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feat: strategy builder

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OpenSquared
2026-07-19 10:00:17 +02:00
parent 3417bb6075
commit 0cf6a68d2d
2 changed files with 23 additions and 5 deletions
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21
backend/services/strategy_engine.py
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@@ -285,15 +285,30 @@ def payoff_curves(
entry_ref = priced["entry_cost"]
lo, hi = spot * 0.6, spot * 1.4
prices = np.linspace(lo, hi, n)
# A calendar/ratio spread's payoff can spike sharply right at a strike — a plain
# uniform sweep over the full 0.6x-1.4x range (n points) can straddle right over that
# peak without ever sampling it (same issue fixed in check_bounded_risk). Blend a
# coarse baseline (overall shape) with a dense window around the legs' own strikes.
baseline = np.linspace(lo, hi, n)
strikes = [l["strike"] for l in legs]
lo_k, hi_k = max(min(strikes) * 0.9, lo), min(max(strikes) * 1.1, hi)
near_strikes = np.linspace(lo_k, hi_k, n * 3)
prices = np.unique(np.concatenate([baseline, near_strikes]))
prices.sort()
eval_days_expiry = min(l["days_to_expiry"] for l in legs)
# Both curves share the scenario's volatility view (surface_scenario) — only the
# evaluation DATE differs: "à échéance" prices the day the near leg expires (matching
# the Max gain/Max perte tile, itself computed with surface_scenario for the same
# reason — see check_bounded_risk), "à J+8" prices your chosen scenario horizon. Using
# surface_now here instead would silently mix in today's un-shocked vol, producing a
# curve whose peak doesn't match the Max gain tile right next to it.
at_expiry = [
{"underlying": round(float(p), 2), "pnl": round(float(value_at(legs, float(p), eval_days_expiry, surface_now, r, contract_size) - entry_ref), 2)}
{"underlying": round(float(p), 4), "pnl": round(float(value_at(legs, float(p), eval_days_expiry, surface_scenario, r, contract_size) - entry_ref), 2)}
for p in prices
]
at_scenario = [
{"underlying": round(float(p), 2), "pnl": round(float(value_at(legs, float(p), horizon_days, surface_scenario, r, contract_size) - entry_ref), 2)}
{"underlying": round(float(p), 4), "pnl": round(float(value_at(legs, float(p), horizon_days, surface_scenario, r, contract_size) - entry_ref), 2)}
for p in prices
]
return {"at_expiry": at_expiry, "at_scenario": at_scenario, **priced}