. An…

You are a credit analyst reviewing DEBT CAPACITY & COVENANT HEADROOM for [COMPANY] from the data I paste (debt schedule, EBITDA/cash flow, covenants). Produce: 1. A…

Common failure modes (and the fixes)

• Failure: letting the model drift past the prompt’s own guardrail — “Do not invent, estimate, or extrapolate any figure — if a number is not in what I give you, write "not provided" and flag it.” Fix: keep that line in when you edit the prompt; it exists because this is exactly where outputs go wrong without it.
• Failure: letting the model drift past the prompt’s own guardrail — “Mark every claim I should verify externally before relying on it.” Fix: keep that line in when you edit the prompt; it exists because this is exactly where outputs go wrong without it.
• Failure: letting the model drift past the prompt’s own guardrail — “Never use, infer, or request material non-public information (MNPI) or client-confidential data.” Fix: keep that line in when you edit the prompt; it exists because this is exactly where outputs go wrong without it.
• Failure: filling [PASTE POSITIONS] with a vague summary. The output can only be as specific as this input — generic context in, generic deliverable out. Fix: paste raw specifics (real names, real numbers, real constraints), then trim the model’s output, not your input.
• Failure: accepting the first pass. Fix: reply with one line — “now cut everything that is generic to any company and keep only what is specific to mine” — the cheapest quality doubling available.

Quick answers

Is “Quarterly attribution + trim/add decision list” free to use?

Yes — every weekday issue of the PromptSharp Finance publishes one full pool prompt free on the web, and it stays free in the archive. Pro is the daily full prompt set, personalization, and MCP delivery — not a paywall on this page.

Which AI model does this prompt work with?

Any of them. Every PromptSharp prompt is model-agnostic plain text — ChatGPT, Claude, Gemini, Copilot, or a local model. No plugins, no custom GPTs; paste and run.

How is the finance prompt of the day chosen?

Deterministic rotation over the curated finance pool — currently 75 prompts across 5 sections — the same single source the paid brief reads. Same date, same prompt: the archive never silently changes under you.

What goes in the [BRACKETED] placeholders?

Your context — the walkthrough above covers each one. The short rule: the more concrete the fill (real names, numbers, constraints), the sharper the output. Save your details once at /profile and web copies arrive pre-filled.

How do I get this in my inbox instead?

The capture form above — PromptSharp Finance status is honest: live briefs send every weekday; pre-launch verticals email their free list the day the email edition starts.

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