diff --git a/src/charts/bubble_dashboard.py b/src/charts/bubble_dashboard.py
new file mode 100644
index 0000000..5b2cbc4
--- /dev/null
+++ b/src/charts/bubble_dashboard.py
@@ -0,0 +1,101 @@
+"""Composite Bubble Indicators Dashboard — 2x2 grid"""
+import matplotlib
+matplotlib.use("Agg")
+
+# Patch matplotlib Path.__deepcopy__ to break Python 3.14 recursion loop
+# This is a known bug: https://github.com/matplotlib/matplotlib/issues/29280
+try:
+    from matplotlib.path import Path
+    _original_path_deepcopy = Path.__deepcopy__
+    def _safe_path_deepcopy(self, memo):
+        if id(self) in memo:
+            return memo[id(self)]
+        memo[id(self)] = self
+        return self
+    Path.__deepcopy__ = _safe_path_deepcopy
+except Exception:
+    pass
+
+import matplotlib.pyplot as plt
+from src.data.market_bubbles import shiller_cape, buffett_indicator, sp500_pe
+from src.utils.styling import (
+    get_theme, EXPORT_DPI, BUBBLE_ZONE, WARNING_ZONE, NORMAL_ZONE,
+    GRAY_DARK, BLACK, WHITE, FIGURE_SIZE_WIDE
+)
+
+
+def plot_bubble_dashboard() -> str:
+    """Generate 2x2 composite dashboard: CAPE, Buffett, P/E, AI Multiples."""
+    plt.rcParams.update(get_theme())
+    fig, axes = plt.subplots(2, 2, figsize=(16, 12))
+
+    # Panel 1: CAPE (top-left)
+    ax1 = axes[0, 0]
+    years = [d["year"] for d in shiller_cape]
+    values = [d["value"] for d in shiller_cape]
+    ax1.axhspan(0, 20, alpha=0.15, color=NORMAL_ZONE)
+    ax1.axhspan(20, 30, alpha=0.15, color=WARNING_ZONE)
+    ax1.axhspan(30, 50, alpha=0.15, color=BUBBLE_ZONE)
+    ax1.plot(years, values, color=GRAY_DARK, linewidth=1)
+    ax1.axhline(y=17.39, color="#333", linestyle="--", linewidth=0.8)
+    ax1.set_title("Shiller CAPE (1880–2026)", fontsize=13, fontweight="bold")
+    ax1.set_ylabel("CAPE")
+    ax1.grid(True, alpha=0.2)
+    ax1.set_ylim(0, 50)
+
+    # Panel 2: Buffett Indicator (top-right)
+    ax2 = axes[0, 1]
+    b_years = [d["year"] for d in buffett_indicator]
+    b_values = [d["value"] for d in buffett_indicator]
+    ax2.axhspan(0, 100, alpha=0.15, color=NORMAL_ZONE)
+    ax2.axhspan(100, 200, alpha=0.15, color=WARNING_ZONE)
+    ax2.axhspan(200, 300, alpha=0.15, color=BUBBLE_ZONE)
+    ax2.plot(b_years, b_values, color=GRAY_DARK, linewidth=1)
+    ax2.axhline(y=200, color=BUBBLE_ZONE, linestyle="--", linewidth=1)
+    ax2.text(2010, 205, "Danger: 200%", fontsize=9, color=BUBBLE_ZONE)
+    ax2.set_title("Buffett Indicator (1975–2026)", fontsize=13, fontweight="bold")
+    ax2.set_ylabel("Mkt Cap / GDP (%)")
+    ax2.grid(True, alpha=0.2)
+
+    # Panel 3: P/E (bottom-left)
+    ax3 = axes[1, 0]
+    pe_years = [d["year"] for d in sp500_pe]
+    pe_values = [d["value"] for d in sp500_pe]
+    ax3.plot(pe_years, pe_values, color=GRAY_DARK, linewidth=1)
+    ax3.axhline(y=18.2, color="#333", linestyle="--", linewidth=0.8)
+    ax3.set_title("S&P 500 P/E Ratio (1950–2026)", fontsize=13, fontweight="bold")
+    ax3.set_ylabel("P/E Ratio")
+    ax3.set_xlabel("Year")
+    ax3.grid(True, alpha=0.2)
+    ax3.set_ylim(0, 75)
+
+    # Panel 4: AI Startup Multiples (bottom-right)
+    ax4 = axes[1, 1]
+    companies = ["OpenAI", "Anthropic", "Perplexity", "Mistral AI", "S&P Avg (ref)"]
+    multiples = [31, 40, 45, 120, 18]
+    colors_bar = [WARNING_ZONE, WARNING_ZONE, BUBBLE_ZONE, BUBBLE_ZONE, NORMAL_ZONE]
+    bars = ax4.barh(companies, multiples, color=colors_bar, edgecolor="white", height=0.6)
+    ax4.set_xlabel("Revenue Multiple (x)", fontsize=11)
+    ax4.set_title("AI Startup Valuation Multiples", fontsize=13, fontweight="bold")
+    ax4.grid(True, alpha=0.2, axis="x")
+    # Add value labels
+    for bar, val in zip(bars, multiples):
+        ax4.text(val + 2, bar.get_y() + bar.get_height() / 2, f"{val}x",
+                 va="center", fontsize=10, fontweight="bold")
+
+    fig.suptitle("Market Bubble Indicators — June 2026", fontsize=18, fontweight="bold", y=0.98)
+    fig.subplots_adjust(hspace=0.35, wspace=0.25, top=0.93, bottom=0.05)
+
+    fig.savefig("output/charts/04_bubble_dashboard.png", dpi=EXPORT_DPI,
+                facecolor=fig.get_facecolor(), edgecolor="none")
+    plt.close(fig)
+    return "output/charts/04_bubble_dashboard.png"
+
+
+def main():
+    path = plot_bubble_dashboard()
+    print(f"Dashboard saved: {path}")
+
+
+if __name__ == "__main__":
+    main()