diff --git a/cli/chart_generator.py b/cli/chart_generator.py
new file mode 100644
index 00000000..655396ba
--- /dev/null
+++ b/cli/chart_generator.py
@@ -0,0 +1,248 @@
+"""Chart generation utilities for PDF reports."""
+import io
+from pathlib import Path
+from typing import Optional, Dict, Any
+import datetime
+
+
+def generate_stock_price_chart(ticker: str, analysis_date: str) -> Optional[io.BytesIO]:
+    """
+    Generate a stock price chart with moving averages.
+
+    Args:
+        ticker: Stock ticker symbol
+        analysis_date: Analysis date string (YYYY-MM-DD)
+
+    Returns:
+        BytesIO buffer containing the chart image, or None if generation fails
+    """
+    try:
+        import matplotlib.pyplot as plt
+        import matplotlib.dates as mdates
+        import yfinance as yf
+        from datetime import datetime, timedelta
+    except ImportError:
+        print("Warning: matplotlib required for chart generation")
+        return None
+
+    try:
+        # Parse the analysis date
+        end_date = datetime.strptime(analysis_date, '%Y-%m-%d')
+        # Get 90 days of data for context
+        start_date = end_date - timedelta(days=90)
+
+        # Fetch stock data
+        stock = yf.Ticker(ticker)
+        df = stock.history(start=start_date.strftime('%Y-%m-%d'),
+                          end=end_date.strftime('%Y-%m-%d'))
+
+        if df.empty:
+            print(f"Warning: No data available for {ticker}")
+            return None
+
+        # Calculate moving averages
+        df['SMA_20'] = df['Close'].rolling(window=20).mean()
+        df['SMA_50'] = df['Close'].rolling(window=50).mean()
+
+        # Create the figure
+        fig, ax = plt.subplots(figsize=(10, 6))
+
+        # Plot price and moving averages
+        ax.plot(df.index, df['Close'], label='Close Price', linewidth=2, color='#2E86AB')
+        ax.plot(df.index, df['SMA_20'], label='20-day SMA', linewidth=1.5,
+                linestyle='--', color='#A23B72', alpha=0.8)
+        ax.plot(df.index, df['SMA_50'], label='50-day SMA', linewidth=1.5,
+                linestyle='--', color='#F18F01', alpha=0.8)
+
+        # Formatting
+        ax.set_title(f'{ticker} Stock Price - Last 90 Days', fontsize=14, fontweight='bold')
+        ax.set_xlabel('Date', fontsize=12)
+        ax.set_ylabel('Price ($)', fontsize=12)
+        ax.legend(loc='best', fontsize=10)
+        ax.grid(True, alpha=0.3)
+
+        # Format x-axis dates
+        ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))
+        ax.xaxis.set_major_locator(mdates.MonthLocator())
+        plt.xticks(rotation=45)
+
+        # Tight layout to prevent label cutoff
+        plt.tight_layout()
+
+        # Save to BytesIO buffer
+        buf = io.BytesIO()
+        plt.savefig(buf, format='png', dpi=150, bbox_inches='tight')
+        buf.seek(0)
+        plt.close(fig)
+
+        return buf
+
+    except Exception as e:
+        print(f"Error generating stock price chart: {e}")
+        return None
+
+
+def generate_volume_chart(ticker: str, analysis_date: str) -> Optional[io.BytesIO]:
+    """
+    Generate a trading volume chart.
+
+    Args:
+        ticker: Stock ticker symbol
+        analysis_date: Analysis date string (YYYY-MM-DD)
+
+    Returns:
+        BytesIO buffer containing the chart image, or None if generation fails
+    """
+    try:
+        import matplotlib.pyplot as plt
+        import matplotlib.dates as mdates
+        import yfinance as yf
+        from datetime import datetime, timedelta
+    except ImportError:
+        return None
+
+    try:
+        # Parse the analysis date
+        end_date = datetime.strptime(analysis_date, '%Y-%m-%d')
+        start_date = end_date - timedelta(days=90)
+
+        # Fetch stock data
+        stock = yf.Ticker(ticker)
+        df = stock.history(start=start_date.strftime('%Y-%m-%d'),
+                          end=end_date.strftime('%Y-%m-%d'))
+
+        if df.empty:
+            return None
+
+        # Create the figure
+        fig, ax = plt.subplots(figsize=(10, 4))
+
+        # Plot volume bars
+        colors = ['green' if close >= open_ else 'red'
+                 for close, open_ in zip(df['Close'], df['Open'])]
+        ax.bar(df.index, df['Volume'], color=colors, alpha=0.6)
+
+        # Add average volume line
+        avg_volume = df['Volume'].mean()
+        ax.axhline(y=avg_volume, color='blue', linestyle='--',
+                  linewidth=1.5, label=f'Avg Volume: {avg_volume:,.0f}', alpha=0.7)
+
+        # Formatting
+        ax.set_title(f'{ticker} Trading Volume - Last 90 Days', fontsize=14, fontweight='bold')
+        ax.set_xlabel('Date', fontsize=12)
+        ax.set_ylabel('Volume', fontsize=12)
+        ax.legend(loc='best', fontsize=10)
+        ax.grid(True, alpha=0.3, axis='y')
+
+        # Format y-axis to show volume in millions
+        ax.yaxis.set_major_formatter(plt.FuncFormatter(lambda x, p: f'{x/1e6:.1f}M'))
+
+        # Format x-axis dates
+        ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))
+        ax.xaxis.set_major_locator(mdates.MonthLocator())
+        plt.xticks(rotation=45)
+
+        plt.tight_layout()
+
+        # Save to BytesIO buffer
+        buf = io.BytesIO()
+        plt.savefig(buf, format='png', dpi=150, bbox_inches='tight')
+        buf.seek(0)
+        plt.close(fig)
+
+        return buf
+
+    except Exception as e:
+        print(f"Error generating volume chart: {e}")
+        return None
+
+
+def generate_technical_indicators_chart(ticker: str, analysis_date: str) -> Optional[io.BytesIO]:
+    """
+    Generate a chart showing RSI and MACD technical indicators.
+
+    Args:
+        ticker: Stock ticker symbol
+        analysis_date: Analysis date string (YYYY-MM-DD)
+
+    Returns:
+        BytesIO buffer containing the chart image, or None if generation fails
+    """
+    try:
+        import matplotlib.pyplot as plt
+        import matplotlib.dates as mdates
+        import yfinance as yf
+        import pandas as pd
+        from datetime import datetime, timedelta
+    except ImportError:
+        return None
+
+    try:
+        # Parse the analysis date
+        end_date = datetime.strptime(analysis_date, '%Y-%m-%d')
+        start_date = end_date - timedelta(days=90)
+
+        # Fetch stock data
+        stock = yf.Ticker(ticker)
+        df = stock.history(start=start_date.strftime('%Y-%m-%d'),
+                          end=end_date.strftime('%Y-%m-%d'))
+
+        if df.empty:
+            return None
+
+        # Calculate RSI
+        delta = df['Close'].diff()
+        gain = (delta.where(delta > 0, 0)).rolling(window=14).mean()
+        loss = (-delta.where(delta < 0, 0)).rolling(window=14).mean()
+        rs = gain / loss
+        df['RSI'] = 100 - (100 / (1 + rs))
+
+        # Calculate MACD
+        exp1 = df['Close'].ewm(span=12, adjust=False).mean()
+        exp2 = df['Close'].ewm(span=26, adjust=False).mean()
+        df['MACD'] = exp1 - exp2
+        df['Signal'] = df['MACD'].ewm(span=9, adjust=False).mean()
+
+        # Create subplots
+        fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(10, 8), sharex=True)
+
+        # RSI plot
+        ax1.plot(df.index, df['RSI'], label='RSI', linewidth=2, color='#2E86AB')
+        ax1.axhline(y=70, color='red', linestyle='--', linewidth=1, alpha=0.7, label='Overbought (70)')
+        ax1.axhline(y=30, color='green', linestyle='--', linewidth=1, alpha=0.7, label='Oversold (30)')
+        ax1.fill_between(df.index, 30, 70, alpha=0.1, color='gray')
+        ax1.set_ylabel('RSI', fontsize=12)
+        ax1.set_title(f'{ticker} Technical Indicators', fontsize=14, fontweight='bold')
+        ax1.legend(loc='best', fontsize=10)
+        ax1.grid(True, alpha=0.3)
+        ax1.set_ylim(0, 100)
+
+        # MACD plot
+        ax2.plot(df.index, df['MACD'], label='MACD', linewidth=2, color='#2E86AB')
+        ax2.plot(df.index, df['Signal'], label='Signal', linewidth=2, color='#F18F01')
+        ax2.bar(df.index, df['MACD'] - df['Signal'], label='Histogram',
+                color='gray', alpha=0.3)
+        ax2.axhline(y=0, color='black', linestyle='-', linewidth=0.5)
+        ax2.set_xlabel('Date', fontsize=12)
+        ax2.set_ylabel('MACD', fontsize=12)
+        ax2.legend(loc='best', fontsize=10)
+        ax2.grid(True, alpha=0.3)
+
+        # Format x-axis dates
+        ax2.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))
+        ax2.xaxis.set_major_locator(mdates.MonthLocator())
+        plt.xticks(rotation=45)
+
+        plt.tight_layout()
+
+        # Save to BytesIO buffer
+        buf = io.BytesIO()
+        plt.savefig(buf, format='png', dpi=150, bbox_inches='tight')
+        buf.seek(0)
+        plt.close(fig)
+
+        return buf
+
+    except Exception as e:
+        print(f"Error generating technical indicators chart: {e}")
+        return None
diff --git a/cli/main.py b/cli/main.py
index 2e06d50c..571575a0 100644
--- a/cli/main.py
+++ b/cli/main.py
@@ -28,6 +28,7 @@ from tradingagents.graph.trading_graph import TradingAgentsGraph
 from tradingagents.default_config import DEFAULT_CONFIG
 from cli.models import AnalystType
 from cli.utils import *
+from cli.pdf_generator import generate_pdf_report
 
 console = Console()
 
@@ -1099,6 +1100,23 @@ def run_analysis():
 
         update_display(layout)
 
+    # Generate PDF report after the Live display context ends
+    try:
+        console.print("\n[bold cyan]Generating PDF report...[/bold cyan]")
+        pdf_path = generate_pdf_report(
+            final_state,
+            selections["ticker"],
+            selections["analysis_date"],
+            results_dir
+        )
+        console.print(f"[bold green]PDF report saved to:[/bold green] {pdf_path}")
+    except ImportError as e:
+        console.print(f"[yellow]Warning: {e}[/yellow]")
+        console.print("[yellow]PDF generation skipped. Install reportlab to enable PDF reports:[/yellow]")
+        console.print("[dim]pip install reportlab[/dim]")
+    except Exception as e:
+        console.print(f"[red]Error generating PDF report: {e}[/red]")
+
 
 @app.command()
 def analyze():
diff --git a/cli/pdf_generator.py b/cli/pdf_generator.py
new file mode 100644
index 00000000..1f4c8197
--- /dev/null
+++ b/cli/pdf_generator.py
@@ -0,0 +1,269 @@
+"""PDF report generator for TradingAgents analysis results."""
+import datetime
+import re
+from pathlib import Path
+from typing import Dict, Any
+import io
+from cli.chart_generator import (
+    generate_stock_price_chart,
+    generate_volume_chart,
+    generate_technical_indicators_chart
+)
+
+
+def generate_pdf_report(
+    final_state: Dict[str, Any],
+    ticker: str,
+    analysis_date: str,
+    output_path: Path,
+) -> Path:
+    """
+    Generate a comprehensive PDF report from the analysis results.
+
+    Args:
+        final_state: The final state dictionary containing all analysis results
+        ticker: The stock ticker symbol
+        analysis_date: The analysis date
+        output_path: Path where the PDF should be saved
+
+    Returns:
+        Path to the generated PDF file
+    """
+    try:
+        from reportlab.lib.pagesizes import letter, A4
+        from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle
+        from reportlab.lib.units import inch
+        from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer, PageBreak
+        from reportlab.platypus import Table, TableStyle, Image
+        from reportlab.lib import colors
+        from reportlab.lib.enums import TA_CENTER, TA_LEFT, TA_JUSTIFY
+    except ImportError:
+        raise ImportError(
+            "reportlab is required for PDF generation. "
+            "Install it with: pip install reportlab"
+        )
+
+    # Create the PDF document
+    pdf_file = output_path / f"{ticker}_{analysis_date}_analysis_report.pdf"
+    doc = SimpleDocTemplate(
+        str(pdf_file),
+        pagesize=letter,
+        rightMargin=72,
+        leftMargin=72,
+        topMargin=72,
+        bottomMargin=18,
+    )
+
+    # Container for the 'Flowable' objects
+    elements = []
+
+    # Define styles
+    styles = getSampleStyleSheet()
+    styles.add(ParagraphStyle(
+        name='CustomTitle',
+        parent=styles['Heading1'],
+        fontSize=24,
+        textColor=colors.HexColor('#1a1a1a'),
+        spaceAfter=30,
+        alignment=TA_CENTER,
+    ))
+    styles.add(ParagraphStyle(
+        name='CustomHeading1',
+        parent=styles['Heading1'],
+        fontSize=18,
+        textColor=colors.HexColor('#2c3e50'),
+        spaceAfter=12,
+        spaceBefore=12,
+    ))
+    styles.add(ParagraphStyle(
+        name='CustomHeading2',
+        parent=styles['Heading2'],
+        fontSize=14,
+        textColor=colors.HexColor('#34495e'),
+        spaceAfter=10,
+        spaceBefore=10,
+    ))
+    styles.add(ParagraphStyle(
+        name='CustomBody',
+        parent=styles['BodyText'],
+        fontSize=10,
+        alignment=TA_JUSTIFY,
+        spaceAfter=12,
+    ))
+
+    # Title Page
+    title = Paragraph(
+        f"TradingAgents Analysis Report<br/>{ticker}",
+        styles['CustomTitle']
+    )
+    elements.append(title)
+    elements.append(Spacer(1, 12))
+
+    # Metadata table
+    metadata = [
+        ['Analysis Date:', analysis_date],
+        ['Report Generated:', datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')],
+        ['Ticker Symbol:', ticker],
+    ]
+
+    t = Table(metadata, colWidths=[2*inch, 4*inch])
+    t.setStyle(TableStyle([
+        ('ALIGN', (0, 0), (-1, -1), 'LEFT'),
+        ('FONTNAME', (0, 0), (0, -1), 'Helvetica-Bold'),
+        ('FONTSIZE', (0, 0), (-1, -1), 10),
+        ('BOTTOMPADDING', (0, 0), (-1, -1), 6),
+        ('TOPPADDING', (0, 0), (-1, -1), 6),
+    ]))
+    elements.append(t)
+    elements.append(Spacer(1, 30))
+
+    # Generate and add charts
+    elements.append(PageBreak())
+    elements.append(Paragraph('Market Data Visualizations', styles['CustomHeading1']))
+    elements.append(Spacer(1, 12))
+
+    # Stock price chart
+    print("Generating stock price chart...")
+    price_chart = generate_stock_price_chart(ticker, analysis_date)
+    if price_chart:
+        img = Image(price_chart, width=6*inch, height=3.6*inch)
+        elements.append(img)
+        elements.append(Spacer(1, 20))
+
+    # Volume chart
+    print("Generating volume chart...")
+    volume_chart = generate_volume_chart(ticker, analysis_date)
+    if volume_chart:
+        img = Image(volume_chart, width=6*inch, height=2.4*inch)
+        elements.append(img)
+        elements.append(Spacer(1, 20))
+
+    # Technical indicators chart
+    print("Generating technical indicators chart...")
+    tech_chart = generate_technical_indicators_chart(ticker, analysis_date)
+    if tech_chart:
+        img = Image(tech_chart, width=6*inch, height=4.8*inch)
+        elements.append(img)
+        elements.append(Spacer(1, 20))
+
+    # Helper function to clean and escape text for PDF
+    def clean_text(text: str) -> str:
+        """Clean text and properly escape for reportlab."""
+        # Remove markdown headers
+        text = re.sub(r'^#{1,6}\s+', '', text, flags=re.MULTILINE)
+
+        # Escape special XML/HTML characters first
+        text = text.replace('&', '&amp;')
+        text = text.replace('<', '&lt;')
+        text = text.replace('>', '&gt;')
+
+        # Now we can safely add our formatting tags
+        # Convert markdown bold (**text** or __text__) to HTML bold
+        text = re.sub(r'\*\*(.+?)\*\*', r'<b>\1</b>', text)
+        text = re.sub(r'__(.+?)__', r'<b>\1</b>', text)
+
+        # Convert markdown italic (*text* or _text_) to HTML italic
+        # Be careful not to match ** or __
+        text = re.sub(r'(?<!\*)\*(?!\*)(.+?)(?<!\*)\*(?!\*)', r'<i>\1</i>', text)
+        text = re.sub(r'(?<!_)_(?!_)(.+?)(?<!_)_(?!_)', r'<i>\1</i>', text)
+
+        # Remove any remaining problematic characters
+        text = text.replace('\r', '')
+
+        return text
+
+    # Helper function to add section
+    def add_section(title: str, content: str):
+        if content:
+            elements.append(Paragraph(title, styles['CustomHeading1']))
+            elements.append(Spacer(1, 12))
+
+            # Clean the content
+            content = clean_text(content)
+
+            # Split content into paragraphs
+            paragraphs = content.split('\n\n')
+            for para in paragraphs:
+                para = para.strip()
+                if para:
+                    # Replace single newlines with spaces, but preserve structure
+                    para = para.replace('\n', ' ')
+                    # Clean up multiple spaces
+                    para = re.sub(r'\s+', ' ', para)
+                    try:
+                        elements.append(Paragraph(para, styles['CustomBody']))
+                    except Exception as e:
+                        # If there's still an error, add as plain text
+                        print(f"Warning: Could not parse paragraph, adding as plain text: {e}")
+                        elements.append(Paragraph(para.replace('<', '&lt;').replace('>', '&gt;'), styles['CustomBody']))
+            elements.append(Spacer(1, 20))
+
+    # I. Analyst Team Reports
+    elements.append(PageBreak())
+    elements.append(Paragraph('I. Analyst Team Reports', styles['CustomHeading1']))
+    elements.append(Spacer(1, 20))
+
+    if final_state.get('market_report'):
+        add_section('Market Analysis', final_state['market_report'])
+
+    if final_state.get('sentiment_report'):
+        add_section('Social Sentiment Analysis', final_state['sentiment_report'])
+
+    if final_state.get('news_report'):
+        add_section('News Analysis', final_state['news_report'])
+
+    if final_state.get('fundamentals_report'):
+        add_section('Fundamentals Analysis', final_state['fundamentals_report'])
+
+    # II. Research Team Reports
+    if final_state.get('investment_debate_state'):
+        elements.append(PageBreak())
+        elements.append(Paragraph('II. Research Team Decision', styles['CustomHeading1']))
+        elements.append(Spacer(1, 20))
+
+        debate_state = final_state['investment_debate_state']
+
+        if debate_state.get('bull_history'):
+            add_section('Bull Researcher Analysis', debate_state['bull_history'])
+
+        if debate_state.get('bear_history'):
+            add_section('Bear Researcher Analysis', debate_state['bear_history'])
+
+        if debate_state.get('judge_decision'):
+            add_section('Research Manager Decision', debate_state['judge_decision'])
+
+    # III. Trading Team Reports
+    if final_state.get('trader_investment_plan'):
+        elements.append(PageBreak())
+        elements.append(Paragraph('III. Trading Team Plan', styles['CustomHeading1']))
+        elements.append(Spacer(1, 20))
+        add_section('Trader Plan', final_state['trader_investment_plan'])
+
+    # IV. Risk Management Team Reports
+    if final_state.get('risk_debate_state'):
+        elements.append(PageBreak())
+        elements.append(Paragraph('IV. Risk Management Team Decision', styles['CustomHeading1']))
+        elements.append(Spacer(1, 20))
+
+        risk_state = final_state['risk_debate_state']
+
+        if risk_state.get('risky_history'):
+            add_section('Aggressive Analyst Analysis', risk_state['risky_history'])
+
+        if risk_state.get('safe_history'):
+            add_section('Conservative Analyst Analysis', risk_state['safe_history'])
+
+        if risk_state.get('neutral_history'):
+            add_section('Neutral Analyst Analysis', risk_state['neutral_history'])
+
+        # V. Portfolio Manager Decision
+        if risk_state.get('judge_decision'):
+            elements.append(PageBreak())
+            elements.append(Paragraph('V. Portfolio Manager Decision', styles['CustomHeading1']))
+            elements.append(Spacer(1, 20))
+            add_section('Final Decision', risk_state['judge_decision'])
+
+    # Build PDF
+    doc.build(elements)
+
+    return pdf_file
diff --git a/requirements.txt b/requirements.txt
index a6154cd2..a8d7c544 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -24,3 +24,5 @@ rich
 questionary
 langchain_anthropic
 langchain-google-genai
+reportlab
+matplotlib