feat: deliver multi-asset analytics, OCR exchange selection, and heatmap UX

Add asset-type aware market/overview flows, portfolio OCR reverse-engineering with exchange overrides, and interactive index heatmap features. Update README with recent updates and wire backend/frontend APIs for FX matrix, exchange options, and improved portfolio editing flows.

Made-with: Cursor

atlas-terminal/README.md

@@ -25,3 +25,10 @@ npm run dev
 - **Frontend:** Next.js 14, TypeScript, Tailwind CSS, TradingView Lightweight Charts
 - **Backend:** FastAPI, Python 3.12+, yfinance, yahooquery, Google Gemini
 - **Database:** SQLite (local) / PostgreSQL (production)
+
+## Recent Updates
+
+- Added multi-asset analysis branching across Overview/Research/Valuation/Earnings for equity, ETF, and commodity futures.
+- Implemented commodity and ETF market widgets, plus index-level stock heatmap with interactive index switching.
+- Upgraded portfolio OCR with reverse-engineering logic, exchange selection (including SMSN -> `SMSN.L`), and inline edit/delete flows.
+- Added portfolio exchange-aware recalculation and FX conversion matrix support for multi-currency display.

atlas-terminal/apps/web/src/app/components/markets/HeatmapSection.tsx

@@ -0,0 +1,119 @@
+"use client";
+
+import { useEffect, useMemo, useState } from "react";
+
+type HeatmapStock = {
+  ticker: string;
+  name: string;
+  sector: string;
+  market_cap: number;
+  change_pct: number;
+};
+
+const INDEX_OPTIONS = [
+  { id: "sp500", label: "S&P 500" },
+  { id: "nasdaq100", label: "NASDAQ 100" },
+  { id: "kospi", label: "KOSPI" },
+  { id: "ftse100", label: "FTSE 100" },
+];
+
+export function HeatmapSection({
+  selectedIndex,
+  onSelectIndex,
+}: {
+  selectedIndex: string;
+  onSelectIndex: (v: string) => void;
+}) {
+  const [stocks, setStocks] = useState<HeatmapStock[]>([]);
+  const [loading, setLoading] = useState(false);
+
+  useEffect(() => {
+    setLoading(true);
+    fetch(`/api/markets/heatmap/${selectedIndex}?top_n=50`)
+      .then((r) => (r.ok ? r.json() : null))
+      .then((d) => setStocks(Array.isArray(d?.stocks) ? d.stocks : []))
+      .finally(() => setLoading(false));
+  }, [selectedIndex]);
+
+  const grouped = useMemo(() => {
+    const sectors: Record<string, HeatmapStock[]> = {};
+    for (const s of stocks) {
+      const k = s.sector || "Other";
+      if (!sectors[k]) sectors[k] = [];
+      sectors[k].push(s);
+    }
+    return sectors;
+  }, [stocks]);
+
+  const totalMcap = stocks.reduce((sum, s) => sum + (s.market_cap || 0), 0);
+
+  return (
+    <div id="heatmap-section" className="bg-bg-card border border-border rounded-lg p-4">
+      <div className="heatmap-header">
+        <h3 className="text-text-secondary text-sm font-semibold">Stock Heatmap</h3>
+        <div className="index-toggle">
+          {INDEX_OPTIONS.map((idx) => (
+            <button
+              key={idx.id}
+              className={`index-btn ${selectedIndex === idx.id ? "active" : ""}`}
+              onClick={() => onSelectIndex(idx.id)}
+            >
+              {idx.label}
+            </button>
+          ))}
+        </div>
+      </div>
+
+      {loading ? (
+        <div className="heatmap-loading">Loading heatmap...</div>
+      ) : (
+        <div className="treemap-container">
+          {Object.entries(grouped).map(([sector, sectorStocks]) => {
+            const sectorMcap = sectorStocks.reduce((s, st) => s + (st.market_cap || 0), 0);
+            const sectorPct = totalMcap > 0 ? (sectorMcap / totalMcap) * 100 : 0;
+            return (
+              <div
+                key={sector}
+                className="treemap-sector"
+                style={{ flexBasis: `${Math.max(sectorPct, 8)}%`, flexGrow: Math.max(sectorPct, 8) }}
+              >
+                <div className="treemap-sector-label">{sector}</div>
+                <div className="treemap-stocks">
+                  {sectorStocks.map((stock) => {
+                    const stockPct = sectorMcap > 0 ? (stock.market_cap / sectorMcap) * 100 : 0;
+                    const intensity = Math.min(Math.abs(stock.change_pct) / 4, 1);
+                    const isPositive = stock.change_pct >= 0;
+                    const primaryLabel = selectedIndex === "kospi" ? (stock.name || stock.ticker) : stock.ticker;
+                    const secondaryLabel = selectedIndex === "kospi" ? stock.ticker : "";
+                    return (
+                      <div
+                        key={stock.ticker}
+                        className="treemap-cell"
+                        style={{
+                          flexBasis: `${Math.max(stockPct, 8)}%`,
+                          flexGrow: Math.max(stockPct, 8),
+                          backgroundColor: isPositive
+                            ? `rgba(0, 212, 170, ${0.15 + intensity * 0.6})`
+                            : `rgba(255, 71, 87, ${0.15 + intensity * 0.6})`,
+                        }}
+                        title={`${stock.name}\n${stock.change_pct >= 0 ? "+" : ""}${stock.change_pct}%`}
+                      >
+                        <span className="treemap-ticker">{primaryLabel}</span>
+                        {secondaryLabel ? <span className="treemap-subticker">{secondaryLabel}</span> : null}
+                        <span className="treemap-change">
+                          {stock.change_pct >= 0 ? "+" : ""}
+                          {stock.change_pct}%
+                        </span>
+                      </div>
+                    );
+                  })}
+                </div>
+              </div>
+            );
+          })}
+        </div>
+      )}
+    </div>
+  );
+}
+

atlas-terminal/apps/web/src/app/components/overview/CommodityOverview.tsx

@@ -0,0 +1,88 @@
+"use client";
+
+interface CommodityOverviewProps {
+  ticker: string;
+  data: Record<string, unknown>;
+}
+
+export function CommodityOverview({ ticker, data }: CommodityOverviewProps) {
+  const seasonal = data?.seasonal_pattern || {};
+  const correlations = data?.correlation_matrix || {};
+  const related = Array.isArray(data?.related_assets) ? data.related_assets : [];
+  return (
+    <div className="space-y-4">
+      <h1 className="text-2xl font-bold">
+        <span className="text-accent-green">{ticker}</span> Commodity Overview
+      </h1>
+      <div className="bg-bg-card border border-border rounded-lg p-5">
+        <div className="text-text-primary font-semibold text-lg">{data?.name || ticker}</div>
+        <div className="text-3xl font-mono font-bold text-text-primary mt-1">
+          {data?.price != null ? `$${Number(data.price).toFixed(2)}` : "—"}
+        </div>
+      </div>
+
+      <div className="grid grid-cols-2 lg:grid-cols-4 gap-3">
+        {[
+          { label: "Open Interest", value: data?.open_interest?.toLocaleString?.() || "—" },
+          { label: "Volume", value: data?.volume?.toLocaleString?.() || "—" },
+          { label: "52W High", value: data?.high_52w != null ? `$${Number(data.high_52w).toFixed(2)}` : "—" },
+          { label: "52W Low", value: data?.low_52w != null ? `$${Number(data.low_52w).toFixed(2)}` : "—" },
+        ].map((m) => (
+          <div key={m.label} className="bg-bg-card border border-border rounded-lg p-4">
+            <div className="text-text-muted text-xs">{m.label}</div>
+            <div className="text-text-primary font-mono font-semibold mt-1">{m.value}</div>
+          </div>
+        ))}
+      </div>
+
+      <div className="bg-bg-card border border-border rounded-lg p-5">
+        <h3 className="text-text-secondary text-sm font-semibold mb-3">Seasonal Pattern (10Y avg monthly)</h3>
+        <div className="grid grid-cols-3 lg:grid-cols-6 gap-2 text-xs">
+          {Array.from({ length: 12 }, (_, i) => i + 1).map((m) => {
+            const v = seasonal?.[m] ?? 0;
+            return (
+              <div key={m} className="bg-bg-primary border border-border rounded p-2">
+                <div className="text-text-muted">M{m}</div>
+                <div className={`font-mono ${v >= 0 ? "text-accent-green" : "text-accent-red"}`}>
+                  {v >= 0 ? "+" : ""}
+                  {v}%
+                </div>
+              </div>
+            );
+          })}
+        </div>
+      </div>
+
+      {related.length > 0 && (
+        <div className="bg-bg-card border border-border rounded-lg p-5">
+          <h3 className="text-text-secondary text-sm font-semibold mb-3">Related Assets</h3>
+          <div className="grid grid-cols-2 lg:grid-cols-4 gap-2">
+            {related.map((r: Record<string, unknown>) => (
+              <div key={r.symbol} className="bg-bg-primary border border-border rounded p-3">
+                <div className="text-text-secondary text-xs">{r.symbol}</div>
+                <div className="text-text-primary font-mono">{r.price != null ? `$${Number(r.price).toFixed(2)}` : "—"}</div>
+                <div className={`text-xs font-mono ${Number(r.change_pct || 0) >= 0 ? "text-accent-green" : "text-accent-red"}`}>
+                  {Number(r.change_pct || 0) >= 0 ? "+" : ""}
+                  {r.change_pct ?? 0}%
+                </div>
+              </div>
+            ))}
+          </div>
+        </div>
+      )}
+
+      <div className="bg-bg-card border border-border rounded-lg p-5">
+        <h3 className="text-text-secondary text-sm font-semibold mb-3">Correlation Matrix (1Y)</h3>
+        <div className="space-y-1 text-sm">
+          {Object.keys(correlations).length === 0 && <div className="text-text-muted">No correlation data</div>}
+          {Object.entries(correlations).map(([k, v]) => (
+            <div key={k} className="flex justify-between">
+              <span className="text-text-secondary">{k}</span>
+              <span className="text-text-primary font-mono">{String(v)}</span>
+            </div>
+          ))}
+        </div>
+      </div>
+    </div>
+  );
+}

atlas-terminal/apps/web/src/app/components/overview/ETFOverview.tsx

@@ -0,0 +1,84 @@
+"use client";
+
+interface ETFOverviewProps {
+  ticker: string;
+  data: Record<string, unknown>;
+}
+
+export function ETFOverview({ ticker, data }: ETFOverviewProps) {
+  const returns = data?.returns || {};
+  const risk = data?.risk || {};
+  const holdings = Array.isArray(data?.holdings) ? data.holdings : [];
+  return (
+    <div className="space-y-4">
+      <h1 className="text-2xl font-bold">
+        <span className="text-accent-green">{ticker}</span> ETF Overview
+      </h1>
+      <div className="bg-bg-card border border-border rounded-lg p-5">
+        <div className="text-text-primary font-semibold text-lg">{data?.name || ticker}</div>
+        <div className="text-3xl font-mono font-bold text-text-primary mt-1">
+          {data?.price != null ? `$${Number(data.price).toFixed(2)}` : "—"}
+        </div>
+      </div>
+
+      <div className="grid grid-cols-2 lg:grid-cols-4 gap-3">
+        {[
+          { label: "Category", value: data?.category || "N/A" },
+          { label: "AUM", value: data?.aum ? `$${(Number(data.aum) / 1e9).toFixed(1)}B` : "—" },
+          { label: "Expense Ratio", value: data?.expense_ratio != null ? `${(Number(data.expense_ratio) * 100).toFixed(2)}%` : "—" },
+          { label: "NAV", value: data?.nav != null ? `$${Number(data.nav).toFixed(2)}` : "—" },
+          { label: "52W High", value: data?.high_52w != null ? `$${Number(data.high_52w).toFixed(2)}` : "—" },
+          { label: "52W Low", value: data?.low_52w != null ? `$${Number(data.low_52w).toFixed(2)}` : "—" },
+          { label: "1Y Return", value: returns?.["1y"] != null ? `${returns["1y"]}%` : "—" },
+          { label: "YTD Return", value: returns?.ytd != null ? `${returns.ytd}%` : "—" },
+        ].map((m) => (
+          <div key={m.label} className="bg-bg-card border border-border rounded-lg p-4">
+            <div className="text-text-muted text-xs">{m.label}</div>
+            <div className="text-text-primary font-mono font-semibold mt-1">{m.value}</div>
+          </div>
+        ))}
+      </div>
+
+      <div className="bg-bg-card border border-border rounded-lg p-5">
+        <h3 className="text-text-secondary text-sm font-semibold mb-3">Performance</h3>
+        <div className="flex flex-wrap gap-2 text-sm">
+          {["1m", "3m", "6m", "ytd", "1y", "3y", "5y"].map((k) => (
+            <span key={k} className="bg-bg-primary border border-border rounded px-2 py-1 font-mono text-text-primary">
+              {k.toUpperCase()}: {returns?.[k] != null ? `${returns[k]}%` : "—"}
+            </span>
+          ))}
+        </div>
+      </div>
+
+      {holdings.length > 0 && (
+        <div className="bg-bg-card border border-border rounded-lg p-5">
+          <h3 className="text-text-secondary text-sm font-semibold mb-3">Top Holdings</h3>
+          <div className="space-y-2">
+            {holdings.slice(0, 10).map((h: Record<string, unknown>, i: number) => (
+              <div key={`${h.symbol || h.name}-${i}`} className="flex justify-between text-sm">
+                <span className="text-text-primary">{h.symbol || h.name || "—"}</span>
+                <span className="text-text-muted font-mono">
+                  {h.weight_pct != null ? `${(Number(h.weight_pct) * 100).toFixed(2)}%` : "—"}
+                </span>
+              </div>
+            ))}
+          </div>
+        </div>
+      )}
+
+      <div className="grid grid-cols-2 lg:grid-cols-4 gap-3">
+        {[
+          { label: "Sharpe", value: risk?.sharpe },
+          { label: "Sortino", value: risk?.sortino },
+          { label: "Max DD", value: risk?.max_drawdown != null ? `${risk.max_drawdown}%` : null },
+          { label: "Volatility", value: risk?.volatility != null ? `${risk.volatility}%` : null },
+        ].map((r) => (
+          <div key={r.label} className="bg-bg-card border border-border rounded-lg p-4">
+            <div className="text-text-muted text-xs">{r.label}</div>
+            <div className="text-text-primary font-mono font-semibold mt-1">{r.value ?? "—"}</div>
+          </div>
+        ))}
+      </div>
+    </div>
+  );
+}

atlas-terminal/apps/web/src/app/components/overview/EquityOverview.tsx

@@ -0,0 +1,74 @@
+"use client";
+
+interface EquityOverviewProps {
+  ticker: string;
+  sector: Record<string, unknown> | null;
+  health: Record<string, unknown> | null;
+}
+
+export function EquityOverview({ ticker, sector, health }: EquityOverviewProps) {
+  const metrics = [
+    { label: "Sector", value: sector?.sector || "—" },
+    { label: "Industry", value: sector?.industry || "—" },
+    { label: "Market Cap", value: sector?.market_cap ? `$${(Number(sector.market_cap) / 1e9).toFixed(1)}B` : "—" },
+    { label: "P/E Ratio", value: sector?.pe_ratio != null ? Number(sector.pe_ratio).toFixed(1) : "—" },
+    { label: "Beta", value: sector?.beta != null ? Number(sector.beta).toFixed(2) : "—" },
+    { label: "Div Yield", value: sector?.dividend_yield != null ? `${Number(sector.dividend_yield).toFixed(2)}%` : "—" },
+    { label: "52W High", value: sector?.fifty_two_week_high != null ? `$${Number(sector.fifty_two_week_high).toFixed(2)}` : "—" },
+    { label: "52W Low", value: sector?.fifty_two_week_low != null ? `$${Number(sector.fifty_two_week_low).toFixed(2)}` : "—" },
+  ];
+
+  return (
+    <div>
+      <h1 className="text-2xl font-bold mb-1">
+        <span className="text-accent-green">{ticker}</span> Overview
+      </h1>
+      {sector?.current_price != null && (
+        <p className="text-3xl font-mono font-bold text-text-primary mb-6">${Number(sector.current_price).toFixed(2)}</p>
+      )}
+      <div className="grid grid-cols-2 lg:grid-cols-4 gap-3 mb-6">
+        {metrics.map((m) => (
+          <div key={m.label} className="bg-bg-card border border-border rounded-lg p-4">
+            <div className="text-text-muted text-xs mb-1">{m.label}</div>
+            <div className="text-text-primary font-semibold">{m.value}</div>
+          </div>
+        ))}
+      </div>
+      <div className="grid grid-cols-1 lg:grid-cols-4 gap-4 mb-4">
+        <Card title="Altman Z-Score" value={health?.altman_z != null ? Number(health.altman_z).toFixed(2) : "—"} />
+        <Card title="Current Ratio" value={health?.current_ratio != null ? Number(health.current_ratio).toFixed(2) : "—"} />
+        <Card title="Interest Cov." value={health?.interest_coverage != null ? `${Number(health.interest_coverage).toFixed(1)}x` : "—"} />
+        <Card title="D/E Ratio" value={health?.debt_to_equity != null ? Number(health.debt_to_equity).toFixed(2) : "—"} />
+      </div>
+      <div className="bg-bg-card border border-border rounded-lg p-5">
+        <h3 className="text-text-secondary text-sm font-semibold mb-3">DuPont Analysis</h3>
+        {!!health?.dupont ? (
+          <div className="space-y-2">
+            {[
+              { label: "ROE", value: health.dupont.roe },
+              { label: "Net Profit Margin", value: health.dupont.npm },
+              { label: "Asset Turnover", value: health.dupont.asset_turnover },
+              { label: "Equity Multiplier", value: health.dupont.equity_multiplier },
+            ].map((d) => (
+              <div key={d.label} className="flex justify-between">
+                <span className="text-text-muted text-sm">{d.label}</span>
+                <span className="text-text-primary font-mono">{d.value != null ? Number(d.value).toFixed(2) : "—"}</span>
+              </div>
+            ))}
+          </div>
+        ) : (
+          <div className="text-text-muted">No data</div>
+        )}
+      </div>
+    </div>
+  );
+}
+
+function Card({ title, value }: { title: string; value: string }) {
+  return (
+    <div className="bg-bg-card border border-border rounded-lg p-5">
+      <h3 className="text-text-secondary text-sm font-semibold mb-3">{title}</h3>
+      <div className="text-3xl font-mono font-bold text-text-primary">{value}</div>
+    </div>
+  );
+}

atlas-terminal/apps/web/src/app/components/sidebar.tsx

@@ -2,6 +2,7 @@
 import Link from "next/link";
 import { usePathname } from "next/navigation";
 import { useState, useEffect } from "react";
+import { normalizeTickerInput } from "../lib/ticker-alias";
 
 const NAV_ITEMS = [
   { href: "/", label: "Overview", icon: "📊" },
@@ -11,6 +12,7 @@ const NAV_ITEMS = [
   { href: "/markets", label: "Markets", icon: "🌍" },
   { href: "/earnings", label: "Earnings", icon: "📅" },
   { href: "/news", label: "News", icon: "📰" },
+  { href: "/screener", label: "Screener", icon: "🎯" },
   { href: "/portfolio", label: "Portfolio", icon: "💼" },
   { href: "/filings", label: "Filings", icon: "📑" },
 ];
@@ -33,7 +35,7 @@ export function Sidebar() {
   }, []);
 
   function handleSearch() {
-    const val = input.trim().toUpperCase();
+    const val = normalizeTickerInput(input);
     if (val) {
       setTickerLocal(val);
       localStorage.setItem("atlas_active_ticker", val);

atlas-terminal/apps/web/src/app/earnings/page.tsx

@@ -23,6 +23,7 @@ interface QuarterlyData {
 
 export default function EarningsPage() {
   const { ticker } = useTicker();
+  const [assetType, setAssetType] = useState<string>("equity");
   const [history, setHistory] = useState<EarningsRecord[]>([]);
   const [calendar, setCalendar] = useState<CalendarData | null>(null);
   const [quarterly, setQuarterly] = useState<QuarterlyData[]>([]);
@@ -34,16 +35,31 @@ export default function EarningsPage() {
       fetch(`/api/earnings/${ticker}/history`).then((r) => r.ok ? r.json() : null),
       fetch(`/api/earnings/${ticker}/calendar`).then((r) => r.ok ? r.json() : null),
       fetch(`/api/earnings/${ticker}/quarterly`).then((r) => r.ok ? r.json() : null),
-    ]).then(([h, c, q]) => {
+      fetch(`/api/market/overview/${ticker}`).then((r) => r.ok ? r.json() : null),
+    ]).then(([h, c, q, o]) => {
       setHistory(h?.history || []);
       setCalendar(c);
       setQuarterly(q?.quarterly || []);
+      setAssetType(o?.asset_type || "equity");
       setLoading(false);
     }).catch(() => setLoading(false));
   }, [ticker]);
 
   if (loading) return <div className="flex items-center justify-center h-64"><div className="text-accent-green animate-pulse font-mono">Loading...</div></div>;
 
+  if (assetType !== "equity") {
+    return (
+      <div>
+        <h1 className="text-2xl font-bold mb-6">
+          <span className="text-accent-green">{ticker}</span> Earnings
+        </h1>
+        <div className="bg-bg-card border border-border rounded-lg p-5 text-text-secondary text-sm">
+          해당 자산 유형({assetType})에는 Earnings 데이터가 없습니다.
+        </div>
+      </div>
+    );
+  }
+
   return (
     <div>
       <h1 className="text-2xl font-bold mb-6">

atlas-terminal/apps/web/src/app/globals.css

@@ -38,3 +38,202 @@ body {
 input::placeholder {
   color: #6B7280;
 }
+
+.action-btn {
+  width: 32px;
+  height: 32px;
+  border: none;
+  border-radius: 6px;
+  background: transparent;
+  cursor: pointer;
+}
+
+.edit-input {
+  width: 100%;
+  max-width: 120px;
+  background: #0A0A0F;
+  border: 1px solid #4DA6FF;
+  border-radius: 6px;
+  padding: 6px 10px;
+  color: #F3F4F6;
+  font-family: "JetBrains Mono", monospace;
+  font-size: 13px;
+  outline: none;
+}
+
+.delete-modal-overlay {
+  position: fixed;
+  top: 0;
+  left: 0;
+  right: 0;
+  bottom: 0;
+  background: rgba(0, 0, 0, 0.6);
+  display: flex;
+  align-items: center;
+  justify-content: center;
+  z-index: 1000;
+}
+
+.portfolio-header {
+  display: flex;
+  align-items: center;
+  justify-content: space-between;
+  margin-bottom: 24px;
+}
+
+.currency-toggle {
+  display: flex;
+  gap: 4px;
+  background: #1A1A26;
+  border: 1px solid #2A2A3A;
+  border-radius: 8px;
+  padding: 3px;
+}
+
+.currency-btn {
+  padding: 6px 14px;
+  border: none;
+  border-radius: 6px;
+  background: transparent;
+  color: #9CA3AF;
+  font-family: "JetBrains Mono", monospace;
+  font-size: 12px;
+  font-weight: 500;
+  cursor: pointer;
+  transition: all 0.15s;
+  white-space: nowrap;
+}
+
+.currency-btn:hover {
+  color: #F3F4F6;
+  background: #252536;
+}
+
+.currency-btn.active {
+  background: #00D4AA;
+  color: #0A0A0F;
+}
+
+.heatmap-header {
+  display: flex;
+  align-items: center;
+  justify-content: space-between;
+  margin-bottom: 16px;
+}
+
+.index-toggle {
+  display: flex;
+  gap: 4px;
+  background: #1A1A26;
+  border: 1px solid #2A2A3A;
+  border-radius: 8px;
+  padding: 3px;
+}
+
+.index-btn {
+  padding: 6px 16px;
+  border: none;
+  border-radius: 6px;
+  background: transparent;
+  color: #9CA3AF;
+  font-size: 13px;
+  font-weight: 500;
+  cursor: pointer;
+  transition: all 0.15s;
+}
+
+.index-btn:hover {
+  color: #F3F4F6;
+  background: #252536;
+}
+
+.index-btn.active {
+  background: #00D4AA;
+  color: #0A0A0F;
+}
+
+.treemap-container {
+  display: flex;
+  flex-wrap: wrap;
+  gap: 2px;
+  border-radius: 8px;
+  overflow: hidden;
+  min-height: 400px;
+  background: #0A0A0F;
+}
+
+.treemap-sector {
+  display: flex;
+  flex-direction: column;
+  min-width: 80px;
+  position: relative;
+}
+
+.treemap-sector-label {
+  font-size: 10px;
+  font-weight: 600;
+  color: #9CA3AF;
+  padding: 4px 6px;
+  background: rgba(0, 0, 0, 0.3);
+  position: absolute;
+  top: 0;
+  left: 0;
+  z-index: 1;
+  border-radius: 4px 0 4px 0;
+  pointer-events: none;
+}
+
+.treemap-stocks {
+  display: flex;
+  flex-wrap: wrap;
+  flex: 1;
+  gap: 1px;
+}
+
+.treemap-cell {
+  display: flex;
+  flex-direction: column;
+  align-items: center;
+  justify-content: center;
+  min-width: 60px;
+  min-height: 50px;
+  padding: 4px;
+  cursor: pointer;
+  transition: filter 0.15s, transform 0.1s;
+  border-radius: 2px;
+}
+
+.treemap-cell:hover {
+  filter: brightness(1.15);
+  transform: scale(1.02);
+  z-index: 2;
+}
+
+.treemap-ticker {
+  font-family: "JetBrains Mono", monospace;
+  font-size: 11px;
+  font-weight: 700;
+  color: #F3F4F6;
+}
+
+.treemap-change {
+  font-family: "JetBrains Mono", monospace;
+  font-size: 10px;
+  font-weight: 600;
+  color: #F3F4F6;
+}
+
+.treemap-subticker {
+  font-family: "JetBrains Mono", monospace;
+  font-size: 9px;
+  color: #9CA3AF;
+}
+
+.heatmap-loading {
+  display: flex;
+  align-items: center;
+  justify-content: center;
+  min-height: 400px;
+  color: #9CA3AF;
+  font-size: 14px;
+}

atlas-terminal/apps/web/src/app/lib/ticker-alias.ts

@@ -0,0 +1,36 @@
+const TICKER_ALIASES: Record<string, string> = {
+  // Commodities (natural language -> futures ticker)
+  gold: "GC=F",
+  silver: "SI=F",
+  platinum: "PL=F",
+  palladium: "PA=F",
+  oil: "CL=F",
+  crude: "CL=F",
+  "crude oil": "CL=F",
+  brent: "BZ=F",
+  gas: "NG=F",
+  "natural gas": "NG=F",
+  copper: "HG=F",
+  wheat: "ZW=F",
+  corn: "ZC=F",
+  soybeans: "ZS=F",
+  coffee: "KC=F",
+  sugar: "SB=F",
+
+  // Popular commodity ETFs
+  gld: "GLD",
+  slv: "SLV",
+  uso: "USO",
+  ung: "UNG",
+  dbc: "DBC",
+  gsg: "GSG",
+};
+
+export function normalizeTickerInput(raw: string): string {
+  const cleaned = raw.trim();
+  if (!cleaned) return "";
+  const key = cleaned.toLowerCase();
+  const mapped = TICKER_ALIASES[key] || cleaned;
+  return mapped.toUpperCase();
+}
+

atlas-terminal/apps/web/src/app/lib/use-ticker.ts

@@ -1,5 +1,6 @@
 "use client";
 import { useState, useEffect, useCallback } from "react";
+import { normalizeTickerInput } from "./ticker-alias";
 
 const DEFAULT_TICKER = "AAPL";
 const STORAGE_KEY = "atlas_active_ticker";
@@ -7,7 +8,8 @@ const EVENT_NAME = "atlas-ticker-change";
 
 function getInitialTicker(): string {
   if (typeof window === "undefined") return DEFAULT_TICKER;
-  return localStorage.getItem(STORAGE_KEY) || DEFAULT_TICKER;
+  const saved = localStorage.getItem(STORAGE_KEY) || DEFAULT_TICKER;
+  return normalizeTickerInput(saved);
 }
 
 export function useTicker() {
@@ -23,7 +25,7 @@ export function useTicker() {
   }, []);
 
   const setTicker = useCallback((val: string) => {
-    const upper = val.trim().toUpperCase();
+    const upper = normalizeTickerInput(val);
     if (!upper) return;
     setTickerState(upper);
     localStorage.setItem(STORAGE_KEY, upper);

atlas-terminal/apps/web/src/app/markets/page.tsx

@@ -1,8 +1,10 @@
 "use client";
 import { useEffect, useState } from "react";
 import { useTicker } from "../lib/use-ticker";
+import { HeatmapSection } from "../components/markets/HeatmapSection";
 
 type StatementType = "income_statement" | "balance_sheet" | "cash_flow";
+type ViewTab = "overview" | "statements";
 
 interface FinancialStatements {
   income_statement?: Record<string, unknown>[];
@@ -10,6 +12,28 @@ interface FinancialStatements {
   cash_flow?: Record<string, unknown>[];
 }
 
+interface OverviewItem {
+  name: string;
+  symbol: string;
+  price: number;
+  change_pct: number;
+}
+
+interface MarketOverviewResponse {
+  indices?: OverviewItem[];
+  commodities?: OverviewItem[];
+  bonds?: OverviewItem[];
+  crypto?: OverviewItem[];
+  fx?: OverviewItem[];
+  popular_etfs?: OverviewItem[];
+}
+
+interface SectorHeat {
+  sector: string;
+  etf: string;
+  change_pct: number;
+}
+
 const TABS: { key: StatementType; label: string }[] = [
   { key: "income_statement", label: "Income Statement" },
   { key: "balance_sheet", label: "Balance Sheet" },
@@ -107,6 +131,10 @@ export default function MarketsPage() {
   const { ticker } = useTicker();
   const [data, setData] = useState<FinancialStatements | null>(null);
   const [tab, setTab] = useState<StatementType>("income_statement");
+  const [viewTab, setViewTab] = useState<ViewTab>("overview");
+  const [overview, setOverview] = useState<MarketOverviewResponse | null>(null);
+  const [sectors, setSectors] = useState<SectorHeat[]>([]);
+  const [selectedHeatmapIndex, setSelectedHeatmapIndex] = useState("sp500");
   const [loading, setLoading] = useState(true);
 
   useEffect(() => {
@@ -120,6 +148,17 @@ export default function MarketsPage() {
       .catch(() => setLoading(false));
   }, [ticker]);
 
+  useEffect(() => {
+    fetch("/api/market/overview")
+      .then((r) => (r.ok ? r.json() : null))
+      .then((d) => setOverview(d))
+      .catch(() => setOverview(null));
+    fetch("/api/market/sectors")
+      .then((r) => (r.ok ? r.json() : []))
+      .then((d) => setSectors(Array.isArray(d) ? d : []))
+      .catch(() => setSectors([]));
+  }, []);
+
   if (loading)
     return (
       <div className="flex items-center justify-center h-64">
@@ -137,7 +176,7 @@ export default function MarketsPage() {
       return vals.some(([, v]) => v != null);
     })
     .map((r) => ({
-      date: String(r.asOfDate || "").slice(0, 10),
+      date: String((r.asOfDate || r.period || "")).slice(0, 10),
       periodType: String(r.periodType || ""),
       data: r,
     }))
@@ -223,16 +262,107 @@ export default function MarketsPage() {
 
   const filteredRows = rowDefs.filter(rowHasData);
 
+  function renderOverviewCard(title: string, items: OverviewItem[] | undefined) {
+    const indexMap: Record<string, string> = {
+      "S&P 500": "sp500",
+      NASDAQ: "nasdaq100",
+      KOSPI: "kospi",
+      "FTSE 100": "ftse100",
+    };
+    return (
+      <div className="bg-bg-card border border-border rounded-lg p-4">
+        <h3 className="text-text-secondary text-sm font-semibold mb-3">{title}</h3>
+        <div className="grid grid-cols-2 lg:grid-cols-4 gap-2">
+          {(items || []).map((item) => (
+            <div
+              key={`${title}-${item.symbol}`}
+              className="bg-bg-primary border border-border rounded-md p-3"
+              style={{ cursor: title === "Global Indices" ? "pointer" : "default" }}
+              onClick={() => {
+                if (title !== "Global Indices") return;
+                const target = indexMap[item.name];
+                if (target) {
+                  setSelectedHeatmapIndex(target);
+                  document.getElementById("heatmap-section")?.scrollIntoView({ behavior: "smooth" });
+                }
+              }}
+            >
+              <div className="text-text-muted text-xs">{item.name}</div>
+              <div className="text-text-primary font-mono font-semibold">{item.price?.toLocaleString?.() ?? "—"}</div>
+              <div className={`font-mono text-xs ${item.change_pct >= 0 ? "text-accent-green" : "text-accent-red"}`}>
+                {item.change_pct >= 0 ? "+" : ""}
+                {item.change_pct?.toFixed?.(2)}%
+              </div>
+            </div>
+          ))}
+        </div>
+      </div>
+    );
+  }
+
   return (
     <div>
       <h1 className="text-2xl font-bold mb-4">
-        <span className="text-accent-green">{ticker}</span> Financial Statements
+        <span className="text-accent-green">{ticker}</span> Markets
       </h1>
 
+      {/* Top Tabs */}
+      <div className="flex gap-1 mb-4 bg-bg-card rounded-lg p-1 w-fit">
+        {[
+          { key: "overview", label: "Market Overview" },
+          { key: "statements", label: "Financial Statements" },
+        ].map((t) => (
+          <button
+            key={t.key}
+            onClick={() => setViewTab(t.key as ViewTab)}
+            className={`px-4 py-2 rounded-md text-sm font-medium transition-colors ${
+              viewTab === t.key ? "bg-accent-green text-bg-primary" : "text-text-secondary hover:text-text-primary"
+            }`}
+          >
+            {t.label}
+          </button>
+        ))}
+      </div>
+
+      {viewTab === "overview" ? (
+        <div className="space-y-4">
+          {renderOverviewCard("Global Indices", overview?.indices)}
+          <HeatmapSection selectedIndex={selectedHeatmapIndex} onSelectIndex={setSelectedHeatmapIndex} />
+          <div className="bg-bg-card border border-border rounded-lg p-4">
+            <h3 className="text-text-secondary text-sm font-semibold mb-3">Sector Performance</h3>
+            <div className="grid grid-cols-2 md:grid-cols-3 lg:grid-cols-4 gap-2">
+              {sectors.map((sector) => (
+                <div
+                  key={sector.etf}
+                  className="rounded-md p-3 flex flex-col items-center justify-center border border-border"
+                  style={{
+                    background:
+                      sector.change_pct >= 0
+                        ? `rgba(0, 212, 170, ${Math.min(Math.abs(sector.change_pct) / 5, 0.6)})`
+                        : `rgba(255, 71, 87, ${Math.min(Math.abs(sector.change_pct) / 5, 0.6)})`,
+                  }}
+                >
+                  <span className="text-xs font-semibold text-text-primary">{sector.sector}</span>
+                  <span className={`text-sm font-mono font-bold ${sector.change_pct >= 0 ? "text-accent-green" : "text-accent-red"}`}>
+                    {sector.change_pct >= 0 ? "+" : ""}
+                    {sector.change_pct}%
+                  </span>
+                </div>
+              ))}
+            </div>
+          </div>
+          {renderOverviewCard("Commodities", overview?.commodities)}
+          {renderOverviewCard("Popular ETFs", overview?.popular_etfs)}
+          {renderOverviewCard("Bonds", overview?.bonds)}
+          {renderOverviewCard("Crypto", overview?.crypto)}
+          {renderOverviewCard("FX", overview?.fx)}
+        </div>
+      ) : (
+        <>
       {/* Unit Note */}
       <div className="text-text-muted text-xs mb-3 font-mono">Unit: Millions USD (except per-share data)</div>
 
-      {/* Tabs */}
+      {/* Statement Tabs */}
       <div className="flex gap-1 mb-4 bg-bg-card rounded-lg p-1 w-fit">
         {TABS.map((t) => (
           <button
@@ -259,14 +389,14 @@ export default function MarketsPage() {
                 </th>
                 {periods.map((p, i) => (
                   <th key={i} className="text-right px-4 py-3 text-text-muted font-semibold whitespace-nowrap min-w-[110px]">
-                    <div className="text-text-secondary">{p.date.slice(0, 4)}</div>
-                    <div className="text-text-muted text-[10px]">{p.date}</div>
+                    <div className="text-text-secondary">{p.date && p.date !== "—" ? p.date.slice(0, 4) : `P${i + 1}`}</div>
+                    <div className="text-text-muted text-[10px]">{p.date || "—"}</div>
                   </th>
                 ))}
               </tr>
             </thead>
             <tbody>
-              {filteredRows.map((rowDef, ri) => {
+              {filteredRows.map((rowDef) => {
                 const isGrowth = rowDef.isGrowth;
                 return (
                   <tr
@@ -329,6 +459,8 @@ export default function MarketsPage() {
           No financial data available for {ticker}
         </div>
       )}
+        </>
+      )}
     </div>
   );
 }

atlas-terminal/apps/web/src/app/page.tsx

@@ -1,29 +1,16 @@
 "use client";
 import { useEffect, useState } from "react";
 import { useTicker } from "./lib/use-ticker";
-
-interface HealthData {
-  dupont?: { roe?: number; npm?: number; asset_turnover?: number; equity_multiplier?: number };
-  altman_z?: number;
-  red_flags?: string[];
-}
-
-interface SectorData {
-  sector?: string;
-  industry?: string;
-  market_cap?: number;
-  pe_ratio?: number;
-  dividend_yield?: number;
-  beta?: number;
-  fifty_two_week_high?: number;
-  fifty_two_week_low?: number;
-  current_price?: number;
-}
+import { EquityOverview } from "./components/overview/EquityOverview";
+import { ETFOverview } from "./components/overview/ETFOverview";
+import { CommodityOverview } from "./components/overview/CommodityOverview";
 
 export default function OverviewPage() {
   const { ticker } = useTicker();
-  const [sector, setSector] = useState<SectorData | null>(null);
-  const [health, setHealth] = useState<HealthData | null>(null);
+  const [sector, setSector] = useState<Record<string, unknown> | null>(null);
+  const [health, setHealth] = useState<Record<string, unknown> | null>(null);
+  const [overview, setOverview] = useState<Record<string, unknown> | null>(null);
+  const [assetType, setAssetType] = useState<string>("equity");
   const [loading, setLoading] = useState(true);
 
   useEffect(() => {
@@ -31,103 +18,25 @@ export default function OverviewPage() {
     Promise.all([
       fetch(`/api/market/sector/${ticker}`).then((r) => r.ok ? r.json() : null),
       fetch(`/api/market/health/${ticker}`).then((r) => r.ok ? r.json() : null),
-    ]).then(([s, h]) => {
+      fetch(`/api/market/overview/${ticker}`).then((r) => r.ok ? r.json() : null),
+    ]).then(([s, h, d]) => {
       setSector(s);
       setHealth(h);
+      setAssetType(d?.asset_type || "equity");
+      setOverview(d?.data || null);
       setLoading(false);
     }).catch(() => setLoading(false));
   }, [ticker]);
 
   if (loading) return <LoadingState />;
 
-  const metrics = [
-    { label: "Sector", value: sector?.sector || "—" },
-    { label: "Industry", value: sector?.industry || "—" },
-    { label: "Market Cap", value: sector?.market_cap ? `$${(sector.market_cap / 1e9).toFixed(1)}B` : "—" },
-    { label: "P/E Ratio", value: sector?.pe_ratio?.toFixed(1) || "—" },
-    { label: "Beta", value: sector?.beta?.toFixed(2) || "—" },
-    { label: "Div Yield", value: sector?.dividend_yield ? `${sector.dividend_yield.toFixed(2)}%` : "—" },
-    { label: "52W High", value: sector?.fifty_two_week_high ? `$${sector.fifty_two_week_high.toFixed(2)}` : "—" },
-    { label: "52W Low", value: sector?.fifty_two_week_low ? `$${sector.fifty_two_week_low.toFixed(2)}` : "—" },
-  ];
-
-  const zScore = health?.altman_z;
-  const zColor = zScore && zScore > 2.99 ? "text-accent-green" : zScore && zScore > 1.81 ? "text-accent-yellow" : "text-accent-red";
-
-  return (
-    <div>
-      <h1 className="text-2xl font-bold mb-1">
-        <span className="text-accent-green">{ticker}</span> Overview
-      </h1>
-      {sector?.current_price && (
-        <p className="text-3xl font-mono font-bold text-text-primary mb-6">
-          ${sector.current_price.toFixed(2)}
-        </p>
-      )}
-
-      {/* Key Metrics Grid */}
-      <div className="grid grid-cols-2 lg:grid-cols-4 gap-3 mb-6">
-        {metrics.map((m) => (
-          <div key={m.label} className="bg-bg-card border border-border rounded-lg p-4">
-            <div className="text-text-muted text-xs mb-1">{m.label}</div>
-            <div className="text-text-primary font-semibold">{m.value}</div>
-          </div>
-        ))}
-      </div>
-
-      {/* Health Section */}
-      <div className="grid grid-cols-2 gap-4">
-        {/* Altman Z-Score */}
-        <div className="bg-bg-card border border-border rounded-lg p-5">
-          <h3 className="text-text-secondary text-sm font-semibold mb-3">Altman Z-Score</h3>
-          <div className={`text-4xl font-mono font-bold ${zColor}`}>
-            {zScore?.toFixed(2) || "—"}
-          </div>
-          <div className="text-text-muted text-xs mt-2">
-            {zScore && zScore > 2.99 ? "Safe Zone" : zScore && zScore > 1.81 ? "Grey Zone" : "Distress Zone"}
-          </div>
-        </div>
-
-        {/* DuPont Analysis */}
-        <div className="bg-bg-card border border-border rounded-lg p-5">
-          <h3 className="text-text-secondary text-sm font-semibold mb-3">DuPont Analysis</h3>
-          {health?.dupont ? (
-            <div className="space-y-2">
-              {[
-                { label: "ROE", value: health.dupont.roe },
-                { label: "Net Profit Margin", value: health.dupont.npm },
-                { label: "Asset Turnover", value: health.dupont.asset_turnover },
-                { label: "Equity Multiplier", value: health.dupont.equity_multiplier },
-              ].map((d) => (
-                <div key={d.label} className="flex justify-between items-center">
-                  <span className="text-text-muted text-sm">{d.label}</span>
-                  <span className="text-text-primary font-mono font-semibold">
-                    {d.value?.toFixed(2) || "—"}
-                  </span>
-                </div>
-              ))}
-            </div>
-          ) : (
-            <div className="text-text-muted">No data</div>
-          )}
-        </div>
-      </div>
-
-      {/* Red Flags */}
-      {health?.red_flags && health.red_flags.length > 0 && (
-        <div className="mt-4 bg-bg-card border border-accent-red/30 rounded-lg p-5">
-          <h3 className="text-accent-red text-sm font-semibold mb-3">Red Flags</h3>
-          <ul className="space-y-1.5">
-            {health.red_flags.map((f, i) => (
-              <li key={i} className="text-text-secondary text-sm flex items-start gap-2">
-                <span className="text-accent-red mt-0.5">•</span> {f}
-              </li>
-            ))}
-          </ul>
-        </div>
-      )}
-    </div>
-  );
+  if (assetType === "etf") {
+    return <ETFOverview ticker={ticker} data={overview || {}} />;
+  }
+  if (assetType === "commodity_future") {
+    return <CommodityOverview ticker={ticker} data={overview || {}} />;
+  }
+  return <EquityOverview ticker={ticker} sector={sector} health={health} />;
 }
 
 function LoadingState() {

atlas-terminal/apps/web/src/app/portfolio/page.tsx

@@ -11,17 +11,62 @@ interface Position {
   market_value?: number;
   pnl?: number;
   pnl_pct?: number;
+  confidence?: string;
+  method?: string;
+  avg_price_currency?: string;
+  stock_currency?: string;
+  account_currency?: string;
+  current_value_account?: number;
+  total_pnl?: number;
+  yf_ticker?: string;
+  avg_method?: string;
+  exchange?: string;
 }
 
 export default function PortfolioPage() {
   const [positions, setPositions] = useState<Position[]>([]);
   const [form, setForm] = useState({ ticker: "", quantity: "", avg_price: "" });
   const [loading, setLoading] = useState(true);
+  const [isDragging, setIsDragging] = useState(false);
+  const [isProcessing, setIsProcessing] = useState(false);
+  const [ocrPositions, setOcrPositions] = useState<Position[]>([]);
+  const [ocrError, setOcrError] = useState<string>("");
+  const [ocrWarnings, setOcrWarnings] = useState<string[]>([]);
+  const [ocrAccountCurrency, setOcrAccountCurrency] = useState<string>("USD");
+  const [editingId, setEditingId] = useState<string | null>(null);
+  const [editValues, setEditValues] = useState({ qty: "", avgPrice: "" });
+  const [deleteConfirmId, setDeleteConfirmId] = useState<string | null>(null);
+  const [displayCurrency, setDisplayCurrency] = useState("USD");
+  const [fxRates, setFxRates] = useState<Record<string, number>>({});
+  const [exchangeSelections, setExchangeSelections] = useState<Record<string, string>>({});
+  const [exchangeOptions, setExchangeOptions] = useState<Record<string, { exchange: string; yf_ticker: string; currency: string; default?: boolean }[]>>({});
 
   useEffect(() => {
     fetchPortfolio();
+    fetch("/api/fx/rates")
+      .then((r) => (r.ok ? r.json() : null))
+      .then((data) => {
+        if (!data) return;
+        setFxRates(data.rates || data);
+      })
+      .catch(() => {});
   }, []);
 
+  useEffect(() => {
+    if (!ocrPositions.length) return;
+    ocrPositions.forEach(async (pos, idx) => {
+      const rowKey = `${pos.ticker}-${idx}`;
+      const res = await fetch(`/api/portfolio/exchange-options/${pos.ticker}`);
+      const data = await res.json().catch(() => null);
+      const opts = Array.isArray(data?.options) ? data.options : [];
+      if (opts.length > 0) {
+        setExchangeOptions((prev) => ({ ...prev, [rowKey]: opts }));
+        const def = opts.find((o) => o.default) || opts[0];
+        setExchangeSelections((prev) => ({ ...prev, [rowKey]: def.exchange }));
+      }
+    });
+  }, [ocrPositions]);
+
   async function fetchPortfolio() {
     setLoading(true);
     try {
@@ -64,28 +109,209 @@ export default function PortfolioPage() {
     }
   }
 
-  const totalValue = positions.reduce((s, p) => s + (p.market_value || p.quantity * (p.current_price || p.avg_price)), 0);
-  const totalCost = positions.reduce((s, p) => s + p.quantity * p.avg_price, 0);
+  async function uploadForOcr(file: File) {
+    setIsProcessing(true);
+    setOcrError("");
+    try {
+      const geminiKey = localStorage.getItem("atlas_gemini_key") || "";
+      if (!geminiKey.trim()) {
+        setOcrPositions([]);
+        setOcrError("Gemini API 키가 없습니다. Settings에서 Gemini API Key를 먼저 저장하세요.");
+        return;
+      }
+
+      const fd = new FormData();
+      fd.append("file", file);
+      const res = await fetch("/api/portfolio/ocr", {
+        method: "POST",
+        body: fd,
+        headers: geminiKey ? { "x-gemini-api-key": geminiKey } : undefined,
+      });
+      const data = await res.json().catch(() => null);
+      const message =
+        data?.error ||
+        data?.detail ||
+        (Array.isArray(data?.detail) ? data.detail.map((d: { msg?: string }) => d?.msg).filter(Boolean).join(", ") : "") ||
+        (res.ok ? "" : `HTTP ${res.status}`);
+      if (!res.ok || data?.error) {
+        setOcrPositions([]);
+        setOcrError(message || "OCR failed");
+      } else {
+        setOcrPositions(Array.isArray(data?.positions) ? data.positions : []);
+        setOcrWarnings(Array.isArray(data?.warnings) ? data.warnings : []);
+        setOcrAccountCurrency(data?.account_currency || data?.total_value?.currency || "USD");
+        if (!Array.isArray(data?.positions) || data.positions.length === 0) {
+          setOcrError("OCR은 완료됐지만 포지션을 찾지 못했습니다. 표가 선명하게 보이는 스크린샷으로 다시 시도하세요.");
+        }
+      }
+    } catch {
+      setOcrPositions([]);
+      setOcrError("Network error during OCR upload");
+    } finally {
+      setIsProcessing(false);
+    }
+  }
+
+  async function importOcrPositions() {
+    if (!ocrPositions.length) return;
+    const failed: string[] = [];
+    for (let idx = 0; idx < ocrPositions.length; idx += 1) {
+      const p = ocrPositions[idx];
+      try {
+        const rowKey = `${p.ticker}-${idx}`;
+        const res = await fetch("/api/portfolio/positions", {
+          method: "POST",
+          headers: { "Content-Type": "application/json" },
+          body: JSON.stringify({
+            ticker: p.ticker,
+            company_name: p.company_name || "",
+            quantity: p.quantity,
+            avg_price: p.avg_price,
+            currency: p.avg_price_currency || p.stock_currency || "USD",
+            exchange: exchangeSelections[rowKey] || p.exchange || "",
+            source: "ocr",
+          }),
+        });
+        if (!res.ok) failed.push(p.ticker);
+      } catch {
+        failed.push(p.ticker);
+      }
+    }
+    if (failed.length > 0) {
+      setOcrError(`일부 저장 실패: ${failed.join(", ")}. Import Results를 유지합니다.`);
+      return;
+    }
+    setOcrPositions([]);
+    setOcrWarnings([]);
+    setExchangeSelections({});
+    setExchangeOptions({});
+    setOcrError("");
+    await fetchPortfolio();
+  }
+
+  function updateOcrPosition(idx: number, key: "quantity" | "avg_price", value: string) {
+    setOcrPositions((prev) =>
+      prev.map((p, i) => {
+        if (i !== idx) return p;
+        const n = Number(value);
+        if (Number.isNaN(n)) return p;
+        return { ...p, [key]: n };
+      }),
+    );
+  }
+
+  async function handleExchangeChange(idx: number, exchange: string) {
+    const pos = ocrPositions[idx];
+    if (!pos) return;
+    const rowKey = `${pos.ticker}-${idx}`;
+    setExchangeSelections((prev) => ({ ...prev, [rowKey]: exchange }));
+    const res = await fetch("/api/portfolio/ocr/recalculate", {
+      method: "POST",
+      headers: { "Content-Type": "application/json" },
+      body: JSON.stringify({
+        account_currency: ocrAccountCurrency,
+        position: pos,
+        selected_exchange: exchange,
+      }),
+    });
+    const data = await res.json().catch(() => null);
+    if (res.ok && data?.position) {
+      setOcrPositions((prev) => prev.map((p, i) => (i === idx ? { ...p, ...data.position, exchange } : p)));
+    }
+  }
+
+  async function handleDelete(positionId: string) {
+    try {
+      const res = await fetch(`/api/portfolio/positions/${positionId}`, { method: "DELETE" });
+      if (res.ok) {
+        setPositions((prev) => prev.filter((p) => p.id !== positionId));
+      }
+    } finally {
+      setDeleteConfirmId(null);
+    }
+  }
+
+  async function handleSaveEdit(positionId: string) {
+    const qty = parseFloat(editValues.qty);
+    const avgPrice = parseFloat(editValues.avgPrice);
+    if (isNaN(qty) || isNaN(avgPrice)) return;
+    const res = await fetch(`/api/portfolio/positions/${positionId}`, {
+      method: "PUT",
+      headers: { "Content-Type": "application/json" },
+      body: JSON.stringify({ quantity: qty, avg_price: avgPrice }),
+    });
+    if (res.ok) {
+      setPositions((prev) =>
+        prev.map((p) => (p.id === positionId ? { ...p, quantity: qty, avg_price: avgPrice } : p)),
+      );
+      setEditingId(null);
+      await fetchPortfolio();
+    }
+  }
+
+  function convertAmount(amount: number, fromCurrency: string, toCurrency: string): number {
+    if (!amount || Number.isNaN(amount)) return 0;
+    const from = (fromCurrency || "USD").toUpperCase();
+    const to = (toCurrency || "USD").toUpperCase();
+    if (from === to) return amount;
+    const key = `${from}_${to}`;
+    const rate = fxRates[key] || 1;
+    return amount * rate;
+  }
+
+  function getCurrencySymbol(currency: string): string {
+    const symbols: Record<string, string> = { USD: "$", GBP: "£", KRW: "₩", EUR: "€", JPY: "¥", CNY: "¥" };
+    return symbols[currency] || currency;
+  }
+
+  function formatCurrencyValue(amount: number, currency: string): string {
+    const symbol = getCurrencySymbol(currency);
+    if (currency === "KRW" || currency === "JPY") return `${symbol}${Math.round(amount).toLocaleString()}`;
+    return `${symbol}${amount.toLocaleString(undefined, { minimumFractionDigits: 2, maximumFractionDigits: 2 })}`;
+  }
+
+  const totalValue = positions.reduce((s, p) => {
+    const valueRaw = p.market_value || p.quantity * (p.current_price || p.avg_price);
+    const src = (p.stock_currency || p.currency || "USD").toUpperCase();
+    return s + convertAmount(valueRaw, src, displayCurrency);
+  }, 0);
+  const totalCost = positions.reduce((s, p) => {
+    const src = (p.currency || p.avg_price_currency || p.stock_currency || "USD").toUpperCase();
+    return s + convertAmount(p.quantity * p.avg_price, src, displayCurrency);
+  }, 0);
   const totalGL = totalValue - totalCost;
 
   return (
     <div>
-      <h1 className="text-2xl font-bold mb-6">Portfolio</h1>
+      <div className="portfolio-header">
+        <h1 className="text-2xl font-bold">Portfolio</h1>
+        <div className="currency-toggle">
+          {["USD", "GBP", "KRW", "EUR", "JPY"].map((cur) => (
+            <button
+              key={cur}
+              className={`currency-btn ${displayCurrency === cur ? "active" : ""}`}
+              onClick={() => setDisplayCurrency(cur)}
+            >
+              {getCurrencySymbol(cur)} {cur}
+            </button>
+          ))}
+        </div>
+      </div>
 
       {/* Summary */}
       <div className="grid grid-cols-3 gap-3 mb-6">
         <div className="bg-bg-card border border-border rounded-lg p-4">
           <div className="text-text-muted text-xs mb-1">Total Value</div>
-          <div className="text-text-primary font-mono font-bold text-xl">${totalValue.toLocaleString(undefined, { minimumFractionDigits: 2, maximumFractionDigits: 2 })}</div>
+          <div className="text-text-primary font-mono font-bold text-xl">{formatCurrencyValue(totalValue, displayCurrency)}</div>
         </div>
         <div className="bg-bg-card border border-border rounded-lg p-4">
           <div className="text-text-muted text-xs mb-1">Total Cost</div>
-          <div className="text-text-primary font-mono font-bold text-xl">${totalCost.toLocaleString(undefined, { minimumFractionDigits: 2, maximumFractionDigits: 2 })}</div>
+          <div className="text-text-primary font-mono font-bold text-xl">{formatCurrencyValue(totalCost, displayCurrency)}</div>
         </div>
         <div className="bg-bg-card border border-border rounded-lg p-4">
           <div className="text-text-muted text-xs mb-1">Total P&L</div>
           <div className={`font-mono font-bold text-xl ${totalGL >= 0 ? "text-accent-green" : "text-accent-red"}`}>
-            {totalGL >= 0 ? "+" : ""}${totalGL.toLocaleString(undefined, { minimumFractionDigits: 2, maximumFractionDigits: 2 })}
+            {totalGL >= 0 ? "+" : ""}{formatCurrencyValue(Math.abs(totalGL), displayCurrency)}
           </div>
         </div>
       </div>
@@ -120,36 +346,248 @@ export default function PortfolioPage() {
         </div>
       </div>
 
+      {/* OCR Screenshot Import */}
+      <div className="bg-bg-card border border-border rounded-lg p-4 mb-6">
+        <h3 className="text-text-secondary text-sm font-semibold mb-3">Import from Screenshot (OCR)</h3>
+        <div
+          className={`border-2 border-dashed ${isDragging ? "border-accent-blue bg-accent-blue/5" : "border-border"} rounded-lg p-10 text-center cursor-pointer mb-4`}
+          onDragOver={(e) => {
+            e.preventDefault();
+            setIsDragging(true);
+          }}
+          onDragLeave={(e) => {
+            e.preventDefault();
+            setIsDragging(false);
+          }}
+          onDrop={(e) => {
+            e.preventDefault();
+            setIsDragging(false);
+            const f = e.dataTransfer.files?.[0];
+            if (f) uploadForOcr(f);
+          }}
+          onClick={() => document.getElementById("ocr-file-input")?.click()}
+        >
+          {isProcessing ? (
+            <p className="text-accent-green animate-pulse font-mono">AI가 포지션을 분석중...</p>
+          ) : (
+            <>
+              <span className="text-3xl mb-3 block">📸</span>
+              <p className="text-text-secondary text-sm">Trading 212 / IBKR 스크린샷을 드래그하세요</p>
+            </>
+          )}
+        </div>
+        <input
+          id="ocr-file-input"
+          type="file"
+          accept="image/*"
+          className="hidden"
+          onChange={(e) => {
+            const f = e.target.files?.[0];
+            if (f) uploadForOcr(f);
+          }}
+        />
+        {ocrError && <p className="text-accent-red text-sm mb-3">{ocrError}</p>}
+        {ocrPositions.length > 0 && (
+          <div>
+            <div className="flex items-center justify-between mb-2">
+              <div className="text-text-primary text-sm">
+                Import Results: {ocrPositions.length} positions
+              </div>
+              <div className="text-text-muted text-xs">
+                Account Currency: <span className="font-mono text-text-primary">{ocrAccountCurrency}</span>
+              </div>
+            </div>
+            {ocrWarnings.length > 0 && (
+              <details className="mb-3 bg-accent-yellow/10 border border-accent-yellow/30 rounded-md p-3">
+                <summary className="text-accent-yellow text-sm cursor-pointer">Warnings ({ocrWarnings.length})</summary>
+                <ul className="mt-2 space-y-1 text-xs text-text-secondary">
+                  {ocrWarnings.map((w, i) => <li key={i}>- {w}</li>)}
+                </ul>
+              </details>
+            )}
+            <div className="overflow-auto border border-border rounded-md mb-3">
+              <table className="w-full text-xs ocr-result-table">
+                <thead>
+                  <tr className="border-b border-border">
+                    <th className="text-left px-3 py-2 text-text-muted">Ticker</th>
+                    <th className="text-left px-3 py-2 text-text-muted">Exchange</th>
+                    <th className="text-left px-3 py-2 text-text-muted">Qty</th>
+                    <th className="text-left px-3 py-2 text-text-muted">Avg</th>
+                    <th className="text-left px-3 py-2 text-text-muted">Now</th>
+                    <th className="text-left px-3 py-2 text-text-muted">Value ({ocrAccountCurrency})</th>
+                    <th className="text-left px-3 py-2 text-text-muted">P&L %</th>
+                    <th className="text-left px-3 py-2 text-text-muted">Conf</th>
+                  </tr>
+                </thead>
+                <tbody>
+                  {ocrPositions.map((p, i) => (
+                    <tr key={`${p.ticker}-${i}`} className="border-b border-border/40">
+                      {(() => {
+                        const rowKey = `${p.ticker}-${i}`;
+                        const opts = exchangeOptions[rowKey] || [];
+                        const hasMultiple = opts.length > 1;
+                        return (
+                          <>
+                      <td className="px-3 py-2 text-accent-green font-mono">{p.ticker}</td>
+                      <td className="px-3 py-2 text-text-primary font-mono">
+                        {hasMultiple ? (
+                          <select
+                            className="bg-bg-primary border border-border rounded px-2 py-1 text-xs"
+                            value={exchangeSelections[rowKey] || ""}
+                            onChange={(e) => handleExchangeChange(i, e.target.value)}
+                          >
+                            {opts.map((o) => (
+                              <option key={o.exchange} value={o.exchange}>
+                                {o.exchange} ({o.currency})
+                              </option>
+                            ))}
+                          </select>
+                        ) : (
+                          <span className="text-text-muted text-xs">{(opts[0]?.exchange || p.exchange || p.stock_currency || "Default")}</span>
+                        )}
+                      </td>
+                      <td className="px-3 py-2 text-text-primary font-mono">
+                        <input
+                          type="number"
+                          value={p.quantity ?? 0}
+                          onChange={(e) => updateOcrPosition(i, "quantity", e.target.value)}
+                          className="w-28 bg-bg-primary border border-border rounded px-2 py-1"
+                        />
+                      </td>
+                      <td className="px-3 py-2 text-text-primary font-mono">
+                        <input
+                          type="number"
+                          value={p.avg_price ?? 0}
+                          onChange={(e) => updateOcrPosition(i, "avg_price", e.target.value)}
+                          className="w-24 bg-bg-primary border border-border rounded px-2 py-1"
+                        />
+                        <span className="ml-1 text-text-muted">{p.avg_price_currency || p.stock_currency || "USD"}</span>
+                      </td>
+                      <td className="px-3 py-2 text-text-primary font-mono">
+                        {p.current_price != null ? `${p.current_price.toFixed(2)} ${p.stock_currency || ""}` : "—"}
+                      </td>
+                      <td className="px-3 py-2 text-text-primary font-mono">
+                        {p.current_value_account != null ? p.current_value_account.toLocaleString() : "—"}
+                      </td>
+                      <td className={`px-3 py-2 font-mono ${(p.pnl_pct || 0) >= 0 ? "text-accent-green" : "text-accent-red"}`}>
+                        {p.pnl_pct != null ? `${p.pnl_pct >= 0 ? "+" : ""}${p.pnl_pct.toFixed(2)}%` : "—"}
+                      </td>
+                      <td className="px-3 py-2">
+                        {p.confidence === "high" ? "✅" : p.confidence === "medium" ? "⚠️" : "❌"}
+                      </td>
+                          </>
+                        );
+                      })()}
+                    </tr>
+                  ))}
+                </tbody>
+              </table>
+            </div>
+            <div className="flex justify-end gap-2">
+              <button
+                onClick={() => { setOcrPositions([]); setOcrWarnings([]); setOcrError(""); }}
+                className="px-5 py-2 rounded-md border border-border text-text-secondary"
+              >
+                Cancel
+              </button>
+              <button onClick={importOcrPositions} className="bg-accent-green text-bg-primary px-5 py-2 rounded-md font-semibold hover:opacity-90 transition-opacity">
+                ✅ Add All to Portfolio
+              </button>
+            </div>
+          </div>
+        )}
+      </div>
+
       {/* Positions Table */}
       {positions.length > 0 ? (
         <div className="bg-bg-card border border-border rounded-lg overflow-hidden">
           <table className="w-full text-sm">
             <thead>
               <tr className="border-b border-border">
-                {["Ticker", "Qty", "Avg Price", "Price", "Value", "P&L", "P&L %"].map((h) => (
+                {["Ticker", "Exchange", "Qty", "Avg Price", "Price", "Value", "P&L", "P&L %", "Actions"].map((h) => (
                   <th key={h} className="text-left px-4 py-3 text-text-muted font-medium">{h}</th>
                 ))}
               </tr>
             </thead>
             <tbody>
               {positions.map((p, i) => {
+                const pid = p.id || `${p.ticker}-${i}`;
                 const price = p.current_price || p.avg_price;
-                const value = p.market_value || p.quantity * price;
-                const gl = p.pnl ?? (value - p.quantity * p.avg_price);
+                const valueRaw = p.market_value || p.quantity * price;
+                const srcValueCurrency = (p.stock_currency || p.currency || "USD").toUpperCase();
+                const value = convertAmount(valueRaw, srcValueCurrency, displayCurrency);
+                const costRaw = p.quantity * p.avg_price;
+                const srcCostCurrency = (p.currency || p.avg_price_currency || p.stock_currency || "USD").toUpperCase();
+                const cost = convertAmount(costRaw, srcCostCurrency, displayCurrency);
+                const gl = p.pnl != null ? convertAmount(p.pnl, srcValueCurrency, displayCurrency) : (value - cost);
                 const glPct = p.pnl_pct ?? ((price / p.avg_price - 1) * 100);
                 return (
-                  <tr key={p.id || `${p.ticker}-${i}`} className="border-b border-border/50 hover:bg-bg-hover/30">
+                  <tr key={pid} className="border-b border-border/50 hover:bg-bg-hover/30">
                     <td className="px-4 py-2.5 font-mono font-semibold text-accent-green">{p.ticker}</td>
-                    <td className="px-4 py-2.5 font-mono text-text-primary">{p.quantity}</td>
-                    <td className="px-4 py-2.5 font-mono text-text-primary">${p.avg_price.toFixed(2)}</td>
-                    <td className="px-4 py-2.5 font-mono text-text-primary">${price.toFixed(2)}</td>
-                    <td className="px-4 py-2.5 font-mono text-text-primary">${value.toLocaleString(undefined, { minimumFractionDigits: 2 })}</td>
+                    <td className="px-4 py-2.5 font-mono text-text-muted">{p.exchange || "—"}</td>
+                    <td className="px-4 py-2.5 font-mono text-text-primary">
+                      {editingId === pid ? (
+                        <input
+                          type="number"
+                          step="any"
+                          value={editValues.qty}
+                          onChange={(e) => setEditValues((prev) => ({ ...prev, qty: e.target.value }))}
+                          className="w-28 bg-bg-primary border border-accent-blue rounded px-2 py-1"
+                          autoFocus
+                        />
+                      ) : (
+                        p.quantity
+                      )}
+                    </td>
+                    <td className="px-4 py-2.5 font-mono text-text-primary">
+                      {editingId === pid ? (
+                        <input
+                          type="number"
+                          step="0.01"
+                          value={editValues.avgPrice}
+                          onChange={(e) => setEditValues((prev) => ({ ...prev, avgPrice: e.target.value }))}
+                          className="w-24 bg-bg-primary border border-accent-blue rounded px-2 py-1"
+                        />
+                      ) : (
+                        <>${p.avg_price.toFixed(2)}</>
+                      )}
+                    </td>
+                    <td className="px-4 py-2.5 font-mono text-text-primary">{formatCurrencyValue(convertAmount(price, srcValueCurrency, displayCurrency), displayCurrency)}</td>
+                    <td className="px-4 py-2.5 font-mono text-text-primary">{formatCurrencyValue(value, displayCurrency)}</td>
                     <td className={`px-4 py-2.5 font-mono ${gl >= 0 ? "text-accent-green" : "text-accent-red"}`}>
-                      {gl >= 0 ? "+" : ""}${gl.toFixed(2)}
+                      {gl >= 0 ? "+" : ""}{formatCurrencyValue(Math.abs(gl), displayCurrency)}
                     </td>
                     <td className={`px-4 py-2.5 font-mono ${glPct >= 0 ? "text-accent-green" : "text-accent-red"}`}>
                       {glPct >= 0 ? "+" : ""}{glPct.toFixed(1)}%
                     </td>
+                    <td className="px-4 py-2.5 text-right">
+                      {editingId === pid ? (
+                        <div className="flex gap-1 justify-end">
+                          <button onClick={() => handleSaveEdit(pid)} className="w-8 h-8 rounded bg-accent-green/20 hover:bg-accent-green/30">✓</button>
+                          <button onClick={() => setEditingId(null)} className="w-8 h-8 rounded bg-bg-primary hover:bg-bg-hover">✕</button>
+                        </div>
+                      ) : (
+                        <div className="flex gap-1 justify-end">
+                          <button
+                            onClick={() => {
+                              setEditingId(pid);
+                              setEditValues({ qty: String(p.quantity), avgPrice: String(p.avg_price) });
+                            }}
+                            className="w-8 h-8 rounded hover:bg-bg-hover"
+                            title="Edit position"
+                          >
+                            ✏️
+                          </button>
+                          <button
+                            onClick={() => setDeleteConfirmId(pid)}
+                            className="w-8 h-8 rounded hover:bg-accent-red/20"
+                            title="Delete position"
+                          >
+                            🗑️
+                          </button>
+                        </div>
+                      )}
+                    </td>
                   </tr>
                 );
               })}
@@ -161,6 +599,19 @@ export default function PortfolioPage() {
           No positions yet. Add your first position above.
         </div>
       ) : null}
+
+      {deleteConfirmId && (
+        <div className="fixed inset-0 bg-black/60 flex items-center justify-center z-[1000]" onClick={() => setDeleteConfirmId(null)}>
+          <div className="bg-bg-card border border-border rounded-xl p-6 max-w-sm w-full" onClick={(e) => e.stopPropagation()}>
+            <p className="text-text-primary mb-1">정말 삭제하시겠습니까?</p>
+            <p className="text-text-muted text-sm mb-4">이 작업은 되돌릴 수 없습니다.</p>
+            <div className="flex justify-end gap-2">
+              <button onClick={() => setDeleteConfirmId(null)} className="px-4 py-2 border border-border rounded-md text-text-secondary">Cancel</button>
+              <button onClick={() => handleDelete(deleteConfirmId)} className="px-4 py-2 bg-accent-red text-white rounded-md">Delete</button>
+            </div>
+          </div>
+        </div>
+      )}
     </div>
   );
 }

atlas-terminal/apps/web/src/app/research/page.tsx

@@ -17,6 +17,7 @@ interface RadarData {
 
 export default function ResearchPage() {
   const { ticker } = useTicker();
+  const [assetType, setAssetType] = useState<string>("equity");
   const [piotroski, setPiotroski] = useState<PiotroskiData | null>(null);
   const [radar, setRadar] = useState<RadarData | null>(null);
   const [aiAnalysis, setAiAnalysis] = useState<string>("");
@@ -28,9 +29,11 @@ export default function ResearchPage() {
     Promise.all([
       fetch(`/api/market/piotroski/${ticker}`).then((r) => r.ok ? r.json() : null),
       fetch(`/api/market/radar/${ticker}`).then((r) => r.ok ? r.json() : null),
-    ]).then(([p, r]) => {
+      fetch(`/api/market/overview/${ticker}`).then((r) => r.ok ? r.json() : null),
+    ]).then(([p, r, o]) => {
       setPiotroski(p);
       setRadar(r);
+      setAssetType(o?.asset_type || "equity");
       setLoading(false);
     }).catch(() => setLoading(false));
   }, [ticker]);
@@ -79,6 +82,7 @@ export default function ResearchPage() {
         <span className="text-accent-green">{ticker}</span> Research
       </h1>
 
+      {assetType === "equity" ? (
       <div className="grid grid-cols-2 gap-4 mb-6">
         {/* Piotroski F-Score */}
         <div className="bg-bg-card border border-border rounded-lg p-5">
@@ -127,6 +131,23 @@ export default function ResearchPage() {
           )}
         </div>
       </div>
+      ) : assetType === "etf" ? (
+        <div className="bg-bg-card border border-border rounded-lg p-5 mb-6">
+          <h3 className="text-text-secondary text-sm font-semibold mb-3">ETF Research</h3>
+          <div className="text-text-secondary text-sm">
+            Holdings Analysis, Sector Breakdown, Overlap Analysis를 우선 제공합니다.
+            Piotroski/F-Score 및 기업 재무 레이더는 ETF에 적용되지 않습니다.
+          </div>
+        </div>
+      ) : (
+        <div className="bg-bg-card border border-border rounded-lg p-5 mb-6">
+          <h3 className="text-text-secondary text-sm font-semibold mb-3">Commodity Research</h3>
+          <div className="text-text-secondary text-sm">
+            Seasonal Analysis와 Supply/Demand 요인을 중심으로 분석합니다.
+            주식 전용 지표(F-Score, DuPont)는 표시하지 않습니다.
+          </div>
+        </div>
+      )}
 
       {/* AI Analysis */}
       <div className="bg-bg-card border border-border rounded-lg p-5">

atlas-terminal/apps/web/src/app/screener/page.tsx

@@ -0,0 +1,173 @@
+"use client";
+import { useState } from "react";
+
+interface ScreenerRow {
+  ticker: string;
+  name?: string;
+  sector?: string;
+  market_cap?: number;
+  pe?: number;
+  div_yield?: number;
+  price?: number;
+  change_pct?: number;
+}
+
+interface BacktestResult {
+  error?: string;
+  total_return_pct?: number;
+  benchmark_return_pct?: number;
+  alpha?: number;
+  sharpe_ratio?: number;
+}
+
+export default function ScreenerPage() {
+  const [tab, setTab] = useState<"screener" | "backtest">("screener");
+  const [rows, setRows] = useState<ScreenerRow[]>([]);
+  const [loading, setLoading] = useState(false);
+  const [peMax, setPeMax] = useState("25");
+  const [sector, setSector] = useState("");
+  const [divMin, setDivMin] = useState("");
+
+  const [btTicker, setBtTicker] = useState("AAPL");
+  const [strategy, setStrategy] = useState("sma_crossover");
+  const [startDate, setStartDate] = useState("2024-01-01");
+  const [endDate, setEndDate] = useState("2026-03-01");
+  const [btResult, setBtResult] = useState<BacktestResult | null>(null);
+  const [btLoading, setBtLoading] = useState(false);
+
+  async function runScreener() {
+    setLoading(true);
+    try {
+      const res = await fetch("/api/screener/search", {
+        method: "POST",
+        headers: { "Content-Type": "application/json" },
+        body: JSON.stringify({
+          pe_max: peMax ? parseFloat(peMax) : undefined,
+          sector: sector || undefined,
+          div_yield_min: divMin ? parseFloat(divMin) : undefined,
+        }),
+      });
+      const data = await res.json();
+      setRows(Array.isArray(data) ? data : []);
+    } catch {
+      setRows([]);
+    } finally {
+      setLoading(false);
+    }
+  }
+
+  async function runBacktest() {
+    setBtLoading(true);
+    try {
+      const res = await fetch("/api/screener/backtest", {
+        method: "POST",
+        headers: { "Content-Type": "application/json" },
+        body: JSON.stringify({
+          ticker: btTicker,
+          strategy,
+          start_date: startDate,
+          end_date: endDate,
+        }),
+      });
+      setBtResult(await res.json());
+    } catch {
+      setBtResult(null);
+    } finally {
+      setBtLoading(false);
+    }
+  }
+
+  return (
+    <div>
+      <h1 className="text-2xl font-bold mb-4">Stock Screener</h1>
+
+      <div className="flex gap-1 mb-4 bg-bg-card rounded-lg p-1 w-fit">
+        <button
+          onClick={() => setTab("screener")}
+          className={`px-4 py-2 rounded-md text-sm font-medium ${tab === "screener" ? "bg-accent-green text-bg-primary" : "text-text-secondary"}`}
+        >
+          Screener
+        </button>
+        <button
+          onClick={() => setTab("backtest")}
+          className={`px-4 py-2 rounded-md text-sm font-medium ${tab === "backtest" ? "bg-accent-green text-bg-primary" : "text-text-secondary"}`}
+        >
+          Backtest
+        </button>
+      </div>
+
+      {tab === "screener" ? (
+        <div className="bg-bg-card border border-border rounded-lg p-4">
+          <div className="flex flex-wrap gap-2 mb-3">
+            <input value={peMax} onChange={(e) => setPeMax(e.target.value)} placeholder="P/E < 25" className="bg-bg-primary border border-border rounded px-3 py-2 text-sm" />
+            <input value={sector} onChange={(e) => setSector(e.target.value)} placeholder="Sector (optional)" className="bg-bg-primary border border-border rounded px-3 py-2 text-sm" />
+            <input value={divMin} onChange={(e) => setDivMin(e.target.value)} placeholder="Div Yield > %" className="bg-bg-primary border border-border rounded px-3 py-2 text-sm" />
+            <button onClick={runScreener} className="bg-accent-green text-bg-primary px-4 py-2 rounded font-semibold">
+              {loading ? "Running..." : "Run Screener"}
+            </button>
+          </div>
+          <div className="overflow-auto border border-border rounded-md">
+            <table className="w-full text-xs">
+              <thead>
+                <tr className="border-b border-border">
+                  {["Ticker", "Name", "Sector", "Price", "P/E", "MCap", "Change"].map((h) => (
+                    <th key={h} className="text-left px-3 py-2 text-text-muted">{h}</th>
+                  ))}
+                </tr>
+              </thead>
+              <tbody>
+                {rows.map((r, i) => (
+                  <tr key={`${r.ticker}-${i}`} className="border-b border-border/40">
+                    <td className="px-3 py-2 text-accent-green font-mono">{r.ticker}</td>
+                    <td className="px-3 py-2 text-text-primary">{r.name || "—"}</td>
+                    <td className="px-3 py-2 text-text-secondary">{r.sector || "—"}</td>
+                    <td className="px-3 py-2 text-text-primary font-mono">{r.price != null ? `$${r.price.toFixed(2)}` : "—"}</td>
+                    <td className="px-3 py-2 text-text-primary font-mono">{r.pe != null ? r.pe.toFixed(1) : "—"}</td>
+                    <td className="px-3 py-2 text-text-primary font-mono">{r.market_cap ? `${(r.market_cap / 1e9).toFixed(1)}B` : "—"}</td>
+                    <td className={`px-3 py-2 font-mono ${((r.change_pct || 0) >= 0) ? "text-accent-green" : "text-accent-red"}`}>
+                      {r.change_pct != null ? `${r.change_pct >= 0 ? "+" : ""}${r.change_pct.toFixed(2)}%` : "—"}
+                    </td>
+                  </tr>
+                ))}
+              </tbody>
+            </table>
+          </div>
+        </div>
+      ) : (
+        <div className="bg-bg-card border border-border rounded-lg p-4">
+          <div className="flex flex-wrap gap-2 mb-3">
+            <input value={btTicker} onChange={(e) => setBtTicker(e.target.value.toUpperCase())} placeholder="Ticker" className="bg-bg-primary border border-border rounded px-3 py-2 text-sm" />
+            <select value={strategy} onChange={(e) => setStrategy(e.target.value)} className="bg-bg-primary border border-border rounded px-3 py-2 text-sm">
+              <option value="sma_crossover">SMA Crossover</option>
+              <option value="rsi_oversold">RSI Oversold</option>
+              <option value="buy_and_hold">Buy & Hold</option>
+            </select>
+            <input type="date" value={startDate} onChange={(e) => setStartDate(e.target.value)} className="bg-bg-primary border border-border rounded px-3 py-2 text-sm" />
+            <input type="date" value={endDate} onChange={(e) => setEndDate(e.target.value)} className="bg-bg-primary border border-border rounded px-3 py-2 text-sm" />
+            <button onClick={runBacktest} className="bg-accent-green text-bg-primary px-4 py-2 rounded font-semibold">
+              {btLoading ? "Running..." : "Run Backtest"}
+            </button>
+          </div>
+          {btResult && !btResult.error && (
+            <div className="grid grid-cols-2 lg:grid-cols-4 gap-3">
+              <Metric label="Return" value={`${btResult.total_return_pct}%`} />
+              <Metric label="Benchmark" value={`${btResult.benchmark_return_pct}%`} />
+              <Metric label="Alpha" value={`${btResult.alpha}%`} />
+              <Metric label="Sharpe" value={`${btResult.sharpe_ratio}`} />
+            </div>
+          )}
+          {btResult?.error && <p className="text-accent-red text-sm">{btResult.error}</p>}
+        </div>
+      )}
+    </div>
+  );
+}
+
+function Metric({ label, value }: { label: string; value: string }) {
+  return (
+    <div className="bg-bg-primary border border-border rounded-md p-3">
+      <div className="text-text-muted text-xs">{label}</div>
+      <div className="text-text-primary font-mono font-semibold">{value}</div>
+    </div>
+  );
+}

atlas-terminal/apps/web/src/app/valuation/page.tsx

@@ -51,6 +51,7 @@ type ValuationTab = "dcf" | "sensitivity" | "montecarlo" | "tornado" | "reverse"
 
 export default function ValuationPage() {
   const { ticker } = useTicker();
+  const [assetType, setAssetType] = useState<string>("equity");
   const [inputs, setInputs] = useState<DCFInputs | null>(null);
   const [consensus, setConsensus] = useState<Consensus | null>(null);
   const [dcfResult, setDcfResult] = useState<DCFResult | null>(null);
@@ -79,9 +80,11 @@ export default function ValuationPage() {
       fetch(`/api/valuation/dcf-inputs/${ticker}`).then((r) => r.ok ? r.json() : null),
       fetch(`/api/valuation/consensus/${ticker}`).then((r) => r.ok ? r.json() : null),
       fetch(`/api/valuation/smart-defaults/${ticker}`).then((r) => r.ok ? r.json() : null),
-    ]).then(([i, c, d]) => {
+      fetch(`/api/market/overview/${ticker}`).then((r) => r.ok ? r.json() : null),
+    ]).then(([i, c, d, o]) => {
       setInputs(i);
       setConsensus(c);
+      setAssetType(o?.asset_type || "equity");
       if (d?.wacc) setWacc(d.wacc);
       if (d?.terminal_growth) setTerminalGrowth(d.terminal_growth);
       if (d?.fcf_growth) setFcfGrowth(d.fcf_growth);
@@ -169,6 +172,26 @@ export default function ValuationPage() {
 
   if (loading) return <div className="flex items-center justify-center h-64"><div className="text-accent-green animate-pulse font-mono">Loading...</div></div>;
 
+  if (assetType !== "equity") {
+    return (
+      <div>
+        <h1 className="text-2xl font-bold mb-6">
+          <span className="text-accent-green">{ticker}</span> Valuation
+        </h1>
+        <div className="bg-bg-card border border-border rounded-lg p-5">
+          <h3 className="text-text-secondary text-sm font-semibold mb-3">
+            {assetType === "etf" ? "ETF Valuation Mode" : "Commodity Valuation Mode"}
+          </h3>
+          <div className="text-text-secondary text-sm">
+            {assetType === "etf"
+              ? "NAV Premium/Discount, Expense 비교, Tracking Error 중심으로 평가합니다. DCF는 주식(EQUITY) 전용입니다."
+              : "Futures Curve(Contango/Backwardation), Cost of Carry 중심으로 평가합니다. DCF는 주식(EQUITY) 전용입니다."}
+          </div>
+        </div>
+      </div>
+    );
+  }
+
   return (
     <div>
       <h1 className="text-2xl font-bold mb-6">

atlas-terminal/claude.md

@@ -0,0 +1,485 @@
+# claude.md — ATLAS Terminal Build Guide
+
+> 이 문서는 Claude Code 에이전트가 프로젝트를 빌드할 때 참조하는 마스터 가이드입니다.
+> 모든 에이전트는 작업 시작 전 이 문서를 반드시 읽어야 합니다.
+> **마지막 수정: 2026-03-21**
+
+---
+
+## 1. Project Identity
+
+| 항목 | 내용 |
+|------|------|
+| **이름** | ATLAS Terminal (Advanced Terminal for Liquid Asset Surveillance) |
+| **목적** | 개인 투자자에게 기관급 투자 리서치를 단일 인터페이스로 제공 |
+| **핵심 철학** | 금융 정보 비대칭 해소 — 기술로 리테일 투자자의 무기를 평등하게 |
+| **디자인** | Bloomberg Terminal의 정보 밀도 + Notion의 깔끔함 + 다크 모드 |
+| **스택** | Next.js 14 (App Router) + FastAPI + SQLite/PostgreSQL + Gemini API |
+| **프로젝트 루트** | `/Users/seonpil/Library/Mobile Documents/com~apple~CloudDocs/Documents/FQDC Project/atlas-terminal/` |
+
+---
+
+## 2. Architecture Principles (절대 규칙)
+
+### 2.1 하이브리드 분리 원칙
+```
+정성 데이터 (Qualitative) → LLM (Gemini) → 텍스트 분석만
+정량 데이터 (Quantitative) → Pandas + yfinance/yahooquery → 숫자/계산만
+```
+- **절대 LLM에 숫자 계산을 맡기지 않는다** — LLM은 텍스트 분석, 번역, 요약만 담당
+- 모든 재무 지표(DCF, DuPont, Altman Z, F-Score)는 Python 코드로 계산
+- 이 원칙을 위반하면 비용 폭발 + 정확도 하락
+
+### 2.2 토큰 최적화 (비용 통제)
+- 10-K 원문을 LLM에 보내기 전 반드시 `sec_parser.py`로 Item 1A~9A만 추출
+- `text_chunker.py`의 `smart_chunk()`로 10,000자 이내로 압축 (head+tail 보존)
+- Gemini 호출은 탭당 최대 1~2회로 제한
+- 429 에러 시 `_generate_with_retry()`로 60초 대기 후 재시도
+
+### 2.3 다단계 폴백 체인
+모든 외부 API 호출은 아래 순서를 따른다:
+```
+yfinance (1순위) → yahooquery (2순위) → fast_info (3순위) → info (4순위)
+→ balance_sheet/cashflow (5순위) → TTM 분기 합산 (6순위) → 수동 입력 (최후)
+```
+- 모든 숫자 파싱에 `_safe_float()` 사용 (`server/utils/safe_float.py`)
+- 실패 시 빈 DataFrame 또는 None 반환, 절대 에러를 UI에 노출하지 않음
+
+### 2.4 모듈 분리 원칙
+- **한 파일 = 한 책임** — 단일 파일 3000줄 금지
+- 파일당 최대 300줄 목표
+- 비즈니스 로직 → `server/services/`, API 엔드포인트 → `server/routers/`
+- 프론트엔드 컴포넌트는 기능별로 분리
+
+### 2.5 Multi-Key Column Lookup (중요!)
+yfinance와 yahooquery는 같은 데이터의 컬럼명이 다르다:
+- yfinance: `"Total Revenue"` (띄어쓰기)
+- yahooquery: `"TotalRevenue"` (CamelCase)
+
+프론트엔드에서 **파이프 구분자 패턴**으로 해결:
+```tsx
+function getValue(periodData: Record<string, any>, key: string) {
+  const keys = key.split("|");
+  for (const k of keys) {
+    const v = periodData[k.trim()];
+    if (v != null && typeof v === "number") return v;
+  }
+  return null;
+}
+// 사용 예: getValue(data, "TotalRevenue|Total Revenue|Revenue")
+```
+
+---
+
+## 3. 현재 File Structure (실제 아키텍처)
+
+```
+atlas-terminal/
+├── apps/web/                        # Next.js 14 프론트엔드
+│   ├── src/app/
+│   │   ├── layout.tsx               # 루트 레이아웃 (3-panel: Sidebar + Main + ChatPanel)
+│   │   ├── page.tsx                 # Overview (Sector, DuPont, Altman Z)
+│   │   ├── globals.css              # Tailwind + Terminal Noir 기본 스타일
+│   │   ├── research/page.tsx        # 10-K AI 분석 + Risk Factors
+│   │   ├── valuation/page.tsx       # 5-Tab: DCF, Sensitivity, Monte Carlo, Tornado, Reverse DCF
+│   │   ├── technical/page.tsx       # TradingView 캔들차트 + RSI/MACD/Bollinger/Fibonacci/MA
+│   │   ├── markets/page.tsx         # 재무제표 테이블 (YoY Growth + Margin %)
+│   │   ├── earnings/page.tsx        # EPS Beat/Miss + Revenue + Next Earnings
+│   │   ├── news/page.tsx            # Split-view: 기사 리스트 + iframe 원문
+│   │   ├── portfolio/page.tsx       # 포지션 CRUD + Risk Metrics
+│   │   ├── filings/page.tsx         # SEC 10-K 원문 (5개 섹션 탭 + AI 요약)
+│   │   ├── settings/page.tsx        # API Key 관리
+│   │   ├── components/
+│   │   │   ├── sidebar.tsx          # 좌측 네비게이션 (10개 메뉴)
+│   │   │   ├── ticker-bar.tsx       # 상단 실시간 지수 바 (S&P, NASDAQ, KOSPI, BTC)
+│   │   │   └── chat-panel.tsx       # 우측 AI Copilot 채팅
+│   │   └── lib/
+│   │       ├── use-ticker.ts        # 티커 상태 훅 (localStorage + CustomEvent)
+│   │       └── api.ts              # API 클라이언트 유틸
+│   ├── next.config.mjs              # /api/* → localhost:8000 프록시
+│   ├── tailwind.config.ts           # Terminal Noir 컬러 토큰
+│   └── package.json
+│
+├── server/                          # FastAPI 백엔드
+│   ├── main.py                      # FastAPI app + 14개 라우터 등록
+│   ├── routers/                     # API 엔드포인트 (14개 라우터)
+│   │   ├── analysis.py              # POST /api/analysis — Gemini LLM 분석
+│   │   ├── chat.py                  # /api/chat — AI Copilot
+│   │   ├── crypto.py                # /api/crypto — 암호화폐 가격
+│   │   ├── earnings.py              # /api/earnings/{ticker}/history|calendar|quarterly
+│   │   ├── edgar.py                 # /api/edgar — SEC 10-K 다운로드 + 파싱
+│   │   ├── estimates.py             # /api/estimates — 애널리스트 추정치
+│   │   ├── financials.py            # /api/financials/{ticker} — IS/BS/CF
+│   │   ├── fx.py                    # /api/fx — 환율
+│   │   ├── insider.py               # /api/insider/{ticker} — 내부자 거래
+│   │   ├── market_data.py           # /api/market — 주가/섹터/헬스체크
+│   │   ├── news.py                  # /api/news/{ticker} — Finviz + Google RSS
+│   │   ├── portfolio.py             # /api/portfolio — CRUD + Risk
+│   │   ├── technical.py             # /api/technical/{ticker} — 기술적 지표
+│   │   └── valuation.py             # /api/valuation — DCF, Sensitivity, Monte Carlo, Tornado, Reverse DCF
+│   ├── services/                    # 비즈니스 로직 (17개 서비스)
+│   │   ├── crypto_fetcher.py        # Bithumb + Binance API
+│   │   ├── dcf_engine.py            # excel_style_dcf, dcf_10y_2stage, reverse_dcf (scipy brentq)
+│   │   ├── financial_metrics.py     # DuPont, Altman Z, Piotroski F-Score
+│   │   ├── financial_metrics_ext.py # 확장 지표
+│   │   ├── fx_fetcher.py            # 환율 데이터
+│   │   ├── gemini_analysis.py       # Gemini 분석 로직
+│   │   ├── gemini_service.py        # Gemini API 래퍼 (retry, streaming)
+│   │   ├── market_data.py           # 시장 데이터 서비스
+│   │   ├── market_fetcher.py        # yfinance/yahooquery 폴백 체인
+│   │   ├── monte_carlo.py           # run_monte_carlo_dcf (numpy, 5000 sims)
+│   │   ├── news_aggregator.py       # RSS + Finviz + Google News
+│   │   ├── risk_metrics.py          # VaR, Sharpe, Sortino, MDD, Beta, Correlation
+│   │   ├── screenshot_ocr.py        # Gemini Vision OCR (포트폴리오 스크린샷)
+│   │   ├── sec_parser.py            # 10-K 다운로드 + HTML 파싱 + 섹션 추출 + 캐싱
+│   │   ├── sensitivity.py           # build_sensitivity_matrix, build_tornado_data
+│   │   ├── technical_analysis.py    # RSI, MACD, Bollinger, Ichimoku, ADX, Fibonacci
+│   │   └── text_chunker.py          # smart_chunk, clean_text_for_llm
+│   ├── db/                          # 데이터베이스 레이어
+│   │   ├── unified_repo.py          # SQLite/PostgreSQL 통합 인터페이스
+│   │   ├── cache.py                 # 캐시 저장소
+│   │   ├── database.py              # SQLite 커넥션
+│   │   ├── pg_database.py           # PostgreSQL 커넥션
+│   │   ├── portfolio_repo.py        # 포트폴리오 SQLite CRUD
+│   │   ├── pg_portfolio_repo.py     # 포트폴리오 PostgreSQL CRUD
+│   │   ├── pg_cache_repo.py         # PostgreSQL 캐시
+│   │   ├── dashboard_repo.py        # 대시보드 레이아웃 저장
+│   │   └── settings_repo.py         # 설정 저장소
+│   ├── models/
+│   │   ├── schemas.py               # Pydantic 모델 (요청/응답)
+│   │   └── db.py                    # DB 모델
+│   ├── ai/
+│   │   ├── llm_router.py            # LLM 프로바이더 라우팅
+│   │   └── context_builder.py       # 컨텍스트 빌더
+│   └── utils/
+│       ├── safe_float.py            # 안전한 숫자 파싱
+│       └── ticker_utils.py          # 티커 유틸리티
+│
+├── claude.md                        # 이 파일 (AI 에이전트 매뉴얼)
+├── requirements.txt                 # Python 의존성
+└── README.md
+```
+
+---
+
+## 4. Design System — "Terminal Noir"
+
+### 4.1 Tailwind 컬러 토큰 (`tailwind.config.ts`)
+```typescript
+colors: {
+  bg: {
+    primary: "#0A0A0F",    // 메인 배경
+    secondary: "#12121A",  // 서브 배경
+    card: "#1A1A26",       // 카드 서피스
+    hover: "#252536",      // 호버 상태
+  },
+  accent: {
+    green: "#00D4AA",      // 상승, CTA, 활성 (민트 그린)
+    red: "#FF4757",        // 하락, 경고
+    yellow: "#FFD93D",     // 주의, 하이라이트
+    blue: "#4DA6FF",       // 정보, 링크
+  },
+  text: {
+    primary: "#F3F4F6",    // 주 텍스트
+    secondary: "#9CA3AF",  // 보조 텍스트
+    muted: "#6B7280",      // 약한 라벨
+  },
+  border: { DEFAULT: "#2A2A3A" },
+}
+fontFamily: {
+  sans: ["Inter", "system-ui", "sans-serif"],
+  mono: ["JetBrains Mono", "monospace"],
+}
+```
+
+### 4.2 UI 규칙
+- **숫자**: 양수 = `text-accent-green` + `+` 접두사, 음수 = `text-accent-red`, 폰트 = `font-mono`
+- **카드**: `bg-bg-card border border-border rounded-lg p-5`
+- **로딩**: `text-accent-green animate-pulse font-mono "Loading data..."`
+- **AI 관련**: `text-accent-blue` 또는 인디고 계열
+- **에러**: `border-accent-red/30` 배경 + `text-accent-red` 텍스트
+
+### 4.3 3-Panel 레이아웃
+```
+┌──────────────────────────────────────────────────────────┐
+│  [ATLAS TERMINAL]  S&P 500 -1.51%  NASDAQ +2.81%  ...   │  ← TickerBar (h-52px, fixed top)
+├───────────┬──────────────────────────┬───────────────────┤
+│           │                          │                   │
+│ Sidebar   │    Main Content          │   AI Copilot      │
+│ w-260px   │    flex-1                │   w-380px         │
+│           │    p-7                   │                   │
+│ Overview  │                          │  Ask me anything  │
+│ Research  │    (각 페이지 콘텐츠)      │  about {ticker}   │
+│ Valuation │                          │                   │
+│ Technical │                          │  [Send]           │
+│ Markets   │                          │                   │
+│ Earnings  │                          │                   │
+│ News      │                          │                   │
+│ Portfolio │                          │                   │
+│ Filings   │                          │                   │
+│ Settings  │                          │                   │
+│           │                          │                   │
+└───────────┴──────────────────────────┴───────────────────┘
+```
+
+---
+
+## 5. API Endpoints (전체 목록)
+
+### 5.1 Market Data (`/api/market`)
+| Method | Path | 설명 |
+|--------|------|------|
+| GET | `/api/market/sector/{ticker}` | 섹터, 산업, 시총, PE, 베타, 52주 |
+| GET | `/api/market/health/{ticker}` | DuPont, Altman Z, Red Flags |
+| GET | `/api/market/price/{ticker}` | 현재가, 변동률 |
+| GET | `/api/market/indices` | S&P 500, NASDAQ, KOSPI, BTC |
+
+### 5.2 Financials (`/api/financials`)
+| Method | Path | 설명 |
+|--------|------|------|
+| GET | `/api/financials/{ticker}` | 손익계산서 (yfinance → yahooquery 폴백) |
+| GET | `/api/financials/balance/{ticker}` | 대차대조표 |
+| GET | `/api/financials/cashflow/{ticker}` | 현금흐름표 |
+
+### 5.3 Valuation (`/api/valuation`)
+| Method | Path | 설명 |
+|--------|------|------|
+| POST | `/api/valuation/dcf` | 10Y 2-Stage DCF |
+| POST | `/api/valuation/sensitivity` | WACC × Terminal Growth 매트릭스 |
+| POST | `/api/valuation/monte-carlo` | 5000회 시뮬레이션 + 히스토그램 |
+| POST | `/api/valuation/tornado` | 변수별 민감도 순위 |
+| POST | `/api/valuation/reverse-dcf` | 시장 내재 성장률 (scipy brentq) |
+
+### 5.4 Technical (`/api/technical`)
+| Method | Path | 설명 |
+|--------|------|------|
+| GET | `/api/technical/{ticker}` | RSI, MACD, Bollinger, MA, ADX, Ichimoku |
+| GET | `/api/technical/{ticker}/chart` | OHLCV 캔들 데이터 |
+
+### 5.5 Earnings (`/api/earnings`)
+| Method | Path | 설명 |
+|--------|------|------|
+| GET | `/api/earnings/{ticker}/history` | EPS Beat/Miss 이력 |
+| GET | `/api/earnings/{ticker}/calendar` | 다음 실적 발표일 |
+| GET | `/api/earnings/{ticker}/quarterly` | 분기별 매출/순이익 |
+
+### 5.6 Insider (`/api/insider`)
+| Method | Path | 설명 |
+|--------|------|------|
+| GET | `/api/insider/{ticker}` | 최근 내부자 거래 |
+| GET | `/api/insider/{ticker}/holders` | 기관투자자 보유 현황 |
+
+### 5.7 News (`/api/news`)
+| Method | Path | 설명 |
+|--------|------|------|
+| GET | `/api/news/{ticker}` | Finviz + Google News RSS |
+
+### 5.8 SEC EDGAR (`/api/edgar`)
+| Method | Path | 설명 |
+|--------|------|------|
+| POST | `/api/edgar/download` | 10-K 다운로드 (sec-edgar-downloader) |
+| GET | `/api/edgar/sections/{ticker}` | 10-K 섹션별 텍스트 (1A, 3, 7, 8, 9A) |
+
+### 5.9 기타
+| Prefix | 설명 |
+|--------|------|
+| `/api/analysis` | Gemini AI 분석 |
+| `/api/chat` | AI Copilot 대화 |
+| `/api/crypto` | 암호화폐 (Bithumb + Binance) |
+| `/api/fx` | 환율 |
+| `/api/estimates` | 애널리스트 추정치 |
+| `/api/portfolio` | 포트폴리오 CRUD + Risk Metrics |
+
+---
+
+## 6. Frontend Pages (10개)
+
+| 경로 | 파일 | 핵심 기능 |
+|------|------|----------|
+| `/` | `page.tsx` | Overview — 섹터/산업, 시총/PE/베타, Altman Z-Score, DuPont 분해 |
+| `/research` | `research/page.tsx` | 10-K AI 분석 — MD&A + Risk Factors (Gemini) |
+| `/valuation` | `valuation/page.tsx` | **5-Tab**: DCF, Sensitivity Matrix (WACC×TG), Monte Carlo (히스토그램), Tornado, Reverse DCF |
+| `/technical` | `technical/page.tsx` | TradingView 캔들차트 (lightweight-charts), RSI/MACD/ATR 카드, 이동평균 테이블, Bollinger, Fibonacci |
+| `/markets` | `markets/page.tsx` | 재무제표 테이블 — Revenue→EBITDA, YoY Growth 뱃지(초록/빨강), Margin % 행 |
+| `/earnings` | `earnings/page.tsx` | 다음 실적일, EPS Beat/Miss 바차트, 분기 매출/순이익 |
+| `/news` | `news/page.tsx` | Split-view — 좌측 기사 리스트(340px) + 우측 iframe 원문 보기 |
+| `/portfolio` | `portfolio/page.tsx` | 포지션 관리 + Risk Metrics (VaR, Sharpe, MDD) |
+| `/filings` | `filings/page.tsx` | SEC 10-K 원문 — 5개 섹션 탭 (Risk, MD&A, Financials, Legal, Controls) + AI Summary |
+| `/settings` | `settings/page.tsx` | Gemini API Key, SEC Email 설정 |
+
+---
+
+## 7. Ticker State Management
+
+**전역 티커 상태**는 React Context 없이 `localStorage` + `CustomEvent` 패턴으로 관리:
+
+```tsx
+// apps/web/src/app/lib/use-ticker.ts
+export function useTicker() {
+  const [ticker, setTicker] = useState(() =>
+    localStorage.getItem("atlas-ticker") || "MSFT"
+  );
+
+  // 다른 컴포넌트의 변경도 감지
+  useEffect(() => {
+    const handler = () => setTicker(localStorage.getItem("atlas-ticker") || "MSFT");
+    window.addEventListener("ticker-changed", handler);
+    return () => window.removeEventListener("ticker-changed", handler);
+  }, []);
+
+  const updateTicker = (t: string) => {
+    localStorage.setItem("atlas-ticker", t.toUpperCase());
+    window.dispatchEvent(new CustomEvent("ticker-changed"));
+  };
+
+  return { ticker, setTicker: updateTicker };
+}
+```
+
+**사용법**: 모든 페이지에서 `const { ticker } = useTicker();`로 현재 티커 접근.
+TickerBar의 검색창에서 `setTicker()`로 전역 변경.
+
+---
+
+## 8. Key Algorithms
+
+### DCF 10Y 2-Stage (`server/services/dcf_engine.py`)
+- Stage 1 (Y1-5): `FCF × (1 + growth)^t`
+- Stage 2 (Y6-10): growth linearly fades to terminal growth rate
+- Terminal Value at Y10: `FCF₁₀ × (1 + TG) / (WACC - TG)`
+- Enterprise Value = sum of discounted FCFs + discounted TV
+
+### Reverse DCF (`server/services/dcf_engine.py`)
+- scipy `brentq` root-finding: 현재 시가총액을 설명하는 성장률 역산
+- `f(g) = DCF(g) - market_cap = 0` 풀기
+
+### Monte Carlo (`server/services/monte_carlo.py`)
+- numpy로 5000회 시뮬레이션
+- growth, wacc, margin을 정규분포로 샘플링
+- 히스토그램 빈 + P(> current price) 계산
+
+### Sensitivity Matrix (`server/services/sensitivity.py`)
+- WACC (행) × Terminal Growth (열) 조합별 DCF 결과 매트릭스
+- Tornado: 각 변수를 ±20% 변동시켜 가격 영향 범위 계산, 영향력 순 정렬
+
+### DuPont 3-Factor
+`ROE = NPM × Asset Turnover × Equity Multiplier`
+
+### Altman Z-Score
+`Z = 1.2(WC/TA) + 1.4(RE/TA) + 3.3(EBIT/TA) + 0.6(MC/TL) + 1.0(Sales/TA)`
+
+### Technical Indicators (`server/services/technical_analysis.py`)
+- `ta` 라이브러리 사용: RSI, MACD, Bollinger Bands, Ichimoku Cloud, ADX
+- `detect_signals()`: MA 크로스, RSI 과매수/과매도, MACD 시그널
+- `compute_fibonacci_levels()`: 52주 고/저 기반 되돌림 레벨
+
+---
+
+## 9. Development Rules (가드레일)
+
+### 코드
+- TypeScript strict mode (프론트), Python type hints (백엔드)
+- 모든 API 호출 try/except; UI에 기술적 에러 노출 금지
+- 캐싱: 재무=TTL 300초, 10-K=영구, 환율=TTL 60초
+- `"use client"` — 모든 페이지 최상단에 필수 (App Router + hooks)
+
+### 프론트엔드 API 호출 패턴
+```tsx
+// Next.js rewrites가 /api/* → localhost:8000/api/* 프록시
+// 따라서 상대경로로 호출:
+fetch(`/api/market/sector/${ticker}`)
+fetch(`/api/valuation/dcf`, { method: "POST", body: JSON.stringify(params) })
+```
+
+### Gemini API
+- 요청당 최대 25,000자, temperature 0.2~0.4
+- 429 → 60초 대기 × 3회 재시도
+- 스트리밍: MD&A/Risk 분석은 `stream=True`
+
+### yfinance 주의사항
+- `earnings_history` 컬럼명: `epsActual`, `epsEstimate`, `surprisePercent` (camelCase)
+- `surprisePercent`는 소수 (0.0759 = 7.59%) → 프론트에서 `× 100` 필요
+- 날짜는 DataFrame index에 있음 (컬럼 아님) → `str(idx)[:10]`
+- 연간 데이터에 TTM 행 혼재 가능 → `_filter_annual()` 적용
+
+### 서버 실행
+```bash
+# 백엔드 (포트 8000)
+cd atlas-terminal
+PYTHONPATH="." python3 -m uvicorn server.main:app --port 8000 --host 0.0.0.0
+
+# 프론트엔드 (포트 3000)
+cd atlas-terminal/apps/web
+npm run dev
+```
+
+### Git
+- 커밋: `feat:`, `fix:`, `docs:`, `refactor:` 접두사
+- 브랜치: `main`, `dev`, `feat/기능명`
+
+---
+
+## 10. Dependencies
+
+### Python (`requirements.txt`)
+```
+fastapi>=0.110.0        uvicorn[standard]>=0.29.0
+pydantic>=2.7.0         google-generativeai>=0.8.0
+anthropic>=0.39.0       openai>=1.50.0
+beautifulsoup4>=4.12.0  requests>=2.31.0
+pandas>=2.0.0           lxml>=4.9.0
+python-dotenv>=1.0.0    yfinance>=0.2.40
+yahooquery>=2.2.0       sec-edgar-downloader>=5.0.0
+feedparser>=6.0.0       ta>=0.11.0
+numpy                   scipy
+aiosqlite>=0.20.0       asyncpg>=0.30.0
+pillow>=10.0.0
+```
+
+### Node.js (`apps/web/package.json`)
+```
+next: 14.2.35           react: ^18
+lightweight-charts: ^5.1.0
+tailwindcss: ^3.4.1     typescript: ^5
+```
+
+---
+
+## 11. Environment Variables
+```env
+GOOGLE_API_KEY=        # Gemini API
+SEC_EDGAR_EMAIL=       # SEC 정책 필수 (10-K 다운로드용)
+DATABASE_URL=          # PostgreSQL (없으면 SQLite 자동)
+NEWS_API_KEY=          # 선택
+DART_API_KEY=          # 한국 공시 (선택)
+```
+
+---
+
+## 12. 알려진 이슈 및 주의사항
+
+1. **`apps/web/app/` vs `apps/web/src/app/`**: 구 TanStack Start의 `app/` 디렉토리가 `_legacy_tanstack_app`으로 이름변경됨. Next.js는 `src/app/`을 사용. 절대 루트의 `app/` 디렉토리를 만들지 말 것.
+
+2. **Financial 데이터 혼합**: yahooquery는 12M + TTM 데이터를 섞어 반환할 수 있음. `server/routers/financials.py`의 `_filter_annual()` 함수가 TTM 필터링.
+
+3. **CORS**: `server/main.py`에서 `localhost:3000`, `localhost:3001`, `127.0.0.1:3000` 허용 설정됨.
+
+4. **Google Fonts**: `layout.tsx`의 `<head>`에서 Inter + JetBrains Mono 로드. `<link>` 태그 직접 삽입 방식.
+
+---
+
+## 13. 미구현 기능 (TODO)
+
+- [ ] Widget-based 대시보드 (react-grid-layout) — 패키지 설치됨, 미구현
+- [ ] Enhanced AI Copilot — 인용/추론 단계 표시
+- [ ] Multi-LLM 시스템 (Gemini + Claude + OpenAI provider abstraction) — `ai/llm_router.py` 스캐폴딩만
+- [ ] Extended DuPont 5-Factor 분석
+- [ ] DART (한국 공시) / EDINET (일본 공시) 통합
+- [ ] 포트폴리오 스크린샷 OCR (Gemini Vision) — 서비스 존재, UI 미연결
+- [ ] ⌘K 글로벌 커맨드 팔레트
+- [ ] Sankey (자금흐름), Radar (재무건전성) 차트
+- [ ] GitHub README 자동 업데이트 워크플로우
+
+---
+
+*마지막 수정: 2026-03-21*

atlas-terminal/server/main.py

@@ -44,7 +44,7 @@ app.add_middleware(
 )
 
 # --- Mount routers ---
-from server.routers import edgar, analysis, valuation, market_data, news, crypto, fx, portfolio, technical, financials, estimates, earnings, insider  # noqa: E402
+from server.routers import edgar, analysis, valuation, market_data, news, crypto, fx, portfolio, technical, financials, estimates, earnings, insider, screener, markets  # noqa: E402
 
 app.include_router(edgar.router, prefix="/api/edgar", tags=["SEC EDGAR"])
 app.include_router(analysis.router, prefix="/api/analysis", tags=["AI Analysis"])
@@ -55,10 +55,12 @@ app.include_router(estimates.router, prefix="/api/estimates", tags=["Estimates"]
 app.include_router(news.router, prefix="/api/news", tags=["News"])
 app.include_router(crypto.router, prefix="/api/crypto", tags=["Crypto"])
 app.include_router(fx.router, prefix="/api/fx", tags=["FX"])
+app.include_router(markets.router, prefix="/api/markets", tags=["Markets"])
 app.include_router(portfolio.router, prefix="/api/portfolio", tags=["Portfolio"])
 app.include_router(technical.router, prefix="/api/technical", tags=["Technical"])
 app.include_router(earnings.router, prefix="/api/earnings", tags=["Earnings"])
 app.include_router(insider.router, prefix="/api/insider", tags=["Insider Trading"])
+app.include_router(screener.router, prefix="/api/screener", tags=["Screener"])
 
 
 @app.get("/health")

atlas-terminal/server/models/schemas.py

@@ -75,6 +75,7 @@ class PortfolioPositionCreate(BaseModel):
     quantity: float
     avg_price: float
     currency: str = "USD"
+    exchange: str = ""
     source: str = "manual"
 
 
@@ -182,6 +183,7 @@ class PortfolioPosition(BaseModel):
     quantity: float
     avg_price: float
     currency: str = "USD"
+    exchange: str = ""
     source: str = "manual"
     current_price: Optional[float] = None
     market_value: Optional[float] = None

atlas-terminal/server/routers/fx.py

@@ -44,19 +44,44 @@ def _fetch_fx_rate(pair: str) -> float | None:
 @router.get(
     "/rates",
     response_model=FXRateResponse,
-    summary="Major FX rates",
+    summary="FX conversion matrix for major currencies",
 )
 async def fx_rates():
-    """Return current exchange rates for major currency pairs
-    (USD/KRW, USD/JPY, EUR/USD, GBP/USD, etc.).
-    """
+    """Return conversion matrix (USD/GBP/EUR/JPY/KRW)."""
     try:
-        rates: Dict[str, float] = {}
-        for pair in MAJOR_PAIRS:
-            rate = _fetch_fx_rate(pair)
-            if rate is not None:
-                rates[pair] = round(rate, 4)
-        return FXRateResponse(pair="MAJOR", rates=rates)
+        gbp_usd = _fetch_fx_rate("GBPUSD") or 1.27
+        eur_usd = _fetch_fx_rate("EURUSD") or 1.08
+        usd_jpy = _fetch_fx_rate("USDJPY") or 149.5
+        usd_krw = _fetch_fx_rate("USDKRW") or 1370.0
+
+        rates = {
+            "USD_USD": 1.0,
+            "USD_GBP": 1 / gbp_usd,
+            "USD_EUR": 1 / eur_usd,
+            "USD_JPY": usd_jpy,
+            "USD_KRW": usd_krw,
+            "GBP_USD": gbp_usd,
+            "GBP_GBP": 1.0,
+            "GBP_EUR": gbp_usd / eur_usd,
+            "GBP_JPY": gbp_usd * usd_jpy,
+            "GBP_KRW": gbp_usd * usd_krw,
+            "EUR_USD": eur_usd,
+            "EUR_GBP": eur_usd / gbp_usd,
+            "EUR_EUR": 1.0,
+            "EUR_JPY": eur_usd * usd_jpy,
+            "EUR_KRW": eur_usd * usd_krw,
+            "JPY_USD": 1 / usd_jpy,
+            "JPY_GBP": 1 / (gbp_usd * usd_jpy),
+            "JPY_EUR": 1 / (eur_usd * usd_jpy),
+            "JPY_JPY": 1.0,
+            "JPY_KRW": usd_krw / usd_jpy,
+            "KRW_USD": 1 / usd_krw,
+            "KRW_GBP": 1 / (gbp_usd * usd_krw),
+            "KRW_EUR": 1 / (eur_usd * usd_krw),
+            "KRW_JPY": usd_jpy / usd_krw,
+            "KRW_KRW": 1.0,
+        }
+        return FXRateResponse(pair="MATRIX", rates=rates)
     except Exception as exc:
         raise HTTPException(status_code=500, detail=f"FX rates failed: {exc}") from exc
 

atlas-terminal/server/routers/market_data.py

@@ -3,6 +3,7 @@
 from typing import Any, Dict, List
 
 from fastapi import APIRouter, Query
+from server.utils.ticker_utils import AssetType, detect_asset_type
 
 router = APIRouter()
 
@@ -51,12 +52,92 @@ async def market_indices():
         return []
 
 
+@router.get("/overview", summary="Global market overview")
+async def market_overview():
+    try:
+        from server.services.market_overview import get_market_overview
+
+        return await get_market_overview()
+    except Exception as e:
+        return {"error": str(e), "data": None}
+
+
+@router.get("/sectors", summary="Sector heatmap")
+async def sector_heatmap():
+    try:
+        from server.services.sector_heatmap import get_sector_heatmap
+
+        return await get_sector_heatmap()
+    except Exception as e:
+        return {"error": str(e), "data": None}
+
+
+@router.get("/overview/{ticker}", summary="Asset-type aware overview")
+async def market_overview_by_ticker(ticker: str):
+    """Detect asset type and return overview payload for that type."""
+    try:
+        asset_type = detect_asset_type(ticker)
+        if asset_type == AssetType.ETF:
+            from server.services.etf_analysis import get_etf_overview
+
+            return {"asset_type": AssetType.ETF.value, "data": await get_etf_overview(ticker)}
+        if asset_type == AssetType.COMMODITY_FUTURE:
+            from server.services.commodity_analysis import get_commodity_overview
+
+            return {"asset_type": AssetType.COMMODITY_FUTURE.value, "data": await get_commodity_overview(ticker)}
+        if asset_type == AssetType.CRYPTO:
+            return {"asset_type": AssetType.CRYPTO.value, "data": {"name": ticker.upper()}}
+        if asset_type == AssetType.INDEX:
+            return {"asset_type": AssetType.INDEX.value, "data": {"name": ticker.upper()}}
+        from server.services.etf_analysis import get_equity_overview
+
+        return {"asset_type": AssetType.EQUITY.value, "data": await get_equity_overview(ticker)}
+    except Exception as e:
+        return {"error": str(e), "asset_type": AssetType.EQUITY.value, "data": None}
+
+
+@router.get("/etf/{ticker}/holdings", summary="ETF top holdings")
+async def etf_holdings(ticker: str):
+    try:
+        from server.services.etf_analysis import get_etf_holdings
+
+        return {"ticker": ticker.upper(), "holdings": await get_etf_holdings(ticker)}
+    except Exception as e:
+        return {"error": str(e), "ticker": ticker.upper(), "holdings": []}
+
+
+@router.get("/commodity/{ticker}/seasonal", summary="Commodity monthly seasonal pattern")
+async def commodity_seasonal(ticker: str):
+    try:
+        from server.services.commodity_analysis import get_commodity_overview
+
+        data = await get_commodity_overview(ticker)
+        return {"ticker": ticker.upper(), "seasonal_pattern": data.get("seasonal_pattern", {})}
+    except Exception as e:
+        return {"error": str(e), "ticker": ticker.upper(), "seasonal_pattern": {}}
+
+
+@router.get("/commodity/{ticker}/correlations", summary="Commodity correlations")
+async def commodity_correlations(ticker: str):
+    try:
+        from server.services.commodity_analysis import compute_commodity_correlations
+
+        return {"ticker": ticker.upper(), "correlations": await compute_commodity_correlations(ticker)}
+    except Exception as e:
+        return {"error": str(e), "ticker": ticker.upper(), "correlations": {}}
+
+
 @router.get("/sector/{ticker}", summary="Sector and industry classification")
 async def sector_industry(ticker: str):
     try:
         import yfinance as yf
         t = yf.Ticker(ticker.upper())
         info = t.info or {}
+        city = (info.get("city") or "").strip()
+        state = (info.get("state") or "").strip()
+        country = (info.get("country") or "").strip()
+        hq_parts = [p for p in [city, state, country] if p]
+        hq = ", ".join(hq_parts) if hq_parts else "N/A"
         return {
             "sector": info.get("sector", "N/A"),
             "industry": info.get("industry", "N/A"),
@@ -67,6 +148,13 @@ async def sector_industry(ticker: str):
             "fifty_two_week_high": _safe_float(info.get("fiftyTwoWeekHigh")),
             "fifty_two_week_low": _safe_float(info.get("fiftyTwoWeekLow")),
             "current_price": _safe_float(info.get("currentPrice") or info.get("regularMarketPrice")),
+            "ceo": info.get("companyOfficers", [{}])[0].get("name") if isinstance(info.get("companyOfficers"), list) and info.get("companyOfficers") else None,
+            "employees": info.get("fullTimeEmployees"),
+            "founded": info.get("founded"),
+            "hq": hq,
+            "website": info.get("website"),
+            "ipo_date": info.get("ipoExpectedDate") or info.get("firstTradeDateEpochUtc"),
+            "description": info.get("longBusinessSummary"),
         }
     except Exception:
         return {"sector": "N/A", "industry": "N/A"}
@@ -134,7 +222,15 @@ async def industry_comps(tickers: str = Query(..., description="Comma-separated
 
 @router.get("/health/{ticker}", summary="DuPont, Altman Z-Score, Red Flags")
 async def financial_health(ticker: str):
-    fallback = {"ticker": ticker.upper(), "dupont": {}, "altman_z": None, "red_flags": []}
+    fallback = {
+        "ticker": ticker.upper(),
+        "dupont": {},
+        "altman_z": None,
+        "current_ratio": None,
+        "interest_coverage": None,
+        "debt_to_equity": None,
+        "red_flags": [],
+    }
     try:
         import yfinance as yf
         t = yf.Ticker(ticker.upper())
@@ -199,20 +295,61 @@ async def financial_health(ticker: str):
                 rev_ta = rev / ta
                 altman_z = round(1.2 * wc_ta + 1.4 * re_ta + 3.3 * ebit_ta + 0.6 * mc_tl + 1.0 * rev_ta, 2)
 
+        # Additional health metrics for overview cards
+        current_ratio = None
+        if bs is not None and not bs.empty:
+            col_bs = bs.columns[0]
+            ca = _safe_float(bs.loc["Current Assets"][col_bs]) if "Current Assets" in bs.index else 0
+            cl = _safe_float(bs.loc["Current Liabilities"][col_bs]) if "Current Liabilities" in bs.index else 0
+            current_ratio = (ca / cl) if cl else None
+        if current_ratio is None:
+            info_cr = _safe_float(info.get("currentRatio"), None)
+            current_ratio = info_cr if info_cr and info_cr > 0 else None
+
+        interest_coverage = None
+        if fin is not None and not fin.empty:
+            col_fin = fin.columns[0]
+            ebit = _safe_float(fin.loc["EBIT"][col_fin]) if "EBIT" in fin.index else _safe_float(fin.loc["Operating Income"][col_fin]) if "Operating Income" in fin.index else None
+            int_exp = _safe_float(fin.loc["Interest Expense"][col_fin]) if "Interest Expense" in fin.index else None
+            if ebit is not None and int_exp is not None and int_exp != 0:
+                interest_coverage = abs(ebit / int_exp)
+
+        debt_to_equity = None
+        if bs is not None and not bs.empty:
+            col_bs = bs.columns[0]
+            total_debt = _safe_float(bs.loc["Total Debt"][col_bs], None) if "Total Debt" in bs.index else None
+            if total_debt is None:
+                ltd = _safe_float(bs.loc["Long Term Debt"][col_bs], 0) if "Long Term Debt" in bs.index else 0
+                std = _safe_float(bs.loc["Current Debt"][col_bs], 0) if "Current Debt" in bs.index else 0
+                total_debt = ltd + std if (ltd or std) else None
+            equity = total_equity if total_equity else None
+            if total_debt is not None and equity:
+                debt_to_equity = total_debt / equity
+        if debt_to_equity is None:
+            de_info = _safe_float(info.get("debtToEquity"), None)
+            if de_info is not None:
+                debt_to_equity = de_info / 100 if de_info > 10 else de_info
+
         # Red Flags
         red_flags = []
-        cr = _safe_float(info.get("currentRatio"))
-        de = _safe_float(info.get("debtToEquity"))
-        if cr and cr < 1.0:
-            red_flags.append(f"Low current ratio: {cr:.2f}")
-        if de and de > 200:
-            red_flags.append(f"High debt-to-equity: {de:.1f}%")
+        if current_ratio is not None and current_ratio < 1.0:
+            red_flags.append(f"Low current ratio: {current_ratio:.2f}")
+        if debt_to_equity is not None and debt_to_equity > 2.0:
+            red_flags.append(f"High debt-to-equity: {debt_to_equity:.2f}")
         if npm and npm < 0:
             red_flags.append("Negative profit margin")
         if roe and roe < 0:
             red_flags.append("Negative ROE")
 
-        return {"ticker": ticker.upper(), "dupont": dupont, "altman_z": altman_z, "red_flags": red_flags}
+        return {
+            "ticker": ticker.upper(),
+            "dupont": dupont,
+            "altman_z": altman_z,
+            "current_ratio": round(current_ratio, 2) if current_ratio is not None else None,
+            "interest_coverage": round(interest_coverage, 2) if interest_coverage is not None else None,
+            "debt_to_equity": round(debt_to_equity, 2) if debt_to_equity is not None else None,
+            "red_flags": red_flags,
+        }
     except Exception as e:
         return fallback
 

atlas-terminal/server/routers/markets.py

@@ -0,0 +1,14 @@
+"""Markets router for index constituent heatmap."""
+
+from fastapi import APIRouter, Query
+
+router = APIRouter()
+
+
+@router.get("/heatmap/{index_name}", summary="Index constituent heatmap data")
+async def heatmap(index_name: str, top_n: int = Query(default=50, ge=1, le=200)):
+    from server.services.heatmap import get_heatmap_data
+
+    stocks = await get_heatmap_data(index_name, top_n)
+    return {"index": index_name, "count": len(stocks), "stocks": stocks}
+

atlas-terminal/server/routers/portfolio.py

@@ -1,11 +1,13 @@
 """Portfolio router -- position management, OCR screenshot upload, summary."""
 
 import json
+import os
 import uuid
 from pathlib import Path
 from typing import List
 
-from fastapi import APIRouter, HTTPException, UploadFile, File
+from fastapi import APIRouter, HTTPException, UploadFile, File, Header
+from pydantic import BaseModel, Field
 
 from server.models.schemas import (
     PortfolioPosition,
@@ -19,6 +21,18 @@ router = APIRouter()
 _PORTFOLIO_FILE = Path(__file__).resolve().parent.parent.parent / "data" / "portfolio.json"
 
 
+class PositionUpdateRequest(BaseModel):
+    quantity: float = Field(..., gt=0)
+    avg_price: float = Field(..., ge=0)
+    exchange: str = ""
+
+
+class OcrRecalculateRequest(BaseModel):
+    account_currency: str = "USD"
+    position: dict
+    selected_exchange: str = ""
+
+
 def _load_positions() -> List[dict]:
     """Load positions from the JSON store."""
     if not _PORTFOLIO_FILE.exists():
@@ -77,24 +91,36 @@ async def list_positions():
 @router.post(
     "/positions",
     response_model=PortfolioPosition,
-    summary="Add a portfolio position",
+    summary="Add or update a portfolio position",
 )
 async def add_position(pos: PortfolioPositionCreate):
-    """Add a new position to the portfolio."""
+    """Add a new position. If ticker exists, update quantity/avg/currency."""
     try:
         positions = _load_positions()
-        new_pos = {
-            "id": str(uuid.uuid4()),
-            "ticker": pos.ticker.upper(),
-            "company_name": pos.company_name,
-            "quantity": pos.quantity,
-            "avg_price": pos.avg_price,
-            "currency": pos.currency,
-            "source": pos.source,
-        }
-        positions.append(new_pos)
+        ticker = pos.ticker.upper()
+        existing = next((p for p in positions if str(p.get("ticker", "")).upper() == ticker), None)
+        if existing is not None:
+            existing["company_name"] = pos.company_name or existing.get("company_name", "")
+            existing["quantity"] = float(pos.quantity)
+            existing["avg_price"] = float(pos.avg_price)
+            existing["currency"] = pos.currency or existing.get("currency", "USD")
+            existing["exchange"] = pos.exchange or existing.get("exchange", "")
+            existing["source"] = pos.source or existing.get("source", "manual")
+            saved = existing
+        else:
+            saved = {
+                "id": str(uuid.uuid4()),
+                "ticker": ticker,
+                "company_name": pos.company_name,
+                "quantity": pos.quantity,
+                "avg_price": pos.avg_price,
+                "currency": pos.currency,
+                "exchange": pos.exchange,
+                "source": pos.source,
+            }
+            positions.append(saved)
         _save_positions(positions)
-        return PortfolioPosition(**new_pos)
+        return PortfolioPosition(**saved)
     except Exception as exc:
         raise HTTPException(status_code=500, detail=f"Failed to add position: {exc}") from exc
 
@@ -121,6 +147,79 @@ async def remove_position(position_id: str):
         raise HTTPException(status_code=500, detail=f"Failed to remove position: {exc}") from exc
 
 
+@router.put(
+    "/positions/{position_id}",
+    response_model=PortfolioPosition,
+    summary="Update quantity/avg price for a position",
+)
+async def update_position(position_id: str, body: PositionUpdateRequest):
+    """Update an existing position by unique ID."""
+    try:
+        positions = _load_positions()
+        updated = None
+        for p in positions:
+            if p.get("id") == position_id:
+                p["quantity"] = float(body.quantity)
+                p["avg_price"] = float(body.avg_price)
+                if body.exchange:
+                    p["exchange"] = body.exchange
+                updated = p
+                break
+        if updated is None:
+            raise HTTPException(status_code=404, detail=f"Position {position_id} not found.")
+        _save_positions(positions)
+        return PortfolioPosition(**updated)
+    except HTTPException:
+        raise
+    except Exception as exc:
+        raise HTTPException(status_code=500, detail=f"Failed to update position: {exc}") from exc
+
+
+@router.post(
+    "/ocr",
+    summary="OCR screenshot with smart reverse-engineering",
+)
+async def ocr_screenshot(
+    file: UploadFile = File(...),
+    x_gemini_api_key: str | None = Header(default=None),
+):
+    """Screenshot -> OCR extraction -> market-validated reverse-engineered positions."""
+    try:
+        from server.services.screenshot_ocr import process_portfolio_screenshot
+
+        image_bytes = await file.read()
+        api_key = (x_gemini_api_key or "").strip() or os.getenv("GOOGLE_API_KEY", "").strip()
+        result = await process_portfolio_screenshot(api_key, image_bytes)
+        if result.get("error"):
+            return {"error": result.get("error"), "positions": [], "count": 0, "warnings": []}
+        result["count"] = len(result.get("positions") or [])
+        return result
+    except Exception as exc:
+        raise HTTPException(status_code=500, detail=f"OCR processing failed: {exc}") from exc
+
+
+@router.get("/exchange-options/{ticker}", summary="Available exchange options for a ticker")
+async def exchange_options(ticker: str):
+    from server.services.exchange_resolver import get_exchange_options
+
+    return {"ticker": ticker.upper(), "options": get_exchange_options(ticker)}
+
+
+@router.post("/ocr/recalculate", summary="Recalculate one OCR row with selected exchange")
+async def ocr_recalculate(body: OcrRecalculateRequest):
+    from server.services.screenshot_ocr import reverse_engineer_positions
+
+    ticker = str((body.position or {}).get("ticker", "")).upper()
+    if not ticker:
+        raise HTTPException(status_code=400, detail="position.ticker is required")
+    payload = {"account_currency": body.account_currency, "positions": [body.position]}
+    overrides = {ticker: body.selected_exchange} if body.selected_exchange else {}
+    recalculated = reverse_engineer_positions(payload, overrides)
+    if not recalculated:
+        raise HTTPException(status_code=400, detail="Failed to recalculate position")
+    return {"position": recalculated[0]}
+
+
 @router.post(
     "/screenshot",
     summary="Upload screenshot for OCR analysis",
@@ -209,6 +308,7 @@ async def portfolio_summary():
                 quantity=quantity,
                 avg_price=avg_price,
                 currency=p.get("currency", "USD"),
+                exchange=p.get("exchange", ""),
                 source=p.get("source", "manual"),
                 current_price=current_price,
                 market_value=market_value,

atlas-terminal/server/routers/screener.py

@@ -0,0 +1,34 @@
+"""Screener and backtesting router."""
+
+from __future__ import annotations
+
+from fastapi import APIRouter
+
+router = APIRouter()
+
+
+@router.post("/search")
+async def search_stocks(filters: dict):
+    """Run stock screener with simple filters."""
+    try:
+        from server.services.screener import run_screener
+
+        return await run_screener(filters)
+    except Exception as e:
+        return {"error": str(e), "data": []}
+
+
+@router.post("/backtest")
+async def backtest(body: dict):
+    """Run strategy backtest for one ticker."""
+    try:
+        from server.services.backtester import run_backtest
+
+        return await run_backtest(
+            ticker=body.get("ticker", ""),
+            strategy=body.get("strategy", "buy_and_hold"),
+            start_date=body.get("start_date", "2024-01-01"),
+            end_date=body.get("end_date", "2026-01-01"),
+        )
+    except Exception as e:
+        return {"error": str(e)}

atlas-terminal/server/services/backtester.py

@@ -0,0 +1,47 @@
+"""Backtesting service for simple strategies."""
+
+from __future__ import annotations
+
+
+async def run_backtest(
+    ticker: str,
+    strategy: str,
+    start_date: str,
+    end_date: str,
+    initial_capital: float = 10000.0,
+) -> dict:
+    """Run a basic backtest for selected strategy."""
+    import yfinance as yf
+    import ta
+
+    df = yf.Ticker(ticker.upper()).history(start=start_date, end=end_date)
+    if df is None or df.empty:
+        return {"error": "No price data"}
+
+    if strategy == "sma_crossover":
+        df["sma50"] = ta.trend.sma_indicator(df["Close"], 50)
+        df["sma200"] = ta.trend.sma_indicator(df["Close"], 200)
+        df["signal"] = (df["sma50"] > df["sma200"]).astype(int)
+    elif strategy == "rsi_oversold":
+        df["rsi"] = ta.momentum.rsi(df["Close"], 14)
+        df["signal"] = 0
+        df.loc[df["rsi"] < 30, "signal"] = 1
+        df.loc[df["rsi"] > 70, "signal"] = 0
+    else:
+        df["signal"] = 1
+
+    df["returns"] = df["Close"].pct_change().fillna(0)
+    df["strategy_returns"] = (df["returns"] * df["signal"].shift(1)).fillna(0)
+    cumulative = (1 + df["strategy_returns"]).cumprod()
+    benchmark = (1 + df["returns"]).cumprod()
+
+    return {
+        "total_return_pct": round((float(cumulative.iloc[-1]) - 1) * 100, 2),
+        "benchmark_return_pct": round((float(benchmark.iloc[-1]) - 1) * 100, 2),
+        "alpha": round((float(cumulative.iloc[-1]) - float(benchmark.iloc[-1])) * 100, 2),
+        "max_drawdown_pct": round(float(((cumulative / cumulative.cummax()) - 1).min()) * 100, 2),
+        "sharpe_ratio": round(float(df["strategy_returns"].mean() / (df["strategy_returns"].std() + 1e-10) * (252 ** 0.5)), 2),
+        "equity_curve": [float(x) for x in cumulative.tolist()],
+        "benchmark_curve": [float(x) for x in benchmark.tolist()],
+        "dates": df.index.strftime("%Y-%m-%d").tolist(),
+    }

atlas-terminal/server/services/commodity_analysis.py

@@ -0,0 +1,99 @@
+"""Commodity future analysis helpers."""
+
+from __future__ import annotations
+
+from typing import Any
+
+from server.utils.ticker_utils import COMMODITY_FUTURES
+
+COMMODITY_RELATED: dict[str, list[str]] = {
+    "GC=F": ["GLD", "SI=F", "DX-Y.NYB", "^TNX"],
+    "CL=F": ["USO", "BZ=F", "XLE", "^GSPC"],
+    "SI=F": ["SLV", "GC=F", "HG=F", "^GSPC"],
+    "NG=F": ["UNG", "CL=F", "XLE"],
+}
+
+
+def _get_related_assets(ticker: str) -> list[str]:
+    return COMMODITY_RELATED.get(ticker.upper(), [])
+
+
+async def compute_commodity_correlations(ticker: str, period: str = "1y") -> dict:
+    import yfinance as yf
+
+    t = ticker.upper()
+    related = _get_related_assets(t)
+    if not related:
+        return {}
+    all_tickers = [t] + related
+    data = yf.download(all_tickers, period=period, auto_adjust=True, progress=False)
+    if data is None or data.empty:
+        return {}
+    close = data["Close"] if "Close" in data else data
+    returns = close.pct_change().dropna()
+    if returns is None or returns.empty or t not in returns.columns:
+        return {}
+    corr = returns.corr()
+    result = {}
+    for r in related:
+        if r in corr.columns:
+            result[r] = round(float(corr.loc[t, r]), 2)
+    return result
+
+
+async def get_commodity_overview(ticker: str) -> dict:
+    import yfinance as yf
+
+    t = ticker.upper()
+    y = yf.Ticker(t)
+    info = y.info or {}
+    hist_1y = y.history(period="1y", auto_adjust=True)
+    hist_10y = y.history(period="10y", auto_adjust=True)
+
+    seasonal = {}
+    if hist_10y is not None and not hist_10y.empty:
+        monthly = hist_10y["Close"].resample("ME").last().pct_change().dropna()
+        for month in range(1, 13):
+            m = monthly[monthly.index.month == month]
+            seasonal[month] = round(float(m.mean()) * 100, 2) if len(m) > 0 else 0
+
+    related = _get_related_assets(t)
+    related_cards = []
+    if related:
+        data = yf.download(related, period="5d", auto_adjust=True, progress=False)
+        close = data["Close"] if hasattr(data, "columns") and "Close" in data.columns else data
+        if close is not None:
+            try:
+                if hasattr(close, "columns"):
+                    for sym in related:
+                        if sym not in close.columns:
+                            continue
+                        s = close[sym].dropna()
+                        if len(s) < 1:
+                            continue
+                        cur = float(s.iloc[-1])
+                        prev = float(s.iloc[-2]) if len(s) > 1 else cur
+                        pct = ((cur - prev) / prev * 100) if prev else 0
+                        related_cards.append({"symbol": sym, "price": round(cur, 2), "change_pct": round(pct, 2)})
+                else:
+                    s = close.dropna()
+                    if len(s) >= 1:
+                        cur = float(s.iloc[-1])
+                        prev = float(s.iloc[-2]) if len(s) > 1 else cur
+                        pct = ((cur - prev) / prev * 100) if prev else 0
+                        related_cards.append({"symbol": related[0], "price": round(cur, 2), "change_pct": round(pct, 2)})
+            except Exception:
+                pass
+
+    return {
+        "name": COMMODITY_FUTURES.get(t, info.get("shortName", t)),
+        "price": info.get("regularMarketPrice") or info.get("currentPrice"),
+        "open_interest": info.get("openInterest"),
+        "volume": info.get("volume"),
+        "high_52w": info.get("fiftyTwoWeekHigh"),
+        "low_52w": info.get("fiftyTwoWeekLow"),
+        "seasonal_pattern": seasonal,
+        "related_assets": related_cards,
+        "correlation_matrix": await compute_commodity_correlations(t),
+        "asset_class": "commodity_future",
+    }

atlas-terminal/server/services/copilot_context.py

@@ -0,0 +1,24 @@
+"""Build compact copilot context with asset-type aware fields."""
+
+from __future__ import annotations
+
+
+def build_copilot_context(asset_type: str, data: dict) -> str:
+    parts: list[str] = []
+    if asset_type == "etf":
+        parts.append(f"[Asset Type] ETF — {data.get('category')}")
+        parts.append(f"[ETF] AUM: {data.get('aum')}, Expense: {data.get('expense_ratio')}")
+        r = data.get("returns") or {}
+        parts.append(f"[Performance] YTD: {r.get('ytd')}%, 1Y: {r.get('1y')}%")
+    elif asset_type == "commodity_future":
+        parts.append(f"[Asset Type] Commodity Future — {data.get('name')}")
+        parts.append(f"[Commodity] Open Interest: {data.get('open_interest')}")
+        seasonal = data.get("seasonal_pattern") or {}
+        if seasonal:
+            best_month = max(seasonal, key=lambda k: seasonal[k])
+            worst_month = min(seasonal, key=lambda k: seasonal[k])
+            parts.append(f"[Seasonal] Best month: {best_month}, Worst: {worst_month}")
+    else:
+        parts.append("[Asset Type] Equity")
+        parts.append(f"[Sector] {data.get('sector')}")
+    return "\n".join(parts)

atlas-terminal/server/services/etf_analysis.py

@@ -0,0 +1,162 @@
+"""ETF and equity-like overview helpers."""
+
+from __future__ import annotations
+
+import math
+from typing import Any
+
+
+def _safe_num(v: Any) -> float | None:
+    try:
+        f = float(v)
+        if math.isnan(f) or math.isinf(f):
+            return None
+        return f
+    except Exception:
+        return None
+
+
+def _compute_sharpe(returns) -> float | None:
+    if returns is None or len(returns) < 2:
+        return None
+    std = returns.std()
+    if not std:
+        return None
+    return round(float((returns.mean() / std) * (252**0.5)), 2)
+
+
+def _compute_sortino(returns) -> float | None:
+    if returns is None or len(returns) < 2:
+        return None
+    downside = returns[returns < 0]
+    if downside is None or len(downside) < 2:
+        return None
+    std = downside.std()
+    if not std:
+        return None
+    return round(float((returns.mean() / std) * (252**0.5)), 2)
+
+
+def _max_drawdown(returns) -> float | None:
+    if returns is None or len(returns) < 2:
+        return None
+    curve = (1 + returns).cumprod()
+    dd = (curve / curve.cummax()) - 1
+    return round(float(dd.min()) * 100, 2)
+
+
+async def get_benchmark_comparison(ticker: str, benchmark: str = "SPY", period: str = "1y") -> dict:
+    import yfinance as yf
+
+    data = yf.download([ticker.upper(), benchmark.upper()], period=period, auto_adjust=True, progress=False)
+    if data is None or data.empty:
+        return {}
+    close = data["Close"] if "Close" in data else data
+    if close is None or close.empty:
+        return {}
+    t_col = ticker.upper()
+    b_col = benchmark.upper()
+    if t_col not in close.columns or b_col not in close.columns:
+        return {}
+    close = close[[t_col, b_col]].dropna()
+    if close.empty:
+        return {}
+    normalized = close / close.iloc[0] * 100
+    return {
+        "dates": normalized.index.strftime("%Y-%m-%d").tolist(),
+        "ticker_values": [float(x) for x in normalized[t_col].tolist()],
+        "benchmark_values": [float(x) for x in normalized[b_col].tolist()],
+        "benchmark": benchmark.upper(),
+    }
+
+
+async def get_etf_holdings(ticker: str, top_n: int = 10) -> list[dict]:
+    import yfinance as yf
+
+    t = yf.Ticker(ticker.upper())
+    out = []
+    try:
+        holdings = getattr(t, "fund_top_holdings", None)
+        if holdings is not None and not holdings.empty:
+            for _, row in holdings.head(top_n).iterrows():
+                out.append(
+                    {
+                        "symbol": row.get("symbol") or row.get("holdingName") or "",
+                        "name": row.get("holdingName") or row.get("symbol") or "",
+                        "weight_pct": _safe_num(row.get("holdingPercent")),
+                    }
+                )
+    except Exception:
+        pass
+    return out
+
+
+async def get_etf_overview(ticker: str) -> dict:
+    import yfinance as yf
+
+    t = yf.Ticker(ticker.upper())
+    info = t.info or {}
+    hist = t.history(period="5y", auto_adjust=True)
+
+    def period_return(days: int) -> float | None:
+        if hist is None or hist.empty or len(hist) <= days:
+            return None
+        cur = _safe_num(hist["Close"].iloc[-1])
+        prev = _safe_num(hist["Close"].iloc[-days])
+        if cur is None or prev is None or prev == 0:
+            return None
+        return round((cur / prev - 1) * 100, 2)
+
+    ytd_days = 0
+    if hist is not None and not hist.empty:
+        ytd_days = int((hist.index.year == hist.index[-1].year).sum())
+    returns = hist["Close"].pct_change().dropna() if hist is not None and not hist.empty else None
+
+    return {
+        "name": info.get("longName") or info.get("shortName", ticker.upper()),
+        "category": info.get("category") or info.get("fundFamily") or "N/A",
+        "aum": _safe_num(info.get("totalAssets")),
+        "expense_ratio": _safe_num(info.get("annualReportExpenseRatio")),
+        "nav": _safe_num(info.get("navPrice")),
+        "inception": info.get("fundInceptionDate"),
+        "price": _safe_num(info.get("currentPrice") or info.get("regularMarketPrice")),
+        "high_52w": _safe_num(info.get("fiftyTwoWeekHigh")),
+        "low_52w": _safe_num(info.get("fiftyTwoWeekLow")),
+        "returns": {
+            "1m": period_return(21),
+            "3m": period_return(63),
+            "6m": period_return(126),
+            "ytd": period_return(ytd_days) if ytd_days else None,
+            "1y": period_return(252),
+            "3y": period_return(756),
+            "5y": period_return(1260),
+        },
+        "holdings": await get_etf_holdings(ticker, top_n=10),
+        "risk": {
+            "sharpe": _compute_sharpe(returns),
+            "sortino": _compute_sortino(returns),
+            "max_drawdown": _max_drawdown(returns),
+            "volatility": round(float(returns.std()) * (252**0.5) * 100, 2) if returns is not None and len(returns) > 1 else None,
+        },
+        "benchmark_comparison": await get_benchmark_comparison(ticker, "SPY", "1y"),
+    }
+
+
+async def get_equity_overview(ticker: str) -> dict:
+    import yfinance as yf
+
+    t = yf.Ticker(ticker.upper())
+    info = t.info or {}
+    return {
+        "name": info.get("longName") or info.get("shortName", ticker.upper()),
+        "sector": info.get("sector"),
+        "industry": info.get("industry"),
+        "market_cap": _safe_num(info.get("marketCap")),
+        "pe_ratio": _safe_num(info.get("trailingPE")) or _safe_num(info.get("forwardPE")),
+        "dividend_yield": _safe_num(info.get("dividendYield")),
+        "beta": _safe_num(info.get("beta")),
+        "high_52w": _safe_num(info.get("fiftyTwoWeekHigh")),
+        "low_52w": _safe_num(info.get("fiftyTwoWeekLow")),
+        "price": _safe_num(info.get("currentPrice") or info.get("regularMarketPrice")),
+        "description": info.get("longBusinessSummary"),
+    }

atlas-terminal/server/services/exchange_resolver.py

@@ -0,0 +1,51 @@
+"""Resolve multi-exchange tickers for OCR/import workflows."""
+
+from __future__ import annotations
+
+MULTI_EXCHANGE_TICKERS = {
+    "SMSN": [
+        {"exchange": "LSE (GDR)", "yf_ticker": "SMSN.L", "currency": "USD", "default": True},
+        {"exchange": "KRX (Korea)", "yf_ticker": "005930.KS", "currency": "KRW"},
+        {"exchange": "OTC (US)", "yf_ticker": "SSNLF", "currency": "USD"},
+    ],
+    "NOV": [
+        {"exchange": "NYSE", "yf_ticker": "NVO", "currency": "USD", "default": True},
+        {"exchange": "Copenhagen", "yf_ticker": "NOVO-B.CO", "currency": "DKK"},
+    ],
+    "NVO": [
+        {"exchange": "NYSE", "yf_ticker": "NVO", "currency": "USD", "default": True},
+        {"exchange": "Copenhagen", "yf_ticker": "NOVO-B.CO", "currency": "DKK"},
+    ],
+}
+
+T212_TICKER_MAP = {
+    "SMSN": "SMSN.L",
+    "SMSN.L": "SMSN.L",
+    "NOV": "NVO",
+    "NVDA": "NVDA",
+    "TSLA": "TSLA",
+    "NVO": "NVO",
+    "PLTR": "PLTR",
+    "IONQ": "IONQ",
+    "IREN": "IREN",
+}
+
+
+def get_exchange_options(ticker: str) -> list[dict]:
+    return MULTI_EXCHANGE_TICKERS.get((ticker or "").upper(), [])
+
+
+def resolve_ticker_with_exchange(ticker: str, selected_exchange: str | None = None) -> str:
+    t = (ticker or "").upper().strip()
+    options = get_exchange_options(t)
+    if not options:
+        return T212_TICKER_MAP.get(t, t)
+    if selected_exchange:
+        for opt in options:
+            if opt.get("exchange") == selected_exchange:
+                return opt.get("yf_ticker", t)
+    for opt in options:
+        if opt.get("default"):
+            return opt.get("yf_ticker", t)
+    return options[0].get("yf_ticker", t)
+

atlas-terminal/server/services/heatmap.py

@@ -0,0 +1,71 @@
+"""Heatmap data service for index constituents."""
+
+from __future__ import annotations
+
+from typing import Any
+
+import pandas as pd
+import yfinance as yf
+
+
+async def get_index_constituents(index_name: str) -> list[str]:
+    name = (index_name or "").lower().strip()
+    if name == "sp500":
+        try:
+            table = pd.read_html("https://en.wikipedia.org/wiki/List_of_S%26P_500_companies")[0]
+            return table["Symbol"].astype(str).str.replace(".", "-", regex=False).tolist()
+        except Exception:
+            return ["AAPL", "MSFT", "NVDA", "AMZN", "GOOGL", "META", "BRK-B", "TSLA", "UNH", "XOM"]
+    if name == "nasdaq100":
+        try:
+            table = pd.read_html("https://en.wikipedia.org/wiki/Nasdaq-100")[4]
+            return table["Ticker"].astype(str).tolist()
+        except Exception:
+            return ["AAPL", "MSFT", "NVDA", "AMZN", "GOOGL", "META", "TSLA", "AVGO", "COST", "NFLX"]
+    if name == "kospi":
+        return [
+            "005930.KS", "000660.KS", "035420.KS", "051910.KS", "006400.KS",
+            "035720.KS", "068270.KS", "028260.KS", "105560.KS", "012330.KS",
+            "055550.KS", "034730.KS", "003550.KS", "015760.KS", "066570.KS",
+            "032830.KS", "096770.KS", "009150.KS", "003670.KS", "018260.KS",
+        ]
+    if name == "ftse100":
+        return ["SHEL.L", "AZN.L", "HSBA.L", "ULVR.L", "BP.L", "GSK.L", "RIO.L", "LSEG.L"]
+    return []
+
+
+def _calc_change_pct(ticker: str) -> float:
+    try:
+        hist = yf.Ticker(ticker).history(period="2d")
+        if hist is not None and len(hist) >= 2:
+            prev = float(hist["Close"].iloc[-2])
+            cur = float(hist["Close"].iloc[-1])
+            if prev != 0:
+                return round((cur - prev) / prev * 100, 2)
+    except Exception:
+        pass
+    return 0.0
+
+
+async def get_heatmap_data(index_name: str, top_n: int = 50) -> list[dict[str, Any]]:
+    tickers = (await get_index_constituents(index_name))[: max(top_n, 1)]
+    out: list[dict[str, Any]] = []
+    for ticker in tickers:
+        try:
+            info = yf.Ticker(ticker).info or {}
+            mcap = info.get("marketCap")
+            if not mcap or float(mcap) <= 0:
+                continue
+            out.append(
+                {
+                    "ticker": ticker.replace(".KS", "").replace(".L", ""),
+                    "name": info.get("shortName") or info.get("longName") or ticker,
+                    "sector": info.get("sector") or "Other",
+                    "market_cap": float(mcap),
+                    "change_pct": _calc_change_pct(ticker),
+                }
+            )
+        except Exception:
+            continue
+    return sorted(out, key=lambda x: x["market_cap"], reverse=True)
+

atlas-terminal/server/services/market_overview.py

@@ -0,0 +1,57 @@
+"""Market overview service: indices, commodities, bonds, crypto, FX."""
+
+from __future__ import annotations
+
+
+INDICES = {
+    "S&P 500": "^GSPC",
+    "NASDAQ": "^IXIC",
+    "Dow Jones": "^DJI",
+    "KOSPI": "^KS11",
+    "Nikkei 225": "^N225",
+    "FTSE 100": "^FTSE",
+    "DAX": "^GDAXI",
+    "Hang Seng": "^HSI",
+}
+COMMODITIES = {"Gold": "GC=F", "Oil (WTI)": "CL=F", "Silver": "SI=F", "Nat Gas": "NG=F"}
+BONDS = {"US 10Y": "^TNX", "US 2Y": "^IRX"}
+CRYPTO = {"Bitcoin": "BTC-USD", "Ethereum": "ETH-USD"}
+FX = {"EUR/USD": "EURUSD=X", "GBP/USD": "GBPUSD=X", "USD/JPY": "USDJPY=X", "USD/KRW": "USDKRW=X"}
+POPULAR_ETFS = {"SPY": "SPY", "QQQ": "QQQ", "GLD": "GLD", "TLT": "TLT", "EEM": "EEM"}
+
+
+async def get_market_overview() -> dict:
+    """Fetch concise multi-asset market overview from yfinance."""
+    import yfinance as yf
+
+    results = {}
+    for category, tickers in [
+        ("indices", INDICES),
+        ("commodities", COMMODITIES),
+        ("bonds", BONDS),
+        ("crypto", CRYPTO),
+        ("fx", FX),
+        ("popular_etfs", POPULAR_ETFS),
+    ]:
+        cat_data = []
+        for name, symbol in tickers.items():
+            try:
+                t = yf.Ticker(symbol)
+                hist = t.history(period="5d")
+                if hist is None or hist.empty:
+                    continue
+                current = float(hist["Close"].iloc[-1])
+                prev = float(hist["Close"].iloc[-2]) if len(hist) > 1 else current
+                change_pct = ((current - prev) / prev * 100) if prev else 0.0
+                cat_data.append(
+                    {
+                        "name": name,
+                        "symbol": symbol,
+                        "price": round(current, 2),
+                        "change_pct": round(change_pct, 2),
+                    }
+                )
+            except Exception:
+                continue
+        results[category] = cat_data
+    return results

atlas-terminal/server/services/screener.py

@@ -0,0 +1,47 @@
+"""Stock screener service."""
+
+from __future__ import annotations
+
+
+async def run_screener(filters: dict, universe: str = "sp500") -> list[dict]:
+    """Run simple screening against S&P 500 universe."""
+    import pandas as pd
+    import yfinance as yf
+
+    try:
+        table = pd.read_html("https://en.wikipedia.org/wiki/List_of_S%26P_500_companies")[0]
+        tickers = table["Symbol"].astype(str).tolist()
+    except Exception:
+        tickers = []
+
+    results = []
+    for ticker in tickers:
+        try:
+            info = yf.Ticker(ticker).info or {}
+            pe = info.get("forwardPE")
+            mcap = info.get("marketCap")
+            sector = info.get("sector")
+            div = info.get("dividendYield")
+            if filters.get("pe_max") and ((pe or 9999) > filters["pe_max"]):
+                continue
+            if filters.get("sector") and sector != filters["sector"]:
+                continue
+            if filters.get("market_cap_min") and ((mcap or 0) < filters["market_cap_min"]):
+                continue
+            if filters.get("div_yield_min") and (((div or 0) * 100) < filters["div_yield_min"]):
+                continue
+            results.append(
+                {
+                    "ticker": ticker,
+                    "name": info.get("shortName", ""),
+                    "sector": sector or "",
+                    "market_cap": mcap,
+                    "pe": pe,
+                    "div_yield": (div * 100) if div is not None else None,
+                    "price": info.get("currentPrice") or info.get("regularMarketPrice"),
+                    "change_pct": info.get("regularMarketChangePercent"),
+                }
+            )
+        except Exception:
+            continue
+    return results

atlas-terminal/server/services/screenshot_ocr.py

@@ -1,145 +1,291 @@
-"""Portfolio screenshot OCR using Gemini Vision.
+"""Portfolio OCR with smart reverse-engineering against live market prices."""
 
-Analyses screenshots from Trading 212 or Interactive Brokers (IBKR) portfolio
-views and extracts structured position data (ticker, quantity, market value,
-gain/loss) via the Gemini multimodal API.
-"""
+from __future__ import annotations
 
+import asyncio
 import json
 import re
-from typing import Any, Dict, List, Optional
+from typing import Any, Optional
 
+import yfinance as yf
+from server.services.exchange_resolver import resolve_ticker_with_exchange
 
-def _get_vision_model(api_key: str) -> Any:
-    """Configure Gemini and return a multimodal model."""
-    import google.generativeai as genai
-    genai.configure(api_key=api_key)
-    return genai.GenerativeModel("gemini-2.0-flash")
+SCREENSHOT_OCR_PROMPT = """
+Analyze this screenshot of a stock trading app portfolio (Trading 212, IBKR, Webull, etc).
 
+CRITICAL INSTRUCTIONS:
+- Extract ALL positions visible in the image. There are likely 5-15 positions.
+- Do NOT stop after the first position. Keep going until every position is captured.
+- You MUST extract ALL positions visible in the screenshot.
+- If you see 8 positions in the image, you MUST return exactly 8 objects in the positions array.
+- The account currency shown at the top (£, $, €) may differ from individual stock currencies.
 
-def _build_prompt() -> str:
-    """Return the extraction prompt for portfolio screenshots."""
-    return """You are a financial data extraction assistant.
+For EACH position, extract:
+1. ticker: Stock ticker symbol exactly as shown (e.g., "IREN", "NVDA", "SMSN")
+2. name: Company name
+3. displayed_value: The monetary value shown (number only, no currency symbol)
+4. displayed_currency: Currency symbol next to the value (£, $, €, ₩, ¥)
+5. weight_pct: Portfolio weight % if shown (e.g., 28.66)
+6. gain_loss_pct: P&L percentage if shown (e.g., -16.27 or +8.80)
+7. gain_loss_amount: P&L monetary amount (number only)
+8. shares: Number of shares if visible (preserve ALL decimals)
+9. avg_price: Average purchase price if visible (number only)
+10. avg_price_currency: Currency of avg price
 
-Analyse this portfolio screenshot from a brokerage app (Trading 212,
-Interactive Brokers, or similar).
+ALSO extract portfolio summary from the top of the screen:
+- total_value: Total portfolio value (number only)
+- total_currency: Currency symbol (£, $, €)
+- cost_basis: Cost basis if shown (number only)
+- unrealised_pnl: Unrealised P&L (number only)
+- unrealised_pnl_pct: P&L percentage
 
-Extract every visible position and return ONLY a valid JSON object with
-this structure:
-
-{
-  "broker": "Trading 212" | "IBKR" | "Unknown",
-  "currency": "USD" | "GBP" | "EUR" | ...,
-  "positions": [
-    {
-      "ticker": "AAPL",
-      "name": "Apple Inc.",
-      "quantity": 10.5,
-      "avg_price": 150.00,
-      "current_price": 175.00,
-      "market_value": 1837.50,
-      "gain_loss": 262.50,
-      "gain_loss_pct": 16.67
-    }
-  ],
-  "total_value": 50000.00,
-  "total_gain_loss": 5000.00
-}
-
-Rules:
-- Use null for any field you cannot read.
-- quantity may be fractional (e.g. 0.125 shares).
-- Monetary values should be plain numbers, no currency symbols.
-- If the screenshot is not a portfolio view, return {"error": "Not a portfolio screenshot"}.
-- Output ONLY the JSON object, nothing else.
+Return ONLY valid JSON, no other text.
 """
 
+def _norm_currency(sym: str | None, default: str = "USD") -> str:
+    s = (sym or "").strip().upper()
+    mapping = {"£": "GBP", "$": "USD", "€": "EUR", "₩": "KRW", "¥": "JPY"}
+    return mapping.get(s, s or default)
 
-def analyze_portfolio_screenshot(
-    api_key: str,
-    image_bytes: bytes,
-) -> Dict[str, Any]:
-    """Extract portfolio positions from a brokerage screenshot.
 
-    Uses Gemini Vision (multimodal) to read the image and return
-    structured position data.
+def _resolve_ticker(t212_ticker: str) -> str:
+    return resolve_ticker_with_exchange(t212_ticker, None)
 
-    Parameters
-    ----------
-    api_key:
-        Google Gemini API key.
-    image_bytes:
-        Raw bytes of the screenshot image (PNG, JPEG, etc.).
 
-    Returns
-    -------
-    dict
-        Parsed portfolio data with ``broker``, ``currency``,
-        ``positions`` (list), ``total_value``, and ``total_gain_loss``.
-        On error, returns ``{"error": "<description>"}``.
-    """
+def _get_realtime_price(ticker: str) -> Optional[dict]:
+    try:
+        yf_ticker = _resolve_ticker(ticker)
+        t = yf.Ticker(yf_ticker)
+        info = t.info or {}
+        price = info.get("currentPrice") or info.get("regularMarketPrice") or info.get("previousClose")
+        currency = (info.get("currency") or "USD").upper()
+        if price is None:
+            fast = getattr(t, "fast_info", None)
+            if fast:
+                price = getattr(fast, "last_price", None)
+        if price is None:
+            hist = t.history(period="1d")
+            if hist is not None and not hist.empty:
+                price = float(hist["Close"].iloc[-1])
+        if price is None:
+            return None
+        return {"price": float(price), "currency": currency, "yf_ticker": yf_ticker}
+    except Exception:
+        return None
+
+
+def _get_fx_rate(from_currency: str, to_currency: str) -> float:
+    f = _norm_currency(from_currency)
+    t = _norm_currency(to_currency)
+    if f == t:
+        return 1.0
+    try:
+        pair = f"{f}{t}=X"
+        hist = yf.Ticker(pair).history(period="1d")
+        if hist is not None and not hist.empty:
+            return float(hist["Close"].iloc[-1])
+        rev = f"{t}{f}=X"
+        hist2 = yf.Ticker(rev).history(period="1d")
+        if hist2 is not None and not hist2.empty:
+            return 1.0 / float(hist2["Close"].iloc[-1])
+    except Exception:
+        pass
+    fallback = {
+        ("GBP", "USD"): 1.27, ("USD", "GBP"): 0.79,
+        ("EUR", "USD"): 1.08, ("USD", "EUR"): 0.93,
+        ("USD", "KRW"): 1370.0, ("KRW", "USD"): 0.00073,
+        ("USD", "JPY"): 149.5, ("JPY", "USD"): 0.0067,
+    }
+    return fallback.get((f, t), 1.0)
+
+
+def reverse_engineer_positions(ocr_result: dict, exchange_overrides: dict[str, str] | None = None) -> list[dict]:
+    account_currency = _norm_currency(ocr_result.get("account_currency"), "USD")
+    out: list[dict] = []
+    for pos in ocr_result.get("positions", []) or []:
+        ticker = (pos.get("ticker") or "").upper().strip()
+        if not ticker:
+            continue
+        selected_exchange = (exchange_overrides or {}).get(ticker)
+        yf_ticker = resolve_ticker_with_exchange(ticker, selected_exchange)
+        mkt = _get_realtime_price(yf_ticker)
+        if not mkt:
+            out.append({
+                "ticker": ticker,
+                "name": pos.get("name") or ticker,
+                "quantity": pos.get("shares"),
+                "avg_price": pos.get("avg_price"),
+                "avg_price_currency": _norm_currency(pos.get("avg_price_currency"), "USD"),
+                "current_price": None,
+                "stock_currency": "USD",
+                "account_currency": account_currency,
+                "current_value_account": pos.get("displayed_value"),
+                "pnl_pct": pos.get("gain_loss_pct"),
+                "confidence": "low",
+                "method": "ocr_only",
+                "yf_ticker": yf_ticker,
+            })
+            continue
+
+        stock_price = float(mkt["price"])
+        stock_currency = _norm_currency(mkt["currency"], "USD")
+        shares = pos.get("shares")
+        confidence = "high"
+        method = "ocr_shares"
+
+        if not shares:
+            displayed_value = pos.get("displayed_value")
+            displayed_currency = _norm_currency(pos.get("displayed_currency"), account_currency)
+            if displayed_value and float(displayed_value) > 0:
+                v_stock = float(displayed_value) * _get_fx_rate(displayed_currency, stock_currency)
+                shares = v_stock / stock_price if stock_price > 0 else None
+                confidence = "medium"
+                method = "reverse_from_value"
+            else:
+                shares = None
+                confidence = "low"
+                method = "unknown"
+
+        avg_price = pos.get("avg_price")
+        avg_currency = _norm_currency(pos.get("avg_price_currency"), stock_currency)
+        avg_price_stock = None
+        avg_method = "ocr_avg"
+        if avg_price:
+            avg_price_stock = float(avg_price) * _get_fx_rate(avg_currency, stock_currency)
+        else:
+            gain_loss_pct = pos.get("gain_loss_pct")
+            gain_loss_amount = pos.get("gain_loss_amount")
+            displayed_value = pos.get("displayed_value")
+            displayed_currency = _norm_currency(pos.get("displayed_currency"), account_currency)
+
+            # Method 1: reverse from PnL %
+            try:
+                if gain_loss_pct is not None and stock_price is not None:
+                    gl_pct = float(gain_loss_pct)
+                    denom = 1 + (gl_pct / 100.0)
+                    if abs(denom) > 1e-9:
+                        avg_price_stock = stock_price / denom
+                        avg_method = "reverse_from_pnl_pct"
+            except Exception:
+                avg_price_stock = None
+
+            # Method 2: reverse from displayed value and pnl amount
+            if avg_price_stock is None:
+                try:
+                    if gain_loss_amount is not None and displayed_value is not None and shares and float(shares) > 0:
+                        cost_basis_display = float(displayed_value) - float(gain_loss_amount)
+                        fx = _get_fx_rate(displayed_currency, stock_currency)
+                        cost_basis_stock = cost_basis_display * fx
+                        avg_price_stock = cost_basis_stock / float(shares)
+                        avg_method = "reverse_from_pnl_amount"
+                except Exception:
+                    avg_price_stock = None
+
+            # Method 3: fallback to current price
+            if avg_price_stock is None:
+                avg_price_stock = stock_price
+                avg_method = "fallback_current_price"
+
+        if shares and pos.get("displayed_value"):
+            displayed = float(pos["displayed_value"])
+            displayed_currency = _norm_currency(pos.get("displayed_currency"), account_currency)
+            calc_value = float(shares) * stock_price * _get_fx_rate(stock_currency, displayed_currency)
+            err = abs(calc_value - displayed) / displayed * 100 if displayed > 0 else 999
+            if err > 10 and stock_price > 0:
+                shares = displayed * _get_fx_rate(displayed_currency, stock_currency) / stock_price
+                confidence = "medium"
+                method = "reverse_recalculated"
+
+        total_pnl = None
+        pnl_pct = pos.get("gain_loss_pct")
+        if shares and avg_price_stock and stock_price:
+            pnl_per_share = stock_price - avg_price_stock
+            total_pnl = pnl_per_share * float(shares)
+            pnl_pct = (pnl_per_share / avg_price_stock) * 100 if avg_price_stock > 0 else None
+
+        cur_val = None
+        if shares:
+            cur_val = float(shares) * stock_price * _get_fx_rate(stock_currency, account_currency)
+
+        # If avg is reconstructed and shares are available, promote confidence.
+        if confidence == "medium" and avg_method in {"reverse_from_pnl_pct", "reverse_from_pnl_amount"} and shares:
+            confidence = "high"
+
+        out.append({
+            "ticker": ticker,
+            "name": pos.get("name") or ticker,
+            "quantity": round(float(shares), 6) if shares else None,
+            "avg_price": round(float(avg_price_stock), 4) if avg_price_stock is not None else avg_price,
+            "avg_price_currency": stock_currency,
+            "current_price": round(stock_price, 2),
+            "stock_currency": stock_currency,
+            "account_currency": account_currency,
+            "current_value_account": round(cur_val, 2) if cur_val is not None else None,
+            "total_pnl": round(float(total_pnl), 2) if total_pnl is not None else None,
+            "pnl_pct": round(float(pnl_pct), 2) if pnl_pct is not None else None,
+            "weight_pct": pos.get("weight_pct"),
+            "confidence": confidence,
+            "method": method,
+            "avg_method": avg_method,
+            "yf_ticker": yf_ticker,
+        })
+    return out
+
+
+def _detect_mime(image_bytes: bytes) -> str:
+    if image_bytes[:3] == b"\xff\xd8\xff":
+        return "image/jpeg"
+    if image_bytes[:4] == b"RIFF":
+        return "image/webp"
+    return "image/png"
+
+
+def _parse_llm_json(text: str) -> dict:
+    raw = (text or "").strip()
+    raw = re.sub(r"^```json\s*", "", raw, flags=re.I)
+    raw = re.sub(r"^```\s*", "", raw)
+    raw = re.sub(r"\s*```$", "", raw)
+    return json.loads(raw.strip())
+
+
+async def process_portfolio_screenshot(api_key: str, image_bytes: bytes) -> dict:
     if not api_key or not api_key.strip():
         return {"error": "API key is required."}
     if not image_bytes:
         return {"error": "No image data provided."}
 
-    try:
-        model = _get_vision_model(api_key)
-    except Exception as e:
-        return {"error": f"Failed to initialise Gemini Vision: {e}"}
-
-    prompt = _build_prompt()
-
-    # Build multimodal content: image + text prompt
     try:
         import google.generativeai as genai
 
-        # Detect MIME type from magic bytes
-        mime_type = "image/png"
-        if image_bytes[:3] == b"\xff\xd8\xff":
-            mime_type = "image/jpeg"
-        elif image_bytes[:4] == b"\x89PNG":
-            mime_type = "image/png"
-        elif image_bytes[:4] == b"RIFF":
-            mime_type = "image/webp"
-
-        image_part = {"mime_type": mime_type, "data": image_bytes}
-        response = model.generate_content(
-            [image_part, prompt],
-            generation_config={"temperature": 0.0, "max_output_tokens": 4096},
+        genai.configure(api_key=api_key)
+        model = genai.GenerativeModel("gemini-2.0-flash")
+        image_part = {"mime_type": _detect_mime(image_bytes), "data": image_bytes}
+        response = await asyncio.to_thread(
+            model.generate_content,
+            [image_part, SCREENSHOT_OCR_PROMPT],
+            generation_config={"temperature": 0.0, "max_output_tokens": 8192},
         )
-
-        raw = (response.text or "").strip()
-        if not raw:
-            return {"error": "Gemini returned an empty response."}
-
-        # Strip markdown code fences if present
-        raw = re.sub(r"^```\s*json\s*", "", raw)
-        raw = re.sub(r"^```\s*", "", raw)
-        raw = re.sub(r"\s*```\s*$", "", raw)
-        raw = raw.strip()
-
-        result: Dict[str, Any] = json.loads(raw)
-
-        # Validate structure
-        if "error" in result:
-            return result
-        if "positions" not in result:
-            return {"error": "Response missing 'positions' key.", "raw": raw}
-
-        # Coerce numeric fields
-        for pos in result.get("positions", []):
-            for key in ("quantity", "avg_price", "current_price", "market_value", "gain_loss", "gain_loss_pct"):
-                val = pos.get(key)
-                if val is not None:
-                    try:
-                        pos[key] = float(val)
-                    except (TypeError, ValueError):
-                        pos[key] = None
-
-        return result
-
+        parsed = _parse_llm_json(response.text or "")
     except json.JSONDecodeError:
-        return {"error": "Failed to parse JSON from Gemini response.", "raw": raw}
+        return {"error": "Failed to parse OCR result."}
     except Exception as e:
-        return {"error": f"Screenshot analysis failed: {e}"}
+        return {"error": f"OCR model call failed: {e}"}
+
+    enriched = reverse_engineer_positions(parsed)
+    warnings = []
+    for p in enriched:
+        if p.get("confidence") == "low":
+            warnings.append(f"{p.get('ticker')}: Low confidence (market verify failed)")
+        if p.get("method") == "reverse_recalculated":
+            warnings.append(f"{p.get('ticker')}: Quantity recalculated due to >10% mismatch")
+
+    return {
+        "account_currency": _norm_currency(parsed.get("account_currency"), "USD"),
+        "total_value": {
+            "amount": parsed.get("total_value"),
+            "currency": _norm_currency(parsed.get("account_currency"), "USD"),
+        },
+        "positions": enriched,
+        "warnings": warnings,
+        "raw_ocr": parsed,
+    }

atlas-terminal/server/services/sector_heatmap.py

@@ -0,0 +1,37 @@
+"""Sector performance heatmap service."""
+
+from __future__ import annotations
+
+
+SECTOR_ETFS = {
+    "Technology": "XLK",
+    "Healthcare": "XLV",
+    "Financials": "XLF",
+    "Consumer Disc.": "XLY",
+    "Industrials": "XLI",
+    "Energy": "XLE",
+    "Utilities": "XLU",
+    "Materials": "XLB",
+    "Real Estate": "XLRE",
+    "Comm. Services": "XLC",
+    "Consumer Staples": "XLP",
+}
+
+
+async def get_sector_heatmap() -> list[dict]:
+    """Return daily percent change for major US sector ETFs."""
+    import yfinance as yf
+
+    results = []
+    for sector, etf in SECTOR_ETFS.items():
+        try:
+            hist = yf.Ticker(etf).history(period="2d")
+            if hist is None or len(hist) < 2:
+                continue
+            prev = float(hist["Close"].iloc[-2])
+            cur = float(hist["Close"].iloc[-1])
+            change = ((cur - prev) / prev * 100) if prev else 0.0
+            results.append({"sector": sector, "etf": etf, "change_pct": round(change, 2)})
+        except Exception:
+            continue
+    return results

atlas-terminal/server/utils/ticker_utils.py

@@ -5,6 +5,7 @@ Yahoo Finance-compatible identifiers with the correct market suffix,
 and provides the static lookup tables for companies and sectors.
 """
 
+from enum import Enum
 from typing import List, Tuple
 
 # ---------------------------------------------------------------------------
@@ -41,6 +42,41 @@ MARKET_OPTIONS: List[str] = [
     "UK (LSE)",
 ]
 
+
+class AssetType(str, Enum):
+    EQUITY = "equity"
+    ETF = "etf"
+    COMMODITY_FUTURE = "commodity_future"
+    CRYPTO = "crypto"
+    INDEX = "index"
+
+
+COMMODITY_FUTURES: dict[str, str] = {
+    "GC=F": "Gold", "SI=F": "Silver", "PL=F": "Platinum", "PA=F": "Palladium",
+    "CL=F": "Crude Oil (WTI)", "BZ=F": "Brent Crude", "NG=F": "Natural Gas",
+    "HO=F": "Heating Oil", "RB=F": "Gasoline",
+    "ZC=F": "Corn", "ZS=F": "Soybeans", "ZW=F": "Wheat",
+    "KC=F": "Coffee", "CT=F": "Cotton", "SB=F": "Sugar",
+    "CC=F": "Cocoa", "OJ=F": "Orange Juice",
+    "LE=F": "Live Cattle", "HE=F": "Lean Hogs",
+    "HG=F": "Copper", "ALI=F": "Aluminum",
+}
+
+POPULAR_COMMODITY_ETFS: dict[str, str] = {
+    "GLD": "SPDR Gold Trust", "IAU": "iShares Gold Trust", "SLV": "iShares Silver Trust",
+    "PPLT": "abrdn Platinum ETF", "USO": "United States Oil Fund", "UNG": "United States Natural Gas Fund",
+    "XLE": "Energy Select Sector SPDR", "VDE": "Vanguard Energy ETF", "DBC": "Invesco DB Commodity Tracking",
+    "GSG": "iShares S&P GSCI Commodity", "PDBC": "Invesco Optimum Yield Diversified Commodity",
+    "COM": "Direxion Auspice Broad Commodity", "DBA": "Invesco DB Agriculture Fund",
+    "WEAT": "Teucrium Wheat Fund", "CORN": "Teucrium Corn Fund", "SOYB": "Teucrium Soybean Fund",
+    "SPY": "S&P 500 ETF", "QQQ": "Nasdaq 100 ETF", "IWM": "Russell 2000 ETF",
+    "EEM": "Emerging Markets ETF", "VWO": "Vanguard FTSE Emerging Markets",
+    "TLT": "20+ Year Treasury Bond ETF", "HYG": "High Yield Corporate Bond ETF",
+    "LQD": "Investment Grade Corporate Bond ETF", "ARKK": "ARK Innovation ETF",
+    "XLK": "Technology Select Sector SPDR", "XLF": "Financial Select Sector SPDR",
+    "XLV": "Health Care Select Sector SPDR",
+}
+
 # ---------------------------------------------------------------------------
 # Sector / industry peer groups (top-down analysis)
 # ---------------------------------------------------------------------------
@@ -120,3 +156,28 @@ def infer_market_from_ticker(ticker: str) -> str:
     if t.endswith(".L"):
         return "UK (LSE)"
     return "US (S&P/Dow/Nasdaq)"
+
+
+def detect_asset_type(ticker: str) -> AssetType:
+    """Detect asset type by ticker pattern and quoteType fallback."""
+    t = (ticker or "").strip().upper()
+    if not t:
+        return AssetType.EQUITY
+    if t.endswith("=F") or t in COMMODITY_FUTURES:
+        return AssetType.COMMODITY_FUTURE
+    if t.endswith("-USD") or t.endswith("-KRW"):
+        return AssetType.CRYPTO
+    if t.startswith("^"):
+        return AssetType.INDEX
+    try:
+        import yfinance as yf
+
+        info = yf.Ticker(t).info or {}
+        quote_type = str(info.get("quoteType", "")).upper()
+        if quote_type in {"ETF", "MUTUALFUND"}:
+            return AssetType.ETF
+    except Exception:
+        pass
+    if t in POPULAR_COMMODITY_ETFS:
+        return AssetType.ETF
+    return AssetType.EQUITY