/position-ladder

description: Plan a staged position — entry ladder, share-count floor/ceiling, and the trim/re-add cycle that lowers average cost — with lot accounting, wash-sale checks, total-return honesty, and a thesis-break exit gate

Position Ladder — Staged Entry & Cost-Basis Management

⚠️ Data Verification — Do This Before Any Analysis

Before running any analysis, always retrieve the latest market data for the ticker:

1. **Fetch current price** — use web search or ask the user for the live price, 52-week range, and market cap. Never assume a price from training data. 2. **Confirm key figures** — recent earnings, revenue, key ratios (P/E, P/S, etc.) as applicable to this skill. 3. **State your data source** — fill in the `Data & Sources` header (next section) so the origin, as-of date, retrieval path, and confidence of every figure are explicit at the top of the output. 4. **Flag stale data explicitly** — if live data is unavailable, display this warning before proceeding:

> ⚠️ **Live data unavailable.** The following analysis uses training-data estimates which may be significantly out of date. Verify all prices and metrics before making any decisions.

Never silently substitute training-data estimates for current prices. When in doubt, ask the user to paste the latest quote.

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📋 Data & Sources Header — Open Every Output With It

The first thing in the output is this provenance block, filled in — never left as placeholders. It is the standard documented on the [Data & Accuracy](https://yennanliu.github.io/InvestSkill/data-and-accuracy.html) page and the first thing `result-validator` looks for:

Data & Sources
  As of:      <date the figures represent, e.g. 2026-06-30>
  Source:     <primary docs — SEC EDGAR 10-K/10-Q, company IR, FRED, exchange data …>
  Retrieval:  <pasted by user | web/tool retrieval | model memory>
  Confidence: <HIGH | MEDIUM | LOW>

• `Retrieval: model memory` must be paired with `Confidence: LOW` — memory is a placeholder until confirmed against a primary source.
• Mixed sources: list each with its own as-of date rather than blending them.
• Sources disagree on the same figure (a closing price, a deal term): prefer the primary source (SEC filing, company release, exchange data) over an aggregator, then the most recent dated one. Show both values with their sources and dates, say which you used and why, and never average them.
• Data the user pasted is reported as `pasted by user`; do not upgrade its confidence beyond what the user's own source supports.

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⚠️ Read This First — This Is Scenario Modeling, Not a Recommendation

This framework is **more prescriptive than the rest of the InvestSkill catalog**: it outputs specific price levels and share counts. Every number it produces is a **conditional plan under stated assumptions**, not an instruction to trade.

Three honest claims must appear in every output:

1. **Lowering average cost is not the same as making money.** Average cost is an accounting anchor and a psychological one — it is not a return metric. Trimming a high-cost lot mechanically lowers the number without creating a dollar of wealth. Always report **total return and realized P&L alongside average cost**, and show the buy-and-hold comparison. 2. **This is volatility harvesting.** The strategy monetizes oscillation around a level. It **outperforms in a range-bound / mean-reverting tape and underperforms in a strong trend** — in either direction. A stock that only goes up leaves the ladder underfilled; a stock that only goes down fills it and keeps falling. 3. **Position control is the actual edge.** The hard ceiling on share count — "stop adding at N shares, no matter what" — is what converts averaging down from an unbounded liability into a bounded, pre-sized bet. Without the cap, this is not a strategy; it is a mechanism for concentrating capital into losers.

State all three, then produce the plan. Never present the ladder as a way to guarantee a recovery.

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Overview

Answer the question the rest of the catalog does not: **"I own this — now what is my execution plan?"**

The other frameworks decide *what* to own (`stock-eval`, `fundamental-analysis`), *what it is worth* (`stock-valuation`, `dcf-valuation`), and *when* to enter (`technical-analysis`). None of them manages a position across its life. This one does. It takes a holding — or a planned holding — and produces:

• A **share-count band**: a floor (core position you always keep) and a ceiling (the hard cap on adding).
• An **entry ladder**: pre-committed rungs between today's price and the bottom of the build zone, with the size of each.
• A **trim/re-add cycle**: sell the highest-cost lots when price trades above blended average cost, buy them back below it, oscillating inside the band.
• The **accounting truth**: capital at full deployment, blended average cost at each stage, realized vs. unrealized P&L, wash-sale exposure, and the total-return comparison against simply holding.
• A **thesis-break gate**: the conditions under which the correct action is to stop laddering and exit.

This is distinct from `portfolio-review`, which operates *across* holdings (allocation, drift, concentration, tax-loss harvesting). This one operates *inside a single holding*. Use `portfolio-review` to decide how big the position may be; use this skill to decide how to get there and how to manage it once there.

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1. Inputs

Collect these before modeling. Ask for anything missing rather than assuming — the plan is only as good as the position cap.

| Input | Required | Default if unstated | |-------|----------|---------------------| | Ticker | ✅ | — | | Current shares held and average cost | ✅ (or 0 for a new position) | — | | Live market price | ✅ | fetch, or ask | | Ceiling: max shares **or** max % of portfolio **or** max dollars | ✅ | ask — never invent a cap | | Floor: the core position never sold | — | 60% of ceiling | | Portfolio size (for the concentration check