feat: add Atlas Terminal — Next.js 14 + FastAPI full-stack migration

Complete migration from Streamlit to Next.js 14 App Router + FastAPI backend.

Frontend (Next.js 14):
- 10 pages: Overview, Research, Valuation, Technical, Markets, Earnings, News, Portfolio, Filings, Settings
- Terminal Noir dark theme with custom Tailwind config
- TradingView Lightweight Charts for candlestick/volume
- Valuation: DCF, Sensitivity Matrix, Monte Carlo, Tornado, Reverse DCF
- Financial Statements table with YoY growth badges and margin rows
- SEC EDGAR inline filing viewer with section tabs
- News split-view with iframe article embedding
- Technical Analysis with RSI, MACD, Bollinger, Fibonacci, Moving Averages
- Earnings beat/miss visualization
- AI Copilot chat panel with Gemini integration

Backend (FastAPI):
- 13 routers: market_data, financials, valuation, technical, earnings, insider, edgar, news, portfolio, analysis, chat, estimates, fx
- Services: DCF engine, Monte Carlo simulation, sensitivity analysis, risk metrics, SEC parser, technical indicators
- yfinance + yahooquery data sources with fallback pattern
- SQLite caching layer

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

data/estimates.py

@@ -0,0 +1,88 @@
+"""
+Analyst estimates — earnings & revenue forecasts, consensus targets.
+"""
+import streamlit as st
+import pandas as pd
+
+try:
+    import yfinance as yf
+except ImportError:
+    yf = None
+
+
+@st.cache_data(ttl=600)
+def get_analyst_estimates(ticker: str) -> dict:
+    """Fetch analyst earnings and revenue estimates from yfinance."""
+    if not yf or not ticker:
+        return {}
+    try:
+        t = yf.Ticker(ticker)
+        result = {}
+
+        # Earnings estimates
+        ee = getattr(t, "earnings_estimate", None)
+        if ee is not None and not ee.empty:
+            result["earnings_estimate"] = ee
+
+        # Revenue estimates
+        re = getattr(t, "revenue_estimate", None)
+        if re is not None and not re.empty:
+            result["revenue_estimate"] = re
+
+        # EPS trend
+        et = getattr(t, "eps_trend", None)
+        if et is not None and not et.empty:
+            result["eps_trend"] = et
+
+        # Earnings history
+        eh = getattr(t, "earnings_history", None)
+        if eh is not None and not eh.empty:
+            result["earnings_history"] = eh
+
+        # Growth estimates
+        ge = getattr(t, "growth_estimates", None)
+        if ge is not None and not ge.empty:
+            result["growth_estimates"] = ge
+
+        # Price targets
+        info = t.info or {}
+        result["targets"] = {
+            "current": info.get("currentPrice") or info.get("regularMarketPrice"),
+            "mean": info.get("targetMeanPrice"),
+            "high": info.get("targetHighPrice"),
+            "low": info.get("targetLowPrice"),
+            "median": info.get("targetMedianPrice"),
+            "recommendation": info.get("recommendationKey", "N/A"),
+            "num_analysts": info.get("numberOfAnalystOpinions"),
+        }
+
+        return result
+    except Exception:
+        return {}
+
+
+@st.cache_data(ttl=600)
+def get_earnings_dates(ticker: str) -> pd.DataFrame:
+    """Fetch historical and upcoming earnings dates with surprise data."""
+    if not yf or not ticker:
+        return pd.DataFrame()
+    try:
+        t = yf.Ticker(ticker)
+        dates = t.earnings_dates
+        if dates is not None and not dates.empty:
+            return dates.head(12)
+    except Exception:
+        pass
+    return pd.DataFrame()
+
+
+def format_estimate_table(df: pd.DataFrame) -> pd.DataFrame:
+    """Format estimate DataFrame for display with proper number formatting."""
+    if df is None or df.empty:
+        return pd.DataFrame()
+    display = df.copy()
+    for col in display.columns:
+        display[col] = display[col].apply(
+            lambda v: f"{v:,.2f}" if isinstance(v, (int, float)) and v == v else "N/A"
+        )
+    return display