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
2026-08-22 15:18:04 +00:00 · 2026-03-21 17:08:00 +00:00
parent e225c05cc8
commit 38c56a5a43
35 changed files with 3224 additions and 287 deletions
@@ -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",
+    }