Add score card, 52W range bar, short interest, options tab, CSV exports

Overview:
- Score card: green/yellow/red signals for valuation, growth, profitability,
  leverage, momentum (vs 52W high), and short interest
- 52W high/low visual range bar with current price marker and % context
- Short interest metrics row: % of float, days to cover, shares short vs
  prior month
- Replaced static 52W High/Low metrics with volume and avg volume

Options tab (new):
- Expiry selector across all available expirations
- Put/call ratio by volume and open interest with bullish/bearish label
- IV smile chart (calls + puts) with ATM marker
- Open interest by strike (calls above, puts mirrored below axis)
- Full chain table (calls/puts) in expandable section

CSV exports:
- Download button on each financial statement (income, balance, cash flow)
- Download button on earnings history table

Also fix top padding cut-off: block-container padding-top 1rem → 3.5rem

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

1 files changed, 200 insertions, 0 deletions

diff --git a/components/options.py b/components/options.py
new file mode 100644
index 0000000..e9bf016
--- /dev/null
+++ b/components/options.py
@@ -0,0 +1,200 @@
+"""Options flow — put/call ratios, IV smile, open interest by strike."""
+import pandas as pd
+import plotly.graph_objects as go
+import streamlit as st
+from services.data_service import get_company_info, get_options_chain
+
+
+def render_options(ticker: str):
+    info = get_company_info(ticker)
+    current_price = info.get("currentPrice") or info.get("regularMarketPrice")
+
+    with st.spinner("Loading options data…"):
+        data = get_options_chain(ticker)
+
+    if not data or not data.get("chains"):
+        st.info("Options data unavailable for this ticker.")
+        return
+
+    expirations = data["expirations"]
+    chains = data["chains"]
+
+    # ── Expiry selector ──────────────────────────────────────────────────────
+    selected_expiry = st.selectbox(
+        "Expiration date",
+        options=expirations,
+        key=f"options_expiry_{ticker}",
+    )
+
+    chain_data = next((c for c in chains if c["expiry"] == selected_expiry), None)
+    if chain_data is None:
+        # Expiry beyond the pre-fetched set — fetch on demand
+        try:
+            import yfinance as yf
+            t = yf.Ticker(ticker.upper())
+            chain = t.option_chain(selected_expiry)
+            chain_data = {"expiry": selected_expiry, "calls": chain.calls, "puts": chain.puts}
+        except Exception:
+            st.info("Could not load chain for this expiry.")
+            return
+
+    calls: pd.DataFrame = chain_data["calls"].copy()
+    puts: pd.DataFrame = chain_data["puts"].copy()
+
+    # ── Summary metrics ──────────────────────────────────────────────────────
+    total_call_vol = float(calls["volume"].sum()) if "volume" in calls.columns else 0.0
+    total_put_vol = float(puts["volume"].sum()) if "volume" in puts.columns else 0.0
+    total_call_oi = float(calls["openInterest"].sum()) if "openInterest" in calls.columns else 0.0
+    total_put_oi = float(puts["openInterest"].sum()) if "openInterest" in puts.columns else 0.0
+
+    pc_vol = total_put_vol / total_call_vol if total_call_vol > 0 else None
+    pc_oi = total_put_oi / total_call_oi if total_call_oi > 0 else None
+
+    def _pc_delta(val):
+        if val is None:
+            return None
+        if val < 0.7:
+            return "Bullish"
+        if val < 1.0:
+            return "Neutral"
+        return "Bearish"
+
+    m1, m2, m3, m4 = st.columns(4)
+    m1.metric(
+        "P/C Ratio (Volume)",
+        f"{pc_vol:.2f}" if pc_vol is not None else "—",
+        delta=_pc_delta(pc_vol),
+        delta_color="inverse" if pc_vol and pc_vol >= 1.0 else "normal",
+        help="Put/Call volume ratio. >1 = more put activity (bearish bets).",
+    )
+    m2.metric(
+        "P/C Ratio (OI)",
+        f"{pc_oi:.2f}" if pc_oi is not None else "—",
+        delta=_pc_delta(pc_oi),
+        delta_color="inverse" if pc_oi and pc_oi >= 1.0 else "normal",
+        help="Put/Call open interest ratio.",
+    )
+    m3.metric("Total Call Volume", f"{int(total_call_vol):,}" if total_call_vol else "—")
+    m4.metric("Total Put Volume", f"{int(total_put_vol):,}" if total_put_vol else "—")
+
+    st.write("")
+
+    # Filter strikes ±30% of current price for cleaner charts
+    if current_price and not calls.empty:
+        lo, hi = current_price * 0.70, current_price * 1.30
+        calls_atm = calls[(calls["strike"] >= lo) & (calls["strike"] <= hi)]
+        puts_atm = puts[(puts["strike"] >= lo) & (puts["strike"] <= hi)]
+    else:
+        calls_atm = calls
+        puts_atm = puts
+
+    if calls_atm.empty and puts_atm.empty:
+        st.info("No near-the-money options found for this expiry.")
+        return
+
+    chart_col1, chart_col2 = st.columns(2)
+
+    # ── IV Smile ─────────────────────────────────────────────────────────────
+    with chart_col1:
+        if "impliedVolatility" in calls_atm.columns:
+            st.markdown("**Implied Volatility Smile**")
+            fig_iv = go.Figure()
+            fig_iv.add_trace(go.Scatter(
+                x=calls_atm["strike"],
+                y=calls_atm["impliedVolatility"] * 100,
+                name="Calls IV",
+                mode="lines+markers",
+                line=dict(color="#4F8EF7", width=2),
+                marker=dict(size=4),
+            ))
+            if not puts_atm.empty and "impliedVolatility" in puts_atm.columns:
+                fig_iv.add_trace(go.Scatter(
+                    x=puts_atm["strike"],
+                    y=puts_atm["impliedVolatility"] * 100,
+                    name="Puts IV",
+                    mode="lines+markers",
+                    line=dict(color="#F7A24F", width=2),
+                    marker=dict(size=4),
+                ))
+            if current_price:
+                fig_iv.add_vline(
+                    x=current_price,
+                    line_dash="dash",
+                    line_color="rgba(255,255,255,0.35)",
+                    annotation_text="ATM",
+                    annotation_position="top",
+                )
+            fig_iv.update_layout(
+                yaxis_title="Implied Volatility (%)",
+                xaxis_title="Strike",
+                plot_bgcolor="rgba(0,0,0,0)",
+                paper_bgcolor="rgba(0,0,0,0)",
+                margin=dict(l=0, r=0, t=10, b=0),
+                height=300,
+                legend=dict(orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1),
+                hovermode="x unified",
+            )
+            st.plotly_chart(fig_iv, use_container_width=True)
+
+    # ── Open Interest by strike ───────────────────────────────────────────────
+    with chart_col2:
+        if "openInterest" in calls_atm.columns:
+            st.markdown("**Open Interest by Strike**")
+            fig_oi = go.Figure()
+            fig_oi.add_trace(go.Bar(
+                x=calls_atm["strike"],
+                y=calls_atm["openInterest"].fillna(0),
+                name="Calls OI",
+                marker_color="rgba(79,142,247,0.75)",
+            ))
+            if not puts_atm.empty and "openInterest" in puts_atm.columns:
+                fig_oi.add_trace(go.Bar(
+                    x=puts_atm["strike"],
+                    y=-puts_atm["openInterest"].fillna(0),
+                    name="Puts OI",
+                    marker_color="rgba(247,162,79,0.75)",
+                ))
+            if current_price:
+                fig_oi.add_vline(
+                    x=current_price,
+                    line_dash="dash",
+                    line_color="rgba(255,255,255,0.35)",
+                    annotation_text="ATM",
+                    annotation_position="top",
+                )
+            fig_oi.update_layout(
+                barmode="overlay",
+                yaxis_title="Open Interest (puts mirrored)",
+                xaxis_title="Strike",
+                plot_bgcolor="rgba(0,0,0,0)",
+                paper_bgcolor="rgba(0,0,0,0)",
+                margin=dict(l=0, r=0, t=10, b=0),
+                height=300,
+                legend=dict(orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1),
+            )
+            st.plotly_chart(fig_oi, use_container_width=True)
+
+    # ── Raw chain table ───────────────────────────────────────────────────────
+    with st.expander("Full options chain"):
+        tab_calls, tab_puts = st.tabs(["Calls", "Puts"])
+        display_cols = ["strike", "lastPrice", "bid", "ask", "volume", "openInterest", "impliedVolatility"]
+
+        with tab_calls:
+            show_cols = [c for c in display_cols if c in calls.columns]
+            if show_cols:
+                df_show = calls[show_cols].copy()
+                if "impliedVolatility" in df_show.columns:
+                    df_show["impliedVolatility"] = df_show["impliedVolatility"].apply(
+                        lambda v: f"{v*100:.1f}%" if pd.notna(v) else "—"
+                    )
+                st.dataframe(df_show, use_container_width=True, hide_index=True)
+
+        with tab_puts:
+            show_cols = [c for c in display_cols if c in puts.columns]
+            if show_cols:
+                df_show = puts[show_cols].copy()
+                if "impliedVolatility" in df_show.columns:
+                    df_show["impliedVolatility"] = df_show["impliedVolatility"].apply(
+                        lambda v: f"{v*100:.1f}%" if pd.notna(v) else "—"
+                    )
+                st.dataframe(df_show, use_container_width=True, hide_index=True)