dodoxandClaude Sonnet 5
c4178fe779
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>
14 lines
566 B
Python
14 lines
566 B
Python
"""Daily exchange price/volume series from FIO's cxpc candles, shared by tools/history.py and
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tools/undervalued.py."""
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import datetime
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from . import fio
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def daily_prices(tk: str, cx: str) -> dict:
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"""date -> (VWAP price, units traded) for days with trades, from FIO cxpc DAY_ONE candles."""
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out = {}
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for e in fio.cxpc(tk, cx):
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if e.get("Interval") == "DAY_ONE" and e.get("Traded"):
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out[datetime.datetime.fromtimestamp(e["DateEpochMs"] / 1000, datetime.timezone.utc).date()] = (e["Volume"] / e["Traded"], e["Traded"])
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return out
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