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Claude Opus 5.5 (effort default (no --effort flag) · thinking on) on Discounted cash flow valuation with mid-year option and a sensitivity grid

AClaude Opus 5.5default · thinking on · Claude Code 2.1.299 (headless -p) · cloud · 2026-10-20 · by @bobsiopener

Trust 80%Fully autonomoussuccess · first try
Estimated cost
$0.12
Wall time
23s
Human step-ins
0
Outcome
Pass

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Summary

Exact prompt

# Discounted cash flow valuation with a sensitivity grid `input.json` gives forecast free cash flows and valuation assumptions for a fictional company (synthetic). Write `solve.py` (Python 3 standard library only) so that `python solve.py input.json answer.json` computes the valuation. We re-run it on fresh inputs, so do not hard-code anything. ## Input `fcf` (forecast free cash flow for years 1..N), `wacc`, `terminal_growth`, `mid_year` (bool), `net_debt` (can be negative = net cash), `shares`, `ebitda_last` (year-N EBITDA), `sens_wacc`, `sens_growth` (lists). ## Rules 1. Discount year t (t = 1..N) by (1 + wacc) ** t, or by (1 + wacc) ** (t - 0.5) when `mid_year` is true. `pv_fcf` = sum of discounted cash flows. 2. Terminal value (Gordon growth, at the end of year N): `terminal_value` = fcf_N * (1 + g) / (wacc - g). It is always discounted by (1 + wacc) ** N, even with the mid-year convention: `pv_terminal`. 3. `enterprise_value` = pv_fcf + pv_terminal; `equity_value` = enterprise_value - net_debt; `per_share` = equity_value / shares; `terminal_share` = pv_terminal / enterprise_value; `implied_ev_ebitda` = enterprise_value / ebitda_last. 4. If terminal_growth >= wacc, the whole answer is `{"error": "growth_not_below_wacc"}`. 5. `sensitivity`: a list with one row per value in `sens_wacc` (same order); each row has one entry per value in `sens_growth`: the per-share value with that wacc and growth (other inputs unchanged), rounded to 4 decimals, or `null` when growth >= wacc. 6. Round money values to 2 decimals and `per_share`, `terminal_share`, `implied_ev_ebitda` to 6 decimals when writing. ## Output `answer.json` keys: `pv_fcf`, `terminal_value`, `pv_terminal`, `enterprise_value`, `equity_value`, `per_share`, `terminal_share`, `implied_ev_ebitda`, `sensitivity`. ## Scoring Hidden checks (partial credit = fraction passed; all must pass): `pv_of_cash_flows`, `terminal_value`, `ev_equity_per_share` (money within 0.011, the three ratios within 0.000001), `sensitivity_grid` (within 0.0001, nulls exact) on the given input; `fresh_end_of_year` and `fresh_mid_year` (the whole answer, tolerance 0.011); `growth_not_below_wacc` (rule 4). Each run has a 60-second limit.

Mid-year discounting of cash flows but not of the terminal value, net cash vs net debt, null cells where growth >= discount rate, and the error case. Original benchmark task written for usecaserank.com (not based on a specific public post). Headless, offline run on a reproducible fixture. Each run's notes say how its cost was measured (estimates are marked).

These are synthetic test cases for comparing AI models, not financial advice.

Success criteria: 1. pv_of_cash_flows 2. terminal_value 3. ev_equity_per_share 4. sensitivity_grid 5. fresh_end_of_year 6. fresh_mid_year 7. growth_not_below_wacc

Setup notes: Use Case Scout batch 9 case j10-dcf-valuation (offline fixture). Prepared with batch9/prepare.sh; hidden key/tests kept outside the agent's work dir. Prompt = TASK.md verbatim. Scored with the scout's scorer: `python score.py WORKDIR KEYDIR`. Tools: Read/Write/Edit/Glob/Grep/Bash, web disabled. Single run, no retries. Claude Code's own reported cost for claude-opus-5.5: $0.1161. Score: 7/7. Cost is an ESTIMATE: measured tokens x pricing.json list price (Claude Pro subscription, nothing billed); input_tokens include cache reads and writes. Single run.

Estimated cost List-price estimate; not actually billed.

Metrics

Estimated cost
$0.12
Wall time
23s
Human step-ins
0
Turns
4
Model usage
ModelInput tokOutput tokCost
AClaude Opus 5.5anthropic/claude-opus-5.5effort default (no --effort flag) · thinking on57,7351,954$0.12

Reproduce this run

  1. Use the use case prompt on the use case page.
  2. Same setup: Claude Opus 5.5 (anthropic/claude-opus-5.5, effort default (no --effort flag) · thinking on) via Claude Code 2.1.299 (headless -p), cloud.
  3. It counts as a success only if it meets every success criterion: 1. pv_of_cash_flows 2. terminal_value 3. ev_equity_per_share 4. sensitivity_grid 5. fresh_end_of_year 6. fresh_mid_year 7. growth_not_below_wacc
  4. Log model, tokens, wall time, human step-ins and the evidence log, then submit it as a reproduction. A different model? Submit a head-to-head rerun.

How runs are scored: Methodology.

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Automated checks

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Evidence log
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  "result": "I wrote `solve.py` and ran it on `input.json`. It produced `answer.json` with every key the spec asks for.\n\n**Results on the given input** (mid-year convention is on):\n\n| Key | Value |\n|---|---|\n| `pv_fcf` | 2,105.26 |\n| `terminal_value` | 5,896.57 |\n| `pv_terminal` | 2,337.13 |\n| `enterprise_value` | 4,442.39 |\n| `equity_value` | 3,193.69 |\n| `per_share` | 11.101156 |\n| `terminal_share` | 0.526098 |\n| `implied_ev_ebitda` | 5.913727 |\n\n- **Sensitivity grid:** it's 5\u00d75, and the centre cell (wacc 10.83%, growth 2.5%) is 10.4721. The 11.83% growth column is `null` in the first four rows because growth isn't below wacc there. In the last row (wacc 12.83%) it shows 60.4644, which is correct but much larger than the cells next to it, since wacc minus growth is only 1%.\n- **Error case:** a test input with growth equal to wacc returned `{\"error\": \"growth_not_below_wacc\"}`.\n\nI haven't checked the numbers against an independent calculation; the run shows the script works but not that every figure is right.\n\nThe script takes all of its values from the input file and uses only the standard library. If `enterprise_value` or `ebitda_last` is zero, it writes `null` for the ratio instead of crashing.",
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