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>

4 files changed, 437 insertions, 22 deletions

diff --git a/components/financials.py b/components/financials.py
index 828f256..9078770 100644
--- a/components/financials.py
+++ b/components/financials.py
@@ -116,6 +116,13 @@ def render_financials(ticker: str):
         else:
             display, colors = _build_statement(df)
             st.dataframe(_style(display, colors), use_container_width=True)
+            st.download_button(
+                "Download CSV",
+                df.to_csv().encode(),
+                file_name=f"{ticker.upper()}_income_{'quarterly' if quarterly else 'annual'}.csv",
+                mime="text/csv",
+                key=f"dl_income_{ticker}_{quarterly}",
+            )
 
     with tab_balance:
         df = get_balance_sheet(ticker, quarterly=quarterly)
@@ -124,6 +131,13 @@ def render_financials(ticker: str):
         else:
             display, colors = _build_statement(df)
             st.dataframe(_style(display, colors), use_container_width=True)
+            st.download_button(
+                "Download CSV",
+                df.to_csv().encode(),
+                file_name=f"{ticker.upper()}_balance_{'quarterly' if quarterly else 'annual'}.csv",
+                mime="text/csv",
+                key=f"dl_balance_{ticker}_{quarterly}",
+            )
 
     with tab_cashflow:
         df = get_cash_flow(ticker, quarterly=quarterly)
@@ -132,3 +146,10 @@ def render_financials(ticker: str):
         else:
             display, colors = _build_statement(df)
             st.dataframe(_style(display, colors), use_container_width=True)
+            st.download_button(
+                "Download CSV",
+                df.to_csv().encode(),
+                file_name=f"{ticker.upper()}_cashflow_{'quarterly' if quarterly else 'annual'}.csv",
+                mime="text/csv",
+                key=f"dl_cashflow_{ticker}_{quarterly}",
+            )
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)
diff --git a/components/overview.py b/components/overview.py
index 7407753..53b8554 100644
--- a/components/overview.py
+++ b/components/overview.py
@@ -1,4 +1,4 @@
-"""Company overview — header, key stats, and price chart."""
+"""Company overview — score card, key stats, 52W range, short interest, price chart."""
 import streamlit as st
 import plotly.graph_objects as go
 from services.data_service import get_company_info, get_price_history
@@ -8,23 +8,202 @@ from utils.formatters import fmt_large, fmt_currency, fmt_pct, fmt_ratio
 PERIODS = {"1 Month": "1mo", "3 Months": "3mo", "6 Months": "6mo", "1 Year": "1y", "5 Years": "5y"}
 
 
+# ── Score card ───────────────────────────────────────────────────────────────
+
+def _score_card(info: dict) -> None:
+    """Render a row of green/yellow/red signal badges."""
+    signals: list[tuple[str, str, str, str]] = []  # (label, color, value, description)
+
+    # Valuation — trailing P/E
+    pe = info.get("trailingPE")
+    if pe and pe > 0:
+        if pe < 15:
+            signals.append(("Valuation", "green", f"P/E {pe:.1f}x", "Attractively valued"))
+        elif pe < 30:
+            signals.append(("Valuation", "yellow", f"P/E {pe:.1f}x", "Fairly valued"))
+        else:
+            signals.append(("Valuation", "red", f"P/E {pe:.1f}x", "Richly valued"))
+    else:
+        signals.append(("Valuation", "neutral", "P/E N/A", "No trailing earnings"))
+
+    # Revenue growth (TTM YoY)
+    rev_growth = info.get("revenueGrowth")
+    if rev_growth is not None:
+        if rev_growth > 0.10:
+            signals.append(("Growth", "green", f"{rev_growth*100:+.0f}% rev", "Strong growth"))
+        elif rev_growth >= 0:
+            signals.append(("Growth", "yellow", f"{rev_growth*100:+.0f}% rev", "Slow growth"))
+        else:
+            signals.append(("Growth", "red", f"{rev_growth*100:+.0f}% rev", "Declining revenue"))
+
+    # Profitability — net margin
+    margin = info.get("profitMargins")
+    if margin is not None:
+        if margin > 0.15:
+            signals.append(("Profit", "green", f"{margin*100:.0f}% margin", "High margins"))
+        elif margin > 0.05:
+            signals.append(("Profit", "yellow", f"{margin*100:.0f}% margin", "Moderate margins"))
+        else:
+            signals.append(("Profit", "red", f"{margin*100:.0f}% margin", "Thin/negative margins"))
+
+    # Leverage — D/E (yfinance returns as %, e.g. 162 = 1.62x)
+    de = info.get("debtToEquity")
+    if de is not None:
+        de_x = de / 100
+        if de_x < 0.5:
+            signals.append(("Leverage", "green", f"D/E {de_x:.2f}x", "Low leverage"))
+        elif de_x < 2.0:
+            signals.append(("Leverage", "yellow", f"D/E {de_x:.2f}x", "Moderate leverage"))
+        else:
+            signals.append(("Leverage", "red", f"D/E {de_x:.2f}x", "High leverage"))
+
+    # Momentum — price vs 52W high
+    price = info.get("currentPrice") or info.get("regularMarketPrice")
+    high52 = info.get("fiftyTwoWeekHigh")
+    if price and high52 and high52 > 0:
+        from_high_pct = (price - high52) / high52 * 100
+        if from_high_pct > -10:
+            signals.append(("Momentum", "green", f"{from_high_pct:.0f}% from 52W↑", "Near highs"))
+        elif from_high_pct > -25:
+            signals.append(("Momentum", "yellow", f"{from_high_pct:.0f}% from 52W↑", "Mid-range"))
+        else:
+            signals.append(("Momentum", "red", f"{from_high_pct:.0f}% from 52W↑", "Far from highs"))
+
+    # Short interest
+    short_pct = info.get("shortPercentOfFloat")
+    if short_pct is not None:
+        if short_pct < 0.05:
+            signals.append(("Short Int.", "green", f"{short_pct*100:.1f}% float", "Low short interest"))
+        elif short_pct < 0.15:
+            signals.append(("Short Int.", "yellow", f"{short_pct*100:.1f}% float", "Moderate short interest"))
+        else:
+            signals.append(("Short Int.", "red", f"{short_pct*100:.1f}% float", "High short interest"))
+
+    if not signals:
+        return
+
+    color_map = {
+        "green":   ("rgba(46,204,113,0.15)",  "#7ce3a1"),
+        "yellow":  ("rgba(243,156,18,0.15)",   "#f0c040"),
+        "red":     ("rgba(231,76,60,0.15)",    "#ff8a8a"),
+        "neutral": ("rgba(255,255,255,0.05)",  "#9aa0b0"),
+    }
+
+    cards_html = ""
+    for label, color, value, desc in signals:
+        bg, fg = color_map[color]
+        cards_html += (
+            f'<div style="background:{bg};border:1px solid {fg}44;border-radius:10px;'
+            f'padding:0.5rem 0.75rem;flex:1;min-width:110px;">'
+            f'<div style="font-size:0.68rem;font-weight:600;color:#9aa0b0;text-transform:uppercase;'
+            f'letter-spacing:0.05em;margin-bottom:0.15rem;">{label}</div>'
+            f'<div style="font-size:0.85rem;font-weight:700;color:{fg};">{value}</div>'
+            f'<div style="font-size:0.68rem;color:#9aa0b0;margin-top:0.1rem;">{desc}</div>'
+            f'</div>'
+        )
+
+    st.markdown(
+        f'<div style="display:flex;gap:0.5rem;margin-bottom:0.75rem;flex-wrap:wrap;">{cards_html}</div>',
+        unsafe_allow_html=True,
+    )
+
+
+# ── 52-week range bar ────────────────────────────────────────────────────────
+
+def _render_52w_bar(info: dict) -> None:
+    low = info.get("fiftyTwoWeekLow")
+    high = info.get("fiftyTwoWeekHigh")
+    price = info.get("currentPrice") or info.get("regularMarketPrice")
+
+    if not (low and high and price and high > low):
+        return
+
+    pct = max(0.0, min(100.0, (price - low) / (high - low) * 100))
+    from_low_pct = (price - low) / low * 100
+    to_high_pct = (high - price) / price * 100
+
+    st.markdown(
+        f"""
+        <div style="margin:0.4rem 0 0.9rem 0;">
+          <div style="display:flex;justify-content:space-between;font-size:0.72rem;color:#9aa0b0;margin-bottom:0.35rem;">
+            <span>52W Low: {fmt_currency(low)}</span>
+            <span style="color:#c6cfdd;font-weight:600;">
+              {fmt_currency(price)} &nbsp;·&nbsp; {pct:.0f}% of range
+            </span>
+            <span>52W High: {fmt_currency(high)}</span>
+          </div>
+          <div style="position:relative;height:7px;background:rgba(255,255,255,0.08);border-radius:4px;overflow:visible;">
+            <div style="position:absolute;left:0;width:{pct}%;height:100%;
+                        background:linear-gradient(to right,#e74c3c,#f0b27a,#2ecc71);border-radius:4px;"></div>
+            <div style="position:absolute;left:calc({pct}% - 2px);top:-4px;width:4px;height:15px;
+                        background:#fff;border-radius:2px;box-shadow:0 0 5px rgba(0,0,0,0.5);"></div>
+          </div>
+          <div style="display:flex;justify-content:space-between;font-size:0.68rem;color:#9aa0b0;margin-top:0.3rem;">
+            <span>+{from_low_pct:.1f}% above low</span>
+            <span>{to_high_pct:.1f}% below high</span>
+          </div>
+        </div>
+        """,
+        unsafe_allow_html=True,
+    )
+
+
+# ── Short interest strip ─────────────────────────────────────────────────────
+
+def _render_short_interest(info: dict) -> None:
+    short_pct = info.get("shortPercentOfFloat")
+    short_ratio = info.get("shortRatio")
+    shares_short = info.get("sharesShort")
+    shares_short_prior = info.get("sharesShortPriorMonth")
+
+    if not any([short_pct, short_ratio, shares_short]):
+        return
+
+    st.markdown("**Short Interest**")
+    cols = st.columns(4)
+
+    cols[0].metric(
+        "Short % of Float",
+        f"{short_pct * 100:.2f}%" if short_pct is not None else "—",
+    )
+    cols[1].metric(
+        "Days to Cover",
+        f"{short_ratio:.1f}" if short_ratio is not None else "—",
+        help="Shares short ÷ avg daily volume. Higher = harder to unwind.",
+    )
+    cols[2].metric(
+        "Shares Short",
+        fmt_large(shares_short) if shares_short else "—",
+    )
+    if shares_short and shares_short_prior:
+        chg = (shares_short - shares_short_prior) / shares_short_prior * 100
+        cols[3].metric(
+            "vs Prior Month",
+            fmt_large(shares_short_prior),
+            delta=f"{chg:+.1f}%",
+        )
+    else:
+        cols[3].metric("Prior Month", fmt_large(shares_short_prior) if shares_short_prior else "—")
+
+
+# ── Main render ──────────────────────────────────────────────────────────────
+
 def render_overview(ticker: str):
     info = get_company_info(ticker)
     if not info:
         st.error(f"Could not load data for **{ticker}**. Check the ticker symbol.")
         return
 
-    # ── Company header ──────────────────────────────────────────────────────
     name = info.get("longName") or info.get("shortName", ticker.upper())
     price = info.get("currentPrice") or info.get("regularMarketPrice")
     prev_close = info.get("regularMarketPreviousClose") or info.get("previousClose")
 
-    price_change = None
-    price_change_pct = None
+    price_change = price_change_pct = None
     if price and prev_close:
         price_change = price - prev_close
         price_change_pct = price_change / prev_close
 
+    # ── Header ──────────────────────────────────────────────────────────────
     col1, col2 = st.columns([3, 1])
     with col1:
         st.subheader(f"{name} ({ticker.upper()})")
@@ -32,7 +211,6 @@ def render_overview(ticker: str):
         industry = info.get("industry", "")
         if sector:
             st.caption(f"{sector} · {industry}")
-
     with col2:
         delta_str = None
         if price_change is not None and price_change_pct is not None:
@@ -43,19 +221,30 @@ def render_overview(ticker: str):
             delta=delta_str,
         )
 
+    # ── Score card ──────────────────────────────────────────────────────────
+    _score_card(info)
+
     # ── Key stats strip ─────────────────────────────────────────────────────
     stats_cols = st.columns(6)
     stats = [
-        ("Mkt Cap", fmt_large(info.get("marketCap"))),
-        ("P/E (TTM)", fmt_ratio(info.get("trailingPE"))),
-        ("EPS (TTM)", fmt_currency(info.get("trailingEps"))),
-        ("52W High", fmt_currency(info.get("fiftyTwoWeekHigh"))),
-        ("52W Low", fmt_currency(info.get("fiftyTwoWeekLow"))),
-        ("Beta", fmt_ratio(info.get("beta"))),
+        ("Mkt Cap",     fmt_large(info.get("marketCap"))),
+        ("P/E (TTM)",   fmt_ratio(info.get("trailingPE"))),
+        ("EPS (TTM)",   fmt_currency(info.get("trailingEps"))),
+        ("Volume",      fmt_large(info.get("volume"))),
+        ("Avg Volume",  fmt_large(info.get("averageVolume"))),
+        ("Beta",        fmt_ratio(info.get("beta"))),
     ]
     for col, (label, val) in zip(stats_cols, stats):
         col.metric(label, val)
 
+    st.write("")
+
+    # ── 52-week range bar ────────────────────────────────────────────────────
+    _render_52w_bar(info)
+
+    # ── Short interest ───────────────────────────────────────────────────────
+    _render_short_interest(info)
+
     st.divider()
 
     # ── Price chart ─────────────────────────────────────────────────────────
@@ -74,17 +263,15 @@ def render_overview(ticker: str):
         return
 
     fig = go.Figure()
-    fig.add_trace(
-        go.Scatter(
-            x=hist.index,
-            y=hist["Close"],
-            mode="lines",
-            name="Close",
-            line=dict(color="#4F8EF7", width=2),
-            fill="tozeroy",
-            fillcolor="rgba(79, 142, 247, 0.08)",
-        )
-    )
+    fig.add_trace(go.Scatter(
+        x=hist.index,
+        y=hist["Close"],
+        mode="lines",
+        name="Close",
+        line=dict(color="#4F8EF7", width=2),
+        fill="tozeroy",
+        fillcolor="rgba(79,142,247,0.08)",
+    ))
     fig.update_layout(
         margin=dict(l=0, r=0, t=10, b=0),
         xaxis=dict(showgrid=False, zeroline=False),
diff --git a/components/valuation.py b/components/valuation.py
index 5536818..b6e9d46 100644
--- a/components/valuation.py
+++ b/components/valuation.py
@@ -567,6 +567,13 @@ def _render_earnings_history(ticker: str):
         use_container_width=True,
         hide_index=False,
     )
+    st.download_button(
+        "Download CSV",
+        display.to_csv().encode(),
+        file_name=f"{ticker.upper()}_earnings_history.csv",
+        mime="text/csv",
+        key=f"dl_earnings_{ticker}",
+    )
 
     # EPS chart — oldest to newest
     df_chart = eh.sort_index()