dodoxandClaude Sonnet 5
58db08b921
- puga/network.py + tools/network.py: model a multi-base chain (e.g. mine LST at one base, ship it, consume it at another). Simulates each base independently, nets a transferred material's producer-surplus against consumer-need, charges real freight only on what's moved, cm_free for a founding covered by a Core Module Kit. Worked example in plans/chains/. - puga/saturation.py: real price-band filtering. FIO's order_book NarrowPriceBandLow/High and WidePriceBandLow/High match APEX's own displayed Price Band exactly (verified live) - an order outside it is a stale artifact, not just uncompetitive. Added in_band() and effective_demand(); effective_supply() gained the same hard band filter alongside its existing soft vwap-proximity filter (renamed that param mult to free up `band`). Wired into tools/scan.py stage 2 in place of the raw, unfiltered demand figure. Was flagged as an unimplemented refinement in saturation-design.md since the original design review. - tools/sell.py: self-contained tranche split (aggressive tranche capped at a volume quantile, median normally or 80th pct with --tight when a payment is imminent and stockout risk outweighs margin; patient tranche priced under the next competitor tier). Instant-bid comparison moved behind --show-bid (off by default). - Docs and roadmap updated accordingly. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
86 lines
4.6 KiB
Python
Executable File
86 lines
4.6 KiB
Python
Executable File
#!/usr/bin/env python3
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"""Where to post a sell order and how long it should take to clear, vs hitting the bids now.
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Formalizes the by-hand check done before every AL/BHP sale, including the tranche split: an
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aggressive (undercut) tranche sized to a quantile of daily volume so it's confident to clear
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today, and a patient tranche (priced just under the next competitor tier) for the rest. The
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quantile is the newsvendor critical fractile Cu/(Cu+Co): median (0.5) when the cost of running
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out of cash (Cu) and the cost of discounting unnecessarily (Co) are about equal; higher (0.8 via
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--tight) when Cu dominates, i.e. a restock/buildout payment is imminent and stockout risk (not
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having cash in time) matters more than a few points of margin.
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puga sell BHP 8 --cx AI1
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puga sell BHP 11 --tight # cash-tight: bias the split toward the aggressive tranche
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"""
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import argparse, datetime, statistics, sys
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from pathlib import Path
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sys.path.insert(0, str(Path(__file__).resolve().parent.parent))
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from puga import config, fio, market
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def quantile(xs: list[float], q: float) -> float:
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return sorted(xs)[int(q * (len(xs) - 1))] if xs else 0.0
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def tranche_split(qty: float, trades: list[float], tight: bool) -> tuple[float, float]:
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"""(aggressive_qty, patient_qty). Aggressive is capped at qty and at the volume quantile."""
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q = 0.8 if tight else 0.5
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aggressive = min(qty, quantile(trades, q)) if trades else qty
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return aggressive, qty - aggressive
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def daily_traded(tk: str, cx: str, days: int = 30) -> list[float]:
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rows = [(datetime.datetime.fromtimestamp(e["DateEpochMs"] / 1000, datetime.timezone.utc).date(), e["Traded"])
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for e in fio.cxpc(tk, cx) if e.get("Interval") == "DAY_ONE" and e.get("Traded")]
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return [t for _, t in rows[-days:]]
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def main():
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ap = argparse.ArgumentParser()
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ap.add_argument("ticker")
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ap.add_argument("qty", type=float)
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ap.add_argument("--cx", default=config.DEFAULT_CX)
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ap.add_argument("--undercut", type=float, default=10, help="AIC to undercut the current best ask by")
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ap.add_argument("--tight", action="store_true", help="cash-tight: bias the tranche split toward the aggressive (undercut) tranche")
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ap.add_argument("--show-bid", action="store_true", help="also show instant-bid revenue (usually worse than the tranche split; off by default)")
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a = ap.parse_args()
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t = a.ticker.upper()
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ob = fio.order_book(t, a.cx)
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asks = sorted((o["ItemCost"], o["ItemCount"] or 0) for o in ob["SellingOrders"] if o.get("ItemCost"))
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best_ask = asks[0][0] if asks else None
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post = round((best_ask - a.undercut) if best_ask else (ob.get("Ask") or 0))
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ahead = sum(u for p, u in asks if p < post)
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trades = daily_traded(t, a.cx)
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med = statistics.median(trades) if trades else 0
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lo = sorted(trades)[int(0.2 * (len(trades) - 1))] if trades else 0
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hi = sorted(trades)[int(0.8 * (len(trades) - 1))] if trades else 0
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print(f"{t}.{a.cx} best ask {best_ask} bid {ob.get('Bid')} vwap7 {ob.get('PriceAverage')}")
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print(f"\npost {a.qty:g} at {post:.0f} ({ahead:.0f} units ahead of you at a lower price)")
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print(f" revenue if filled: {post * a.qty:,.0f}")
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if med:
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print(f" expected clear time (last {len(trades)}d volume): busy day {24 * a.qty / hi:.1f}h | "
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f"median day {24 * a.qty / med:.1f}h | slow day {24 * a.qty / max(lo, 1):.1f}h")
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else:
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print(" no recent trade history to estimate clear time")
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if a.show_bid:
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hit = market.walk(t, a.cx, a.qty, "sell")
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print(f"\ninstant (hit the bids now): {hit['total']:,.0f} (avg {hit['avg']:.0f}, worst {hit['worst']:.0f}"
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+ (f", SHORT: book only fills {hit['filled']:.0f}" if hit["short"] else "") + ")")
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print(f" posting patiently gains {post * a.qty - hit['total']:,.0f} over this, at the cost of waiting")
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aggr_qty, patient_qty = tranche_split(a.qty, trades, a.tight)
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if patient_qty > 0.01:
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tiers_above = sorted({p for p, u in asks if p > post})
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patient_price = round(tiers_above[0] - 1) if tiers_above else round(post + 2 * a.undercut)
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q_label = "80th pct (tight)" if a.tight else "median"
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print(f"\nTRANCHE SPLIT ({q_label} volume quantile, {len(trades)}d):")
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print(f" aggressive: {aggr_qty:.1f} @ {post:.0f} (confident to clear today)")
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print(f" patient: {patient_qty:.1f} @ {patient_price:.0f} (waits behind the next tier, higher margin)")
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print(f" vs posting all {a.qty:g} at {post:.0f}: gains {patient_qty*(patient_price-post):,.0f} extra if the patient tranche fills")
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if __name__ == "__main__":
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main()
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