Add tools/undervalued.py: trading strategy, goods priced below production cost

Finds manufactured goods currently selling below their implied
production cost (live input cost vs output price) - candidates to buy
and hold for a price-reversion bounce, the mirror of the "is this
worth building" question saturation.py already answers.

Backtested first (326 output tickers, 287 deduplicated dip-onset
episodes across 112 distinct tickers): +3mo forward return mean
+21.3%/median +8.9%/73.2% hit rate at >=10 units/day volume - real
signal, not noise, but only ~0.10-0.24%/day, far below the 14-29%/day
marginal ROI this session's production builds found. Documented
prominently in the tool's own docstring and CLAUDE.md so it doesn't
get mistaken for a primary strategy - it's for excess idle capital
once better-yielding builds are exhausted, not before.

Promoted daily_prices() out of tools/history.py into puga/history.py
so both tools share it, per the self-improve rule.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>

CLAUDE.md

@@ -50,6 +50,7 @@ Run as `puga <tool> ...` (e.g. `puga scan --min-n 3`, `puga plan pull <uuid>`);
 - `tools/network.py <chain.yaml>` models a MULTI-BASE chain (e.g. mine LST at Nike, ship it, make BSE at Deimos): simulates each base, nets a transferred material's producer-surplus against consumer-need, charges real freight only on what's moved (`puga/network.py`). Spec and worked example in `plans/chains/`. `cm_free: true` per base for a new founding covered by a Core Module Kit. profit/day per base is the WHOLE plan, not the marginal addition - diff against the base's plan without the addition for a true marginal ROI.
 - `tools/whatif.py <before.yaml> [--add BUILDING:AMOUNT[:RECIPE]] [--infra HB1:+1] [--after after.yaml]` marginal ROI of adding to a base you already run (whole-plan diff, same rule as buy/runway - pass the WHOLE base, not just the addition). `--add` mutates a copy of `before` in-memory (reuses an existing building's recipe if omitted, e.g. `--add POL:1`); `--after` takes a second full spec instead. Flags any workforce tier the addition newly overloads (vs. a pre-existing one, which it won't flag) - this is what caught the PP2/pioneer-housing and 2nd-CHP/pioneer-housing surprises by hand before this tool existed.
 - `tools/runway.py <spec.yaml|--uuid U> [--no-inbound]` days of runway per material before a base stalls: real NET consumption via `simulate()` (self-produced inputs excluded), base storage, PLUS (by default) any ship currently flying to that planet, auto-detected from live flight data (`tools/state.py` tags each ship with its flight origin/destination). Pass the WHOLE base plan (see `docs/library.md`).
+- `tools/undervalued.py [--cx AI1] [--min-vol 5] [--top 20]` manufactured goods currently priced below implied production cost - buy-and-hold-for-reversion candidates, not build candidates. **Expected ROI is much lower than production builds** (~0.10-0.24%/day backtested, vs 14-29%/day for the builds this toolkit recommends) - only worth it for excess idle capital once better-yielding builds are exhausted. Library: `puga/undervalued.py`.
 - `tools/chain.py TICKER` make-vs-buy cost tree plus sourcing depth of inputs. `--consumers` flips it: what recipes EAT this ticker as an input, with each output's market depth - for "is there a deeper downstream product worth chaining into" questions (e.g. checking BOR/BSE/BBH for further processing).
 - `tools/planet.py RESOURCE [--min-factor X] [--from PLANET] [--top N]` ranks planets for a raw resource by extraction factor, with founding cost straight from FIO's own `BuildRequirements` (real environment-extras materials, not guessed temperature/pressure thresholds - PRUNplanner's own calculations don't model those either) and optional jump distance via `tools/route.py`. Pure-factor ranking alone is misleading - the best-factor planets are often thousands of ly away; always pass `--from` an existing base. Library: `puga/planet.py`.
 - `tools/route.py <from planet/system> <to planet/system>` jump-distance route (not a PRUNplanner feature - built from FIO's `/systemstars` graph, Dijkstra by straight-line ly since that's what FTL fuel/time scale with, jump count reported alongside). Accepts planet natural IDs, system natural IDs, or names. Library: `puga/route.py`.