feat: strategy builder
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@@ -285,15 +285,30 @@ def payoff_curves(
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entry_ref = priced["entry_cost"]
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lo, hi = spot * 0.6, spot * 1.4
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prices = np.linspace(lo, hi, n)
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# A calendar/ratio spread's payoff can spike sharply right at a strike — a plain
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# uniform sweep over the full 0.6x-1.4x range (n points) can straddle right over that
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# peak without ever sampling it (same issue fixed in check_bounded_risk). Blend a
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# coarse baseline (overall shape) with a dense window around the legs' own strikes.
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baseline = np.linspace(lo, hi, n)
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strikes = [l["strike"] for l in legs]
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lo_k, hi_k = max(min(strikes) * 0.9, lo), min(max(strikes) * 1.1, hi)
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near_strikes = np.linspace(lo_k, hi_k, n * 3)
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prices = np.unique(np.concatenate([baseline, near_strikes]))
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prices.sort()
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eval_days_expiry = min(l["days_to_expiry"] for l in legs)
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# Both curves share the scenario's volatility view (surface_scenario) — only the
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# evaluation DATE differs: "à échéance" prices the day the near leg expires (matching
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# the Max gain/Max perte tile, itself computed with surface_scenario for the same
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# reason — see check_bounded_risk), "à J+8" prices your chosen scenario horizon. Using
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# surface_now here instead would silently mix in today's un-shocked vol, producing a
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# curve whose peak doesn't match the Max gain tile right next to it.
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at_expiry = [
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{"underlying": round(float(p), 2), "pnl": round(float(value_at(legs, float(p), eval_days_expiry, surface_now, r, contract_size) - entry_ref), 2)}
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{"underlying": round(float(p), 4), "pnl": round(float(value_at(legs, float(p), eval_days_expiry, surface_scenario, r, contract_size) - entry_ref), 2)}
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for p in prices
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]
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at_scenario = [
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{"underlying": round(float(p), 2), "pnl": round(float(value_at(legs, float(p), horizon_days, surface_scenario, r, contract_size) - entry_ref), 2)}
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{"underlying": round(float(p), 4), "pnl": round(float(value_at(legs, float(p), horizon_days, surface_scenario, r, contract_size) - entry_ref), 2)}
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for p in prices
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]
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return {"at_expiry": at_expiry, "at_scenario": at_scenario, **priced}
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@@ -72,14 +72,14 @@ function PayoffChart({ priced, spot, scenarioSpot }: { priced: PriceCombo; spot:
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tickFormatter={(v) => `${v}`} />
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<Tooltip
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contentStyle={{ background: '#0f1623', border: '1px solid #1e2d4d', fontSize: 11 }}
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labelFormatter={(v) => `Sous-jacent: ${Number(v).toFixed(2)}`}
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labelFormatter={(v) => `Sous-jacent: ${Number(v).toFixed(decimals)}`}
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formatter={(v: number, name: string) => [fmtMoney(v), name]}
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/>
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<Legend wrapperStyle={{ fontSize: 11 }} />
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<ReferenceLine y={0} stroke="#475569" strokeDasharray="4 4" />
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<ReferenceLine x={spot} stroke="#3b82f6" strokeDasharray="2 2" label={{ value: 'Spot', fill: '#3b82f6', fontSize: 9, position: 'top' }} />
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<ReferenceLine x={scenarioSpot} stroke="#f59e0b" strokeDasharray="2 2" label={{ value: 'Scénario J+8', fill: '#f59e0b', fontSize: 9, position: 'insideTopRight' }} />
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<Line type="monotone" dataKey="expiry" name="À échéance" stroke="#3b82f6" strokeWidth={2} dot={false} />
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<Line type="monotone" dataKey="expiry" name="À échéance jambe proche" stroke="#3b82f6" strokeWidth={2} dot={false} />
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<Line type="monotone" dataKey="scenario" name="À J+8 (scénario)" stroke="#f59e0b" strokeWidth={2} dot={false} />
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</LineChart>
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</ResponsiveContainer>
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@@ -818,6 +818,9 @@ export default function StrategyBuilder() {
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<div className="card">
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<div className="stat-label mb-2">Diagramme payoff</div>
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<PayoffChart priced={priced} spot={priced.spot} scenarioSpot={priced.scenario_spot} />
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<p className="text-[11px] text-slate-500 mt-1">
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Les deux courbes utilisent la même vue de volatilité (celle du scénario) — seule la date diffère : bleu = à l'échéance de la jambe la plus proche, orange = à J+{horizonDays}.
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</p>
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</div>
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<div className="grid grid-cols-2 md:grid-cols-4 gap-3">
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