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Closes #016 - Deploy Native KaTeX Rig & Dual-Handbook System

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Antigravity Agent
2026-06-13 15:16:57 +02:00
parent 59e0a04bfa
commit 94ccf63a38
26 changed files with 1074 additions and 137 deletions
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28
components/modules/events/EconometricsMathModal.tsx
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@@ -26,7 +26,7 @@ export default function EconometricsMathModal({ isOpen, onClose }: EconometricsM
if (!isOpen) return null;
return (
<div className="fixed inset-0 z-50 flex items-center justify-center bg-slate-955/90 backdrop-blur-md p-4 sm:p-6 md:p-8">
<div className="fixed inset-0 z-50 flex items-center justify-center bg-slate-950/90 backdrop-blur-md p-4 sm:p-6 md:p-8">
<div className="bg-slate-900 border border-slate-800/80 rounded-3xl w-full max-w-4xl h-[80vh] flex flex-col overflow-hidden shadow-2xl relative text-slate-350">
{/* Modal Header */}
@@ -61,7 +61,7 @@ export default function EconometricsMathModal({ isOpen, onClose }: EconometricsM
If an active event's date is in the past:
</p>
<ul className="list-disc pl-5 text-xs text-slate-400 space-y-1">
<li>FMP API fetches relative prices $P_t$ for $t \in [T-30, T+30]$ (60-day historical window).</li>
<li>FMP API fetches relative prices <InlineMath math="P_t" /> for <InlineMath math="t \in [T-30, T+30]" /> (60-day historical window).</li>
<li>Asset curves and the user's manual score are frozen under <code className="bg-slate-950 px-1 py-0.5 rounded text-[10px] text-slate-300">archivedEvents</code> in <code className="bg-slate-950 px-1 py-0.5 text-slate-300 rounded text-[10px]">econometrics_storage.json</code>.</li>
<li>Future edits to the active matrix will <strong>never</strong> modify archived price vectors.</li>
</ul>
@@ -70,10 +70,10 @@ export default function EconometricsMathModal({ isOpen, onClose }: EconometricsM
<div className="space-y-3">
<h4 className="text-xs font-bold text-rose-400 uppercase tracking-wider font-mono">B. Endogenous Calibration</h4>
<p className="text-xs leading-relaxed text-slate-400">
Active future matrix cells pre-fill suggested scores by looking up the corresponding historical LMM coefficient <InlineMath math="\\beta_{\\text{asset}\\_\\text{event}\\_\\text{post}}" /> and scaling it to our native score scale:
Active future matrix cells pre-fill suggested scores by looking up the corresponding historical LMM coefficient <InlineMath math="\beta_{\text{asset}\_\text{event}\_\text{post}}" /> and scaling it to our native score scale:
</p>
<div className="bg-slate-950/40 p-4 rounded-xl border border-slate-800/60 my-2">
<BlockMath math="\\text{Score}_{\\text{suggested}} = \\max\\left(-3, \\min\\left(3, \\text{Round}(\\beta_{\\text{estimate}} \\times 100)\\right)\\right)" />
<BlockMath math="\text{Score}_{\text{suggested}} = \max\left(-3, \min\left(3, \text{Round}(\beta_{\text{estimate}} \times 100)\right)\right)" />
</div>
</div>
@@ -83,17 +83,17 @@ export default function EconometricsMathModal({ isOpen, onClose }: EconometricsM
The engine estimates direct event drift and impact returns, isolating asset-level intercepts as random deviances and purging macro volatility using VIX indices:
</p>
<div className="bg-slate-950/40 p-4 rounded-xl border border-slate-800/60 my-2">
<BlockMath math="Y_{it} = X_{it}\\beta + Z_{it}b_i + \\varepsilon_{it}" />
<BlockMath math="Y_{it} = X_{it}\beta + Z_{it}b_i + \varepsilon_{it}" />
<p className="text-[11px] text-slate-400 mt-2 font-mono leading-relaxed">
{"Where:"}
<br />
{"- "}<InlineMath math="Y_{it}" />{" is the log-return "}<InlineMath math="\\ln(P_t/P_0)" />{" of asset "}<InlineMath math="i" />{" at relative index "}<InlineMath math="t \\in [-30, 30]" />{"."}
{"- "}<InlineMath math="Y_{it}" />{" is the log-return "}<InlineMath math="\ln(P_t/P_0)" />{" of asset "}<InlineMath math="i" />{" at relative index "}<InlineMath math="t \in [-30, 30]" />{"."}
<br />
{"- "}<InlineMath math="X_{it}" />{" design matrix elements isolate Pre-Event Drift ("}<InlineMath math="t < 0" />{") and Post-Event Impact ("}<InlineMath math="t \\ge 0" />{") while controlling for systemic covariates (VIX)."}
{"- "}<InlineMath math="X_{it}" />{" design matrix elements isolate Pre-Event Drift ("}<InlineMath math="t < 0" />{") and Post-Event Impact ("}<InlineMath math="t \ge 0" />{") while controlling for systemic covariates (VIX)."}
<br />
{"- "}<InlineMath math="b_i \\sim N(0, \\sigma_b^2)" />{" random intercept captures unique baseline asset variance."}
{"- "}<InlineMath math="b_i \sim N(0, \sigma_b^2)" />{" random intercept captures unique baseline asset variance."}
<br />
{"- "}<InlineMath math="\\varepsilon_{it} \\sim N(0, \\sigma^2)" />{" residuals noise."}
{"- "}<InlineMath math="\varepsilon_{it} \sim N(0, \sigma^2)" />{" residuals noise."}
</p>
</div>
</div>
@@ -106,15 +106,15 @@ export default function EconometricsMathModal({ isOpen, onClose }: EconometricsM
<div className="bg-slate-950/40 p-4 rounded-xl border border-slate-800/60 my-2 space-y-4">
<div>
<p className="text-xs text-slate-400 mb-1">Logistic Probability Projection:</p>
<BlockMath math="P(\\text{Bullish}) = \\frac{1}{1 + e^{-\\text{Score}}}" />
<BlockMath math="P(\text{Bullish}) = \frac{1}{1 + e^{-\text{Score}}}" />
</div>
<div>
<p className="text-xs text-slate-400 mb-1">Optimal Youden Index (J):</p>
<BlockMath math="J = \\text{Sensitivity} + \\text{Specificity} - 1 = \\text{TPR} + (1 - \\text{FPR}) - 1" />
<BlockMath math="J = \text{Sensitivity} + \text{Specificity} - 1 = \text{TPR} + (1 - \text{FPR}) - 1" />
</div>
<div>
<p className="text-xs text-slate-400 mb-1">{"Inverting probability optimal threshold "}<InlineMath math="P^*" />{" back to native score "}<InlineMath math="S^*" />{" via Logit:"}</p>
<BlockMath math="S^* = \\ln\\left(\\frac{P^*}{1 - P^*}\\right)" />
<BlockMath math="S^* = \ln\left(\frac{P^*}{1 - P^*}\right)" />
</div>
</div>
</div>
@@ -126,7 +126,7 @@ export default function EconometricsMathModal({ isOpen, onClose }: EconometricsM
</p>
<div className="bg-slate-950/40 p-4 rounded-xl border border-slate-800/60 my-2 space-y-4">
<div>
<BlockMath math="\\hat{S}(t) = \\prod_{t_i \\le t} \\left(1 - \\frac{d_i}{n_i}\\right)" />
<BlockMath math="\hat{S}(t) = \prod_{t_i \le t} \left(1 - \frac{d_i}{n_i}\right)" />
<p className="text-[11px] text-slate-400 mt-2 font-mono leading-relaxed">
{"Where:"}
<br />
@@ -137,7 +137,7 @@ export default function EconometricsMathModal({ isOpen, onClose }: EconometricsM
</div>
<div>
<p className="text-xs text-slate-400 mb-1">Reversal trigger with 1% Volatility Buffer:</p>
<BlockMath math="\\text{Sign}(\\text{Score}) \\times \\text{Return} \\le -0.01" />
<BlockMath math="\text{Sign}(\text{Score}) \times \text{Return} \le -0.01" />
</div>
</div>
</div>