stock-evaluator-v3

name	stock-evaluator-v3
description	Comprehensive evaluation of potential stock investments combining valuation analysis, fundamental research, technical assessment, and clear buy/hold/sell recommendations. Use when the user asks about buying a stock, evaluating investment opportunities, analyzing watchlist candidates, or requests stock recommendations. Provides specific entry prices, position sizing, and conviction ratings.

Stock Evaluator (Enhanced)

⚠️ CRITICAL: MANDATORY DELIVERABLES CHECKLIST

Every analysis MUST include ALL of these:

• ☐ Technical Analysis (price action, indicators, key levels, Ichimoku Cloud)
• ☐ Fundamental Analysis (business, financials, competitive position)
• ☐ Advanced Financial Metrics (F-Score, Z-Score, M-Score, Max Drawdown, Value Trap Score)
• ☐ Investor Persona Scores (8 legendary investor frameworks)
• ☐ Valuation Assessment (multiple methods with margin of safety)
• ☐ Bull vs. Bear Case (both sides with balance assessment)
• ☐ Clear Recommendation (BUY / HOLD / SELL with conviction rating)
• ☐ Alternative Candidates (if SELL: provide 3-5 better alternatives)
• ☐ Enhanced Quant-Style Dashboard (React dashboard with 60+ metrics, Ichimoku, investor personas, TOP NEWS, and key notes)

If you cannot complete any item, STOP and ask for clarification.

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⚠️ CRITICAL: DATA INTEGRITY RULES

ZERO FABRICATION POLICY

NEVER fabricate, estimate, or hallucinate ANY numeric data point. Every metric in the dashboard MUST come from:

1. A web search result with a cited source
2. Company filings (10-K, 10-Q, earnings reports)
3. Official financial data providers

If data cannot be found → Use "N/A" or "--"

MANDATORY WEB SEARCHES (minimum per analysis)

You MUST perform these searches before populating the dashboard:

Search #	Query Template	Data Retrieved
1	"[TICKER] stock price market cap P/E ratio"	Price, Market Cap, P/E
2	"[TICKER] ROE ROA profit margin 2024 annual report"	Financial ratios
3	"[TICKER] revenue growth earnings growth FY2024"	Growth rates (REPORTED)
4	"[TICKER] Piotroski F-Score"	F-Score (or calculate)
5	"[TICKER] insider trading SEC Form 4 2025"	Insider buys/sells
6	"[TICKER] short interest percentage float"	Short interest
7	"[TICKER] RSI MACD 50-day 200-day moving average beta volatility"	Technical indicators
8	"[TICKER] analyst price target consensus"	Analyst targets

DATA SOURCE HIERARCHY

Use sources in this priority order:

1. Official company filings (SEC EDGAR, company investor relations)
2. Exchange data (NYSE, NASDAQ, LSE official)
3. Verified financial data (Yahoo Finance, Google Finance, MarketWatch)
4. SEC Form 4 (for insider trading ONLY)
5. FINRA/exchange (for short interest ONLY)

PROHIBITED

• Using training knowledge for ANY specific current numbers
• Analyst reports (per user preference)
• Estimates without sourcing
• "Common knowledge" assumptions

HANDLING UNAVAILABLE DATA

Situation	Action	Display
Metric not found after searching	Display "N/A"	value: "N/A"
Data is outdated (>1 year old)	Note the date	value: "15.2% (2023)"
Conflicting sources	Use most authoritative	Note in analysis
Calculated metric (F-Score)	Show calculation	Explain in text
Insider data unavailable	Show "N/A"	insBuys: "N/A"

CRITICAL: Zero means "zero occurred" - NEVER substitute zeros for missing data.

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STANDARDIZED METRIC LABELS

Use these EXACT labels in the dashboard (matches reference screenshots):

Row 1: PRICE & VALUATION | FINANCIAL PERFORMANCE

Label	Notes
Price:	$XX.XX or €XX.XX
Market Cap:	$XXB or €XXB
Trailing P/E:	XX.XX
Forward P/E:	XX.XX
Subsector P/E:	XX.XX or N/A
PEG (1Y):	X.XX with benchmark (<1)
ROE:	XX.XX% with benchmark (>20%)
ROA:	XX.XX% with benchmark (>10%)
Profit Margin:	XX.XX% with benchmark (>20%)
Operative Margin:	XX.XX% with benchmark (>20%) - NOTE: "Operative" not "Operating"
Gross Margin:	XX.XX% with benchmark (>40%)
ROIC:	XX.X% with benchmark (>15%)

Row 2: GROWTH METRICS | RISK INDICATORS

Label	Notes
Revenue (YoY):	XX.XX% with benchmark (>10%) - REPORTED only
Earning (YoY):	XX.XX% with benchmark (>0%) - REPORTED only
EPS (TTM):	$X.XX
Forward EPS:	$X.XX
Growth Rates:	Capped: X.X% / Uncapped: X.X%
Analyst Target:	$XX.XX
CRS (0-1):	X.XX with benchmark (Medium)
Debt/Equity (mrq):	X.XX with benchmark (0.5-1)
Piotroski F:	X with benchmark (≥7)
Altman Z:	X.XX with benchmark (>3)
Beneish M:	X.XX with benchmark (<-1.78)
Value Trap:	XX (Label)

Row 3: LIQUIDITY & FREE CASH FLOW | INSIDER & SENTIMENT & CLASS

Label	Notes
Current Ratio:	X.XX with benchmark (1-2)
Cash:	$X.XB
Debt:	$X.XB or N/A
FCF Growth 5Y:	XX.X% with benchmark (>5%)
FCF Yield:	X.XX% with benchmark (>4%)
FCF Margin:	XX.XX% with benchmark (>15%)
Payout Ratio:	XX.XX% with benchmark (<50%)
Buys (12M):	X - from SEC Form 4 or N/A
Sells (12M):	X - from SEC Form 4 or N/A
Net Shares (12M):	+/-XXK - from SEC Form 4 or N/A
Short Int (%):	X.X%
Sentiment / Articles:	+X.XXX / XX (Positive/Negative)
Stock: [Type] + Div Yield:	Combined: "Stock: Growth" + "Div Yield: X.XX%"
Sector/Industry:	Combined: "Sector / Industry"

Row 4: QUALITY SCORES | MOAT & OTHER

Label	Notes
CQVS:	XX.XX with benchmark range
Label:	Strong/Moderate/Weak
Valuation:	XX.XX
Quality:	XX.XX
Strength:	XX.XX
Integrity:	XX.XX
Buffett Moat:	X with benchmark (4-7)
Greenblatt (MF):	EY: X.X% / ROC: X.X% or N/A
Beta: + Vol 1Y:	Combined: "Beta: X.XX" + "Vol 1Y: XX.X%"
Earnings Predict.:	XX.X% with benchmark (>80%)
Drawdown (5Y):	-XX.X% with label (Low/Mid/High)
Completeness: + Data Quality:	Combined: "XX.X%" + "High/Medium/Low"

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STANDARDIZED BENCHMARKS (Single Source of Truth)

Use these EXACT thresholds for color coding:

Metric	Green (Good)	Yellow (Neutral)	Red (Warning)
ROE	>20%	10-20%	<10%
ROA	>10%	5-10%	<5%
Profit Margin	>20%	10-20%	<10%
Operative Margin	>20%	10-20%	<10%
Gross Margin	>40%	25-40%	<25%
ROIC	>15%	8-15%	<8%
Debt/Equity	<1	1-2	>2
Current Ratio	1-2	0.5-1 or 2-3	<0.5 or >3
Piotroski F	≥7	4-6	≤3
Altman Z	>2.99	1.81-2.99	<1.81
Beneish M	<-2.22	-2.22 to -1.78	>-1.78
PEG (1Y)	<1	1-2	>2
RSI (14)	30-50	50-70	>70 or <30
Short Interest	<5%	5-10%	>10%
FCF Yield	>5%	2-5%	<2%
FCF Margin	>15%	10-15%	<10%
Dividend Yield	>2%	1-2%	<1% or >8%
Value Trap	0-39	40-59	60-100
Max Drawdown	>-30%	-30% to -50%	<-50%
Revenue Growth	>10%	0-10%	<0%
Earnings Growth

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Overview

This skill provides institutional-grade evaluation of potential stock investments. Unlike portfolio analysis which reviews existing positions, this skill evaluates stocks you're considering buying or deciding whether to purchase.

The evaluation answers:

• Should I buy this stock?
• At what price should I enter?
• How much should I allocate?
• What's my upside and downside?
• When should I sell?

Default Currency: € (Euro)

All monetary values in the dashboard should be displayed in Euro (€) as the default currency:

• Price: €42.13
• Market Cap: €78.3B
• Analyst Target: €56.45
• Entry/Stop/Target prices: €38, €35, €56
• EPS values: €1.39, €1.91

IMPORTANT: Use REPORTED Growth Rates

For the dashboard metrics "Rev Growth" and "Earn Growth":

• USE REPORTED GROWTH - not underlying, adjusted, or organic figures
• Reported figures reflect actual GAAP/IFRS numbers including FX, acquisitions, disposals
• This provides a more accurate picture of what investors actually received
• Example: If underlying growth is 7% but reported is 2.2%, use 2.2%
• Same for earnings: Use reported EPS growth, not adjusted EPS growth

Core Purpose

Stock Evaluator is for:

• ✅ Evaluating potential investments BEFORE buying
• ✅ Analyzing watchlist candidates
• ✅ Getting buy/hold/sell recommendations with specific prices
• ✅ Comparing multiple investment opportunities
• ✅ Finding better alternatives to current consideration

NOT for:

• ❌ Reviewing existing portfolio positions (use Portfolio Analyst skill)
• ❌ General stock market questions
• ❌ Stock screening or discovery from scratch
• ❌ Options, derivatives, or crypto analysis

Evaluation Framework

Five Pillars of Stock Evaluation

1. Valuation Assessment

• Is the stock undervalued, fairly valued, or overvalued?
• Multiple valuation methods (DCF, relative, Peter Lynch, asset-based)
• Margin of safety requirement (15-30%)
• Fair value estimate with confidence range

2. Quality Analysis

• Business model strength and competitive moat
• Financial health and trends (5-10 year view)
• Management quality and capital allocation
• Industry position and competitive advantages

3. Timing Assessment

• Technical setup and entry points
• Near-term catalysts and events
• Market sentiment and positioning
• Optimal entry price range

4. Position Sizing

• Allocation recommendation (% of portfolio)
• Based on conviction, risk, and diversification
• Maximum allocation limits
• Risk-adjusted sizing

5. Conviction Rating

• Strong Buy: High conviction, clear undervaluation, low risk
• Buy: Good opportunity, reasonable valuation, moderate risk
• Hold: Fairly valued, no compelling reason to buy now
• Avoid: Overvalued, significant risks, or better alternatives exist

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Value Trap Indicator

What It Is

A Value Trap is when a stock appears undervalued (low P/E, low P/B) but is actually cheap for valid fundamental reasons. The stock keeps declining despite appearing "cheap."

Value Trap Score Calculation (0-100, LOWER = more genuine, HIGHER = more trap)

Components to evaluate (ADD points for trap indicators):

1. Price Momentum (25 points max)

• 6-month price change vs market: If underperforming by >20%, ADD 15-25 points
• 12-month price change: Sustained decline = ADD 10-20 points
• If price momentum is POSITIVE: ADD 0 points

2. Earnings Quality (25 points max)

• EPS trend (3 years): Declining = ADD 10-25 points
• Revenue trend: Declining = ADD 5-15 points
• Margin trend: Compressing = ADD 5-10 points
• If earnings quality is STRONG: ADD 0 points

3. Balance Sheet Health (25 points max)

• Debt levels increasing? ADD 5-15 points
• Cash flow negative or declining? ADD 10-20 points
• Working capital deteriorating? ADD 5-10 points
• If balance sheet is HEALTHY: ADD 0 points

4. Valuation Context (25 points max)

• Is low multiple justified by declining fundamentals? ADD 10-25 points
• Compare current fundamentals to when multiple was higher
• If fundamentals justify valuation: ADD 0 points

Scoring Formula

Value Trap Score = Momentum Penalty + Quality Penalty + Balance Sheet Penalty + Valuation Penalty

(Score ranges from 0 to 100, where 0 = definitely genuine value, 100 = definite value trap)

Score Interpretation

• 0-19: Genuine Value (likely undervalued, fundamentals intact) - GREEN
• 20-39: Probably Genuine (minor concerns, monitor) - LIGHT GREEN
• 40-59: Caution Zone (mixed signals, proceed carefully) - YELLOW
• 60-79: Likely Trap (multiple red flags) - ORANGE
• 80-100: Strong Trap Signal (avoid) - RED

Display Format

Value Trap: 21 (Genuine)

Color coding: green <40, yellow 40-60, red >60

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Investor Persona Scores

Score each stock against 8 famous investor philosophies (0-10 scale). This helps users understand what type of investor the stock suits.

1. Warren Buffett Score

Based on "The Warren Buffett Way" - seeks durable competitive advantages

Key metrics weighted:

• ROE (>20%): 2 points
• Profit margin (>15%): 2 points
• Free cash flow positive & growing: 2 points
• Moat strength (brand, pricing power): 2 points
• Predictable earnings: 2 points

Buffett likes: Predictable businesses, pricing power, low capex needs, consistent profitability

2. Charlie Munger Score

Based on "Poor Charlie's Almanack" - mental latticework, inversion thinking

Focus on: What could go WRONG (inversion principle)

Scoring: Start at 10, subtract penalties:

• High debt (D/E > 2): -3 points
• Volatile earnings: -2 points
• Poor management history: -2 points
• No competitive moat: -2 points
• Accounting red flags: -3 points

3. Ray Dalio Score

Based on "Principles" - All-Weather portfolio, economic machine understanding

Key metrics:

• D/E ratio < 1: 2 points
• Beta < 1: 2 points
• Stable margins across cycles: 2 points
• Low earnings volatility: 2 points
• Recession resistance history: 2 points

Dalio likes: Deleveraging plays, operational efficiency, cycle resilience

4. Peter Lynch Score

Based on "One Up on Wall Street" - GARP (Growth at Reasonable Price)

Primary metric: PEG Ratio (P/E ÷ Growth Rate)

• PEG < 0.5: 10 points
• PEG 0.5-1.0: 8 points
• PEG 1.0-1.5: 6 points
• PEG 1.5-2.0: 4 points
• PEG > 2.0: 2 points

Adjustment factors:

• +1 if earnings growing consistently
• +1 if business easy to understand
• -1 if declining industry

5. Benjamin Graham Score

Based on "The Intelligent Investor" - Margin of Safety

Graham criteria (2 points each, max 10):

• P/E < 15
• P/B < 1.5
• Current ratio > 2
• Positive earnings 10 years
• Dividend paid 20+ years

6. Joel Greenblatt Score

Based on "The Little Book That Beats the Market" - Magic Formula

Combines two rankings:

• Earnings Yield (EBIT/EV): Higher = better
• Return on Capital (EBIT/Net Fixed Assets + Working Capital): Higher = better

Scoring: Combined rank in top 10% = 10 points, scaled down

7. John Templeton Score

Based on contrarian, global value investing

Key factors:

• Trading at multi-year lows: +3 points
• Out of favor with analysts: +2 points
• Strong fundamentals despite pessimism: +3 points
• Global perspective (non-US opportunity): +2 points

8. George Soros Score

Based on "The Alchemy of Finance" - Reflexivity

Key factors:

• Momentum and trend strength: 3 points
• Macro tailwinds: 3 points
• Market perception shifting: 2 points
• Inflection point catalyst: 2 points

Soros likes: Macro plays, reflexive situations, trend participation

Display Format

Show 8 badges around radar chart with scores and color coding:

• Green (7-10): Strong fit
• Yellow (4-6.9): Moderate fit
• Red (0-3.9): Poor fit

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Enhanced Technical Analysis

Ichimoku Cloud Analysis

Components to Calculate:

• Tenkan-sen (Conversion Line): (9-period high + 9-period low) / 2
• Kijun-sen (Base Line): (26-period high + 26-period low) / 2
• Senkou Span A: (Tenkan-sen + Kijun-sen) / 2, plotted 26 periods ahead
• Senkou Span B: (52-period high + 52-period low) / 2, plotted 26 periods ahead
• Chikou Span (Lagging Span): Current close plotted 26 periods back

Cloud (Kumo): Area between Senkou Span A and B

Signals to Identify and Display:

• TK Bullish Cross: Tenkan-sen crosses above Kijun-sen (bullish) - mark with ◆
• TK Bearish Cross: Tenkan-sen crosses below Kijun-sen (bearish) - mark with ◆
• Kumo Twist Bullish: Cloud changes from red to green - mark with ◆
• Kumo Twist Bearish: Cloud changes from green to red - mark with ◆
• Price vs Cloud: Above cloud (bullish), Below cloud (bearish), In cloud (neutral)

Dual PEG Ratios

• PEG (1Y): P/E ÷ 1-Year Forward Growth Estimate
• PEG (5Y): P/E ÷ 5-Year Historical Growth Rate
• Both provide different perspectives on growth valuation

FCF Margin

• Formula: Free Cash Flow / Revenue × 100
• Benchmark: >15% is excellent, >10% is good
• Shows cash generation efficiency relative to sales

News Sentiment & Short Interest

• News Sentiment: -1 to +1 scale based on recent article sentiment
• Short Interest: % of float sold short (>10% = high, <5% = low)
• Both indicate market sentiment and potential squeeze/reversal

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Fundamental Analysis Process

1. Business Understanding (Always First)

What to Analyze:

• What does the company do? (products, services, business model)
• Revenue sources and breakdown
• Target customers and markets
• Competitive advantages (moat sources)
• Market position and share
• Industry dynamics and trends

Management Evaluation:

• CEO background, tenure, track record
• CFO and key executives
• Capital allocation decisions (dividends, buybacks, acquisitions, R&D)
• Management compensation alignment
• Insider trading patterns (buying is bullish signal)
• Leadership quality from earnings calls and letters

Competitive Position:

• Market share and trends
• Key competitors (identify 3-5 direct peers)
• What differentiates this company?
• Sustainable competitive advantages?

2. Financial Analysis (5-10 Year View)

Research Process Order:

1. Latest 10-K first - Understand current business and recent results
2. Go back 5-10 years through historical 10-Ks - Understand evolution
3. Review last 2-3 years of 10-Qs - Current trajectory
4. Examine proxy statements - Governance and compensation

Key Metrics to Analyze:

Quality Benchmarks:

• ROE > 15% (return on equity)
• Profit Margin > 15%
• Gross Margin > 30%
• Debt < Annual Revenue
• Positive and growing Free Cash Flow
• Revenue growth over 5 years (inflation-adjusted)

Trends to Assess:

• Revenue growth trajectory (accelerating/stable/decelerating?)
• Margin expansion or contraction (why?)
• Cash flow consistency and quality
• Balance sheet strength (debt levels, liquidity)
• Return on invested capital (ROIC)
• Working capital management

Red Flags:

• Declining margins despite revenue growth
• Negative or inconsistent free cash flow
• Debt growing faster than cash generation
• Losing market share
• Chronic guidance misses
• Accounting irregularities

3. Competitive Moat Assessment

Moat Strength: Wide / Narrow / None

Evaluate Sources:

• Network effects: Product improves with more users?
• Brand loyalty: Pricing power from brand strength?
• Switching costs: Difficult/expensive to switch?
• Regulatory barriers: Licenses, patents, regulations?
• Cost advantages: Scale, technology, location?
• Intangible assets: Patents, trademarks, proprietary data?

Moat Durability:

• How long can advantages be sustained?
• What could erode the moat?
• Is moat strengthening or weakening?

Peer Comparison: Compare this company's moat vs. 3-5 direct competitors:

• Market share trends
• Profitability metrics (margins, ROE)
• Growth rates
• Financial strength

4. Advanced Financial Health Metrics

Beyond basic quality metrics, calculate these advanced scores for deeper insight:

Piotroski F-Score (Financial Strength)

Purpose: 9-point score measuring financial strength across profitability, leverage, and operating efficiency.

Scoring (0-9, higher is better):

Profitability (4 points):

• ROA > 0: +1
• Operating Cash Flow > 0: +1
• ROA improving YoY: +1
• Cash Flow from Operations > Net Income (quality of earnings): +1

Leverage/Liquidity (3 points):

• Long-term debt decreasing YoY: +1
• Current ratio improving YoY: +1
• No new shares issued in past year: +1

Operating Efficiency (2 points):

• Gross margin improving YoY: +1
• Asset turnover ratio improving YoY: +1

Interpretation:

• 8-9: Excellent financial health
• 6-7: Good financial health
• 4-5: Adequate financial health
• 0-3: Weak financial health

Altman Z-Score (Bankruptcy Risk)

Purpose: Predicts probability of bankruptcy within 2 years.

Formula (for public manufacturing companies): Z = 1.2(A) + 1.4(B) + 3.3(C) + 0.6(D) + 1.0(E)

Where:

• A = Working Capital / Total Assets
• B = Retained Earnings / Total Assets
• C = EBIT / Total Assets
• D = Market Cap / Total Liabilities
• E = Sales / Total Assets

Interpretation:

• Z > 2.99: Safe Zone (low bankruptcy risk)
• Z 1.81-2.99: Grey Zone (moderate risk)
• Z < 1.81: Distress Zone (high bankruptcy risk)

Note: Adjust for non-manufacturing companies (different coefficients).

Beneish M-Score (Earnings Manipulation Detection)

Purpose: Identifies likelihood of earnings manipulation.

Key Indicators (simplified approach):

• Days Sales Outstanding Index (increasing = warning)
• Gross Margin Index (declining = warning)
• Asset Quality Index (increasing = warning)
• Sales Growth Index (excessive growth = warning)
• Depreciation Index (declining = warning)
• SG&A Index (disproportionate change = warning)
• Leverage Index (increasing = warning)
• Total Accruals to Total Assets (high = warning)

Interpretation:

• M-Score > -1.78: Likely manipulator (RED FLAG)
• M-Score < -1.78: Unlikely manipulator (clean)

Practical Check (if full M-Score unavailable):

• Are accruals consistently high relative to cash flow?
• Is DSO rising faster than revenue?
• Are margins declining with revenue growth?
• Any accounting restatements or auditor changes?

Max Drawdown (5-Year)

Purpose: Measures largest peak-to-trough price decline.

Calculation:

• Identify highest price in past 5 years
• Find lowest subsequent price before recovery
• Max Drawdown % = (Low - High) / High × 100

Interpretation:

• 0-20%: Low volatility (defensive stock)
• 20-40%: Moderate volatility (typical stock)
• 40-60%: High volatility (cyclical/growth)
• >60%: Extreme volatility (speculative)

Consolidated Scores

Strength Score (0-100): Composite of:

• Financial metrics (F-Score contribution)
• Profitability (ROE, margins)
• Growth rates
• Market position

Integrity Score (0-100): Composite of:

• M-Score (earnings quality)
• Cash flow vs. earnings alignment
• Accounting practices
• Management transparency

Predictability Score (0-100): Composite of:

• Revenue consistency (low volatility)
• Earnings consistency
• Business model stability
• Cyclicality assessment

Data Quality Score (0-100):

• Completeness of financial data
• Recency of filings
• Auditor quality
• Disclosure transparency

5. Risk Analysis

Company-Specific Risks:

• Execution risk (can management deliver?)
• Competition risk (share loss, new entrants)
• Product concentration (single product dependency)
• Customer concentration (few large customers)
• Key person risk (CEO dependency)
• Financial distress risk (Z-Score assessment)
• Earnings quality risk (M-Score assessment)

Industry Risks:

• Disruption (technology or business model)
• Cyclicality (economic sensitivity)
• Regulation (policy changes)
• Commoditization (pricing power erosion)
• Structural decline (secular headwinds)

Macro Risks:

• Economic (recession, inflation, rates)
• Geopolitical (trade wars, conflicts)
• Currency (FX exposure)
• Market (valuation levels, sentiment)

Overall Risk Level: Low / Moderate / High

Consolidated Risk Score: (0-1 scale, lower is better)

• Incorporates: Z-Score, volatility, leverage, earnings quality
• <0.30: Low Risk
• 0.30-0.60: Moderate Risk

• 0.60: High Risk

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Valuation Assessment

Use multiple valuation methods - synthesize into fair value estimate.

Required Valuation Methods

1. DCF Analysis (Discounted Cash Flow)

• Project free cash flows (5-10 years)
• Apply appropriate discount rate (WACC)
• Calculate terminal value
• Include margin of safety: 15-30%
• Sensitivity analysis with different assumptions

2. Relative Valuation

• Compare to 3-5 direct peer companies
• Key multiples: P/E, EV/EBITDA, Price/Sales, Price/Book
• Adjust for growth differentials
• Consider industry-specific multiples
• Use both current and historical peer averages

3. Peter Lynch Fair Value

• Growth-at-reasonable-price framework
• Compare P/E to growth rate (PEG ratio)
• Fair value when P/E ≈ growth rate
• Adjust for quality factors

4. Asset-Based (When Applicable)

• For REITs, financials, asset-heavy companies
• Book value or replacement cost
• Net asset value calculations

Valuation Synthesis

Fair Value Estimate: €X.XX

Weight each method appropriately:

• DCF: 40% (if reliable cash flows)
• Relative: 30% (peer comparison)
• Peter Lynch: 30% (growth-adjusted)

Margin of Safety:

• Current Price vs. Fair Value: X% discount/premium
• Required: Minimum 15% margin of safety
• Adequate: 15-30% margin of safety
• Excellent: >30% margin of safety

Valuation Conclusion:

• UNDERVALUED: >15% below fair value (buy opportunity)
• FAIRLY VALUED: Within ±15% of fair value (hold)
• OVERVALUED: >15% above fair value (avoid/sell)

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Technical Analysis (Entry Timing)

Focus on identifying optimal entry points, not full technical analysis.

Key Technical Elements

1. Price Action (Last 30-60 Days)

• Current trend: Uptrend / Downtrend / Range-bound
• Recent price pattern
• Volume trends (increasing on rallies?)
• Momentum assessment

2. Key Levels

• Support levels: Where buying interest emerges
  • Primary support: €X.XX
  • Secondary support: €X.XX
• Resistance levels: Where selling pressure increases
  • Primary resistance: €X.XX
  • Secondary resistance: €X.XX

3. Technical Indicators

• RSI (Relative Strength Index):

  • 70 = Overbought (may pullback)

  • <30 = Oversold (potential bounce)
  • 40-60 = Neutral
• MACD (Moving Average Convergence Divergence):
  • Bullish crossover / Bearish crossover / Neutral
  • Momentum accelerating or decelerating?
• Moving Averages:
  • 50-day MA: €X.XX (price above/below?)
  • 200-day MA: €X.XX (trend indicator)

4. Entry Assessment

• Technical Setup: Bullish / Neutral / Bearish
• Optimal Entry: Wait for pullback to support / Buy at market / Wait for breakout
• Entry Price Range: €X.XX - €X.XX
• Avoid Above: €X.XX (poor risk/reward)

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Bull vs. Bear Case Analysis

MANDATORY: Every analysis must present both sides fairly.

Bull Case (Optimistic Scenario)

Potential Upside: +X% to €X.XX

1. [Key bull argument 1 with specific evidence]
2. [Key bull argument 2 with specific evidence]
3. [Key bull argument 3 with specific evidence]

For this to play out:

• [Required condition 1]
• [Required condition 2]

Bear Case (Pessimistic Scenario)

Potential Downside: -X% to €X.XX

1. [Key bear argument 1 with specific evidence]
2. [Key bear argument 2 with specific evidence]
3. [Key bear argument 3 with specific evidence]

This happens if:

• [Risk trigger 1]
• [Risk trigger 2]

Balance Assessment

Which case is more probable: [Bull / Bear / Balanced]

[Explanation of why one case is more likely, considering:

• Quality of evidence for each side
• Historical precedent
• Management track record
• Industry dynamics
• Current valuation]

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Investment Recommendation Structure

BUY Recommendation Criteria

• Fair value >15% above current price (adequate margin of safety)
• Strong or improving fundamentals
• Reasonable or bullish technical setup
• Identifiable catalysts
• Acceptable risk level
• Conviction: Strong Buy or Buy

HOLD Recommendation Criteria

• Fair value within ±15% of current price
• Stable fundamentals, no compelling catalyst
• Better opportunities may exist elsewhere
• Wait for better entry price
• Conviction: Hold

SELL/AVOID Recommendation Criteria

• Fair value <-15% below current price (overvalued)
• Deteriorating fundamentals
• Significant risks
• Better alternatives available
• Must provide 3-5 alternative candidates
• Conviction: Avoid

---

Position Sizing Framework

Allocation recommendation based on:

Conviction + Risk = Position Size

Strong Buy (High Conviction, Low Risk):

• Position size: 5-8% of portfolio
• Maximum: 10%

Buy (Moderate Conviction, Moderate Risk):

• Position size: 3-5% of portfolio
• Maximum: 7%

Speculative/High Risk:

• Position size: 1-3% of portfolio
• Maximum: 5%

Considerations:

• Diversification needs (avoid sector concentration)
• Correlation with existing holdings
• Overall portfolio risk
• Liquidity requirements
• User's risk tolerance (from project context)

---

Entry and Exit Strategy

Entry Strategy

NO scale-in strategies - recommend single entry approach:

If BUY:

• Ideal Entry Price: €X.XX - €X.XX (optimal range)
• Maximum Buy Price: €X.XX (above this, risk/reward unfavorable)
• Approach:
  • "Buy now at market" (if currently at good price)
  • "Wait for pullback to €X.XX support" (if extended)
  • "Buy on break above €X.XX" (if breakout setup)
  • "Don't buy above €X.XX" (if overvalued)

Exit Strategy

Price Target (12-month): €X.XX (+X% upside)

• Conservative: €X.XX
• Base case: €X.XX
• Optimistic: €X.XX

Stop Loss: €X.XX (-X% maximum loss)

• Technical stop: Below key support
• Fundamental stop: If thesis breaks

Sell If (Thesis-Breaking Conditions):

1. [Specific fundamental deterioration]
2. [Specific competitive threat]
3. [Specific valuation threshold]

Hold Duration:

• Expected timeframe: [6-12 months / 1-3 years / 3-5+ years]
• Based on investment type (swing trade vs long-term hold)

---

Catalyst Identification

Identify specific events that could drive stock performance.

Near-Term (0-6 months):

• Upcoming earnings: [Date]
• Product launches: [Event]
• Regulatory decisions: [Expected timing]
• Industry events: [Conference, data release]

Medium-Term (6-18 months):

• Market expansion plans
• New product cycles
• Margin expansion initiatives
• Strategic partnerships

Long-Term (18+ months):

• Structural industry trends
• Market share gains
• Technological leadership
• Business model evolution

---

Key Analytical Constraints

Critical Principles:

1. No Press/News for Fundamental Analysis

   • Use company filings only (10-K, 10-Q, 8-K, proxy)
   • Use earnings call transcripts
   • Do NOT rely on news articles or press releases
   • Exception: News for recent developments, but verify in filings

2. Magnitude Over Precision

   • Focus on stocks with good margin of safety (>15%)
   • Don't need perfect forecasts
   • Better to be approximately right than precisely wrong
   • Conservative assumptions better than optimistic

3. Long-Term View

   • Analyze 5-10 year trends, not just recent quarters
   • Temporary setbacks vs. structural problems
   • Sustainable competitive advantages matter most
   • Short-term noise vs. long-term signal

4. Compare Apples to Apples

   • Benchmark against 3-5 direct competitors
   • Not just broad market indices
   • Industry-specific metrics and norms
   • Adjust for company size and maturity

5. Intellectual Honesty

   • Acknowledge limitations and unknowns
   • Present both bull and bear cases fairly
   • Say "I don't know" when appropriate
   • Update views when evidence changes

---

Output Template

# [SYMBOL] - [Company Name] Evaluation

## ⚠️ DELIVERABLES CHECKLIST ✓
☑ Technical Analysis Complete
☑ Fundamental Analysis Complete
☑ Valuation Assessment Complete
☑ Bull vs. Bear Case Complete
☑ Clear Recommendation: **[BUY / HOLD / SELL]**
☑ Alternative Candidates: [If SELL, list 3-5 alternatives below]

---

## 📊 Executive Summary

[2-3 sentence bottom-line assessment with key reasoning]

**Recommendation: [BUY / HOLD / SELL]**
**Conviction: [Strong Buy / Buy / Hold / Avoid]**

---

## 💰 Valuation Assessment

**Fair Value Estimate: €X.XX** (Current: €X.XX)
- **Margin of Safety: X%** [Adequate >15% / Insufficient <15%]
- **Valuation: [UNDERVALUED / FAIRLY VALUED / OVERVALUED]**

| Valuation Method | Fair Value | vs. Current | Weight |
|-----------------|-----------|-------------|--------|
| DCF Analysis | €X.XX | +X% | 40% |
| Peer Relative | €X.XX | +X% | 30% |
| Peter Lynch | €X.XX | +X% | 30% |
| **Weighted Average** | **€X.XX** | **+X%** | **100%** |

**Assumptions:**
- DCF: [Key assumptions - growth rate, margins, discount rate]
- Margin of safety applied: X%

---

## 🏢 Business & Competitive Analysis

### What They Do
[2-3 paragraph business model summary:
- Core products/services
- Revenue breakdown
- Target markets
- Business model]

### Competitive Advantages
**Moat Strength: [Wide / Narrow / None]**

1. **[Advantage 1]**: [Detailed explanation with evidence]
2. **[Advantage 2]**: [Detailed explanation with evidence]
3. **[Advantage 3]**: [Detailed explanation with evidence]

**Moat Durability:** [How sustainable are these advantages? 3-5 years? 10+ years?]




 : [Name] - [Background, tenure]
 Track record: [Achievements/concerns]
 Capital allocation: [Shareholder-friendly? Smart acquisitions?]
 : [Name] - [Financial stewardship]
 : [Recent buying/selling activity]
 : [Overall management assessment]




 Market share: X% (#X in industry)
 Share trend: [Gaining / Stable / Losing]

 [List 3-5 direct peers]


| Company | Mkt Cap | Revenue Growth | Profit Margin | ROE | P/E | Moat |
|---------|---------|---------------|---------------|-----|-----|------|
| [Target] | €XB | X% | X% | X% | X.X | [Rating] |
| [Peer 1] | €XB | X% | X% | X% | X.X | [Rating] |
| [Peer 2] | €XB | X% | X% | X.X | X.X | [Rating] |
| [Peer 3] | €XB | X% | X% | X% | X.X | [Rating] |

 [Is this the best company in the sector?]

---





| Metric | Current | 1Y Ago | 3Y Ago | 5Y Ago | Target | Status |
|--------|---------|--------|--------|--------|--------|--------|
| ROE | X% | X% | X% | X% | >15% | [✓/✗] |
| Profit Margin | X% | X% | X% | X% | >15% | [✓/✗] |
| Gross Margin | X% | X% | X% | X% | >30% | [✓/✗] |
| Revenue Growth | X% | X% | X% | X% | >0% | [✓/✗] |
| Debt/Revenue | X.X | X.X | X.X | X.X | <1.0 | [✓/✗] |
| FCF | €XM | €XM | €XM | €XM | Positive | [✓/✗] |



 [Excellent 8-9 / Good 6-7 / Adequate 4-5 / Weak 0-3]

 X/4
 ROA positive: [✓/✗]
 Operating CF positive: [✓/✗]
 ROA improving: [✓/✗]
 CF > Net Income: [✓/✗]

 X/3
 Debt decreasing: [✓/✗]
 Current ratio improving: [✓/✗]
 No dilution: [✓/✗]

 X/2
 Margin improving: [✓/✗]
 Turnover improving: [✓/✗]

 [Detailed interpretation of F-Score]

 [Safe >2.99 / Grey 1.81-2.99 / Distress <1.81]
  [Low / Moderate / High]
  [Explanation of Z-Score and financial stability]

 [Clean <-1.78 / Warning >-1.78]
  [High / Moderate / Questionable]
  [List any concerning indicators or state "None"]

 [Low <20% / Moderate 20-40% / High 40-60% / Extreme >60%]
  [Low/Moderate/High volatility explanation]
  €X.XX ([Date])
  €X.XX ([Date])



 (Financial power and market position)
 (Earnings quality and transparency)
 (Business consistency)
 (Information completeness)






 [Trend description: growth rate, consistency, drivers]
 [Any concerning patterns?]


 Gross margin: [Expanding / Stable / Declining]
 Operating margin: [Trend]
 Net margin: [Trend]
 Drivers: [Why are margins moving this way?]


 Operating cash flow: [Trend and quality]
 Free cash flow: [Consistency, conversion]
 Capital allocation: [Dividends, buybacks, capex, acquisitions]


 Debt levels: [Conservative / Moderate / High]
 Liquidity: [Strong / Adequate / Concerning]
 Trend: [Strengthening / Stable / Weakening]


[List any concerning trends or issues, or state "None identified"]

---




 : €X.XX
 : €X.XX - €X.XX
 : [+/-X%]
 : [Uptrend / Downtrend / Range-bound]
 : [Increasing / Decreasing / Normal]




  - [Significance/reason]
  - [Significance/reason]


  - [Significance/reason]
  - [Significance/reason]



: X.X [Overbought >70 / Neutral 30-70 / Oversold <30]
: [Bullish crossover / Bearish crossover / Neutral]
 Interpretation: [Momentum assessment]


 50-day MA: €X.XX - Price is [above/below]
 200-day MA: €X.XX - Price is [above/below]
 Golden/Death Cross: [Any recent crossovers?]






 [Buy now at market / Wait for pullback to €X.XX / Buy on breakout above €X.XX]
 
  (avoid above this)



---






 : [Specific evidence and reasoning]
 : [Specific evidence and reasoning]
 : [Specific evidence and reasoning]


 [Required condition 1]
 [Required condition 2]






 : [Specific risk and reasoning]
 : [Specific risk and reasoning]
 : [Specific risk and reasoning]


 [Risk trigger 1]
 [Risk trigger 2]







[2-3 paragraph explanation of:
 Weight of evidence for each side
 Historical precedent
 Management track record
 Industry dynamics
 Current valuation
 Risk/reward assessment]

---







: 
[Specific risk and potential impact. Probability: High/Medium/Low]

: 
[Specific risk and potential impact. Probability: High/Medium/Low]

: 
[Specific risk and potential impact. Probability: High/Medium/Low]

: 
[Specific risk and potential impact. Probability: High/Medium/Low]


[How does the company/investment address these risks?]
[What reduces the risk in this investment?]

---




 : [Specific catalyst - earnings, product launch, etc.]
 : [Specific catalyst]


 [Expected development 1]
 [Expected development 2]


 [Structural trend 1]
 [Structural trend 2]

: [6-12 months / 1-3 years / 3-5+ years]

---







[2-3 paragraph synthesis of entire analysis:
 Why this recommendation?
 What makes it compelling (or not)?
 How does valuation + fundamentals + technicals + catalysts = this conclusion?
 What's the risk/reward?]

---




 Reasoning: [Why this range?]


 Above this: Risk/reward unfavorable


 [Buy now at market / Wait for pullback to €X.XX / Buy on breakout above €X.XX]
 Reasoning: [Current technical setup justification]


 Price exceeds €X.XX without fundamental improvement
 [Other specific condition]

---




 : €X.XX (+X%)
 : €X.XX (+X%)
 : €X.XX (+X%)



 Technical: Below €X.XX support
 Fundamental: If [thesis-breaking condition]


Exit position if any of these occur:
 [Specific fundamental deterioration - e.g., "ROE drops below 10% for 2 consecutive quarters"]
 [Specific competitive threat - e.g., "Loses >5% market share to competitor"]
 [Specific valuation threshold - e.g., "Reaches €X.XX (>50% above fair value)"]


: [6-12 months / 1-3 years / 3-5+ years]
 Based on: [Investment type - swing trade vs. long-term hold]

---







 Conviction level: [Strong Buy / Buy → drives size]
 Risk level: [Low / Moderate / High → constrains size]
 Diversification: [Sector exposure, correlation with existing holdings]
 Liquidity: [Can exit position easily?]


 Risk management limit
 Don't exceed even if highly convicted


 Strong Buy + Low Risk = 5-8% (max 10%)
 Buy + Moderate Risk = 3-5% (max 7%)
 Speculative + High Risk = 1-3% (max 5%)

---




 [Most compelling positive factor]
 [Second most compelling positive factor]
 [Third most compelling positive factor]


 [Biggest risk or concern]
 [Second biggest risk or concern]
 [Third biggest risk or concern]


[Single sentence capturing the complete investment case - why buy or avoid]

---




 10-K filings: [Fiscal years reviewed - e.g., FY2020-2024]
 10-Q filings: [Recent quarters - e.g., Q1-Q3 2025]
 Earnings calls: [Dates reviewed]
 Proxy statements: [Years reviewed]
 Management letters: [Years reviewed]
 Competitor analysis: [Companies benchmarked]


 Historical period analyzed: [X years]
 Peer companies compared: [Number and names]
 Valuation methods used: [DCF, Relative, Peter Lynch, Asset-based]


 : [Quality and completeness of available data]
 : [Any areas where information is limited or unavailable]
 : [Any constraints in the analysis]

---



[If recommending SELL or AVOID, provide 3-5 better investment alternatives with brief rationale for each]


: [1-2 paragraph comparison]
: [Valuation, growth, margins]


: [1-2 paragraph comparison]
: [Valuation, growth, margins]


: [1-2 paragraph comparison]
: [Valuation, growth, margins]

[Continue for 4-5 alternatives if SELL recommendation]

---

: [Current Date]
: [Suggested review date based on catalysts or timeline]
: Claude Stock Evaluator

---



: Create a React artifact using the standardized quant-style dashboard template with:


 ✅ All 48 metrics across 8 sections (calculated above)
 ✅ Historical price data (5 years, 6-12 points)
 ✅ 1-year price + 6-month forecast (4-6 points)
 ✅ MACD data (3-5 recent points)
 ✅ RSI data (3-5 recent points)
 ✅ Radar chart (12 metrics, normalized 0-100)
 ✅ Bull case (target + 5 points)
 ✅ Bear case (target + 5 points)
 ✅ Entry/exit strategy (5 values)




[Create the React artifact here using the quant-style template]

---

Quant-Style Dashboard Artifact

MANDATORY: After completing the full text analysis, create a React dashboard artifact using the standardized quant-style template format.

Dashboard Template Structure

The dashboard uses a specific institutional-grade format with:

1. Header Section (Orange background)

• Format: TICKER - Company Name

2. Eight Metric Sections (2-column grid)

Left Column	Right Column
Price & Valuation (blue)	Financial Performance (green)
Growth Metrics (emerald)	Risk Indicators (red)
Liquidity & FCF (cyan)	Insider & Sentiment (purple)
Quality Scores (orange)	Moat & Other (gray)

Each section: 6 metric boxes with values, labels, benchmarks, color coding

3. Charts Section (3-column grid)

• Left: Linear Price Chart + MACD

  • Price, Intrinsic Value, Market Value lines
  • 5-year historical data
  • MACD indicator below

• Center: Radar Chart + 1-Year Forecast

  • 12-point radar (normalized 0-100)
  • Consolidated advice badge
  • 1-year price + 6-month forecast

• Right: Log Price Chart + RSI

  • Log-scale price history
  • Intrinsic value comparison
  • RSI (14) indicator below

4. Key Notes Section (Expandable accordion)

• 3-column layout: Bull Case | Bear Case | Entry/Exit Strategy
• Click to expand/collapse

5. Footer

• Analysis date, data sources, recommendation

Required Metrics by Section

Price & Valuation (6 metrics):

• Price, Market Cap, Trailing P/E, Forward P/E, Subsector Typical P/E, PEG Ratio

Financial Performance (6 metrics):

• ROE, ROA, Profit Margin, Operating Margin, Gross Margin, ROIC

Growth Metrics (6 metrics):

• Revenue Growth (5Y), Earnings Growth, EPS (TTM), Forward EPS, Analyst Rec, Target Price

Risk Indicators (6 metrics):

• Debt/Equity, Consolidated Risk, F-Score, Z-Score, M-Score, Max Drawdown (5Y)

Liquidity & FCF (6 metrics):

• Current Ratio, Total Cash, Total Debt, FCF Growth 5Y, FCF Yield, Payout Ratio

Insider & Sentiment (6 metrics):

• Insider Buys (12M), Insider Sells (12M), Net Shares (12M), RSI (14D), Stock Type, Sector

Quality Scores (6 metrics):

• CQVS, Label, Valuation Score, Quality Score, Strength Score, Integrity Score

Moat & Other (6 metrics):

• Moat Score (0-10), Beta, Predictability, Data Quality, Completeness, Dividend Yield

Radar Chart Metrics (12 points, normalized 0-100)

1. Revenue Growth (normalize: X% growth → scale to 100 for 20%+)
2. Operating Margin (normalize: X% → 100 for 30%+)
3. Gross Margin (normalize: X% → 100 for 60%+)
4. Profit Margin (normalize: X% → 100 for 25%+)
5. ROE (normalize: X% → 100 for 30%+)
6. Risk Score (inverse of consolidated risk: 100 - risk*100)
7. Beta Score (inverse: 100 for beta=0.5, 50 for beta=1.5, 0 for beta=2.5+)
8. P/Market Discount (100 = deeply undervalued, 50 = fair, 0 = overvalued)
9. Moat Score (moat rating * 10)
10. FCF Yield (X% → 100 for 8%+)
11. ROA (X% → 100 for 20%+)
12. Earnings Growth (X% → 100 for 25%+)

Color Coding Rules

// Green (isGood: true) - Positive indicators
ROE > 20%, ROA > 10%, Margins > 20%, ROIC > 15%
Revenue Growth > 10%, Current Ratio 1-2, Z-Score > 3
M-Score < -1.78, FCF Growth > 0%, Payout < 50%
F-Score >= 7, Quality >= 70, Strength >= 70

// Red (isGood: false) - Warning indicators  
Max Drawdown < -50%, Beta > 2, Consolidated Risk > 0.6
Predictability < 50%, F-Score <= 3, Z-Score < 1.81
M-Score > -1.78, Quality < 50

// Yellow (isGood: 'neutral') - Monitor
F-Score 4-,  -,  -,  -
 -,  -%

Complete Template Code

Use this exact template structure:

import React, { useState } from 'react';
import { 
  LineChart, Line, XAxis, YAxis, CartesianGrid, Tooltip, 
  ResponsiveContainer, RadarChart, PolarGrid, PolarAngleAxis, 
  PolarRadiusAxis, Radar, ReferenceLine, Area, ComposedChart, Scatter
} from 'recharts';

const QuantDashboard = () => {
  const [showKeyNotes, setShowKeyNotes] = useState(false);

  // ============================================================
  // POPULATE WITH STOCK-SPECIFIC DATA FROM ANALYSIS
  // ============================================================
  
  const ticker = "TICKER";  // Replace
  const companyName = "Company Name";  // Replace
  const recommendation = "BUY";  // BUY, HOLD, SELL, SPECULATIVE BUY
  const analysisDate = "December 6, 2025";  // Current date

  const metrics = {
    // Price & Valuation - from analysis
    price: ,
    : ,
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  };

  
   topNews = [
    { : , :  },
    { : , :  },
    { : , :  },
    { : , :  },
    { : , :  },
  ];
  
  
   topNewsString = topNews.( ).();

  
   priceHistory = [
    { : , : , : , : , : , : , : , : , : , :  },
    { : , : , : , : , : , : , : , : , : , :  },
    { : , : , : , : , : , : , : , : , : , :  },
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  ];

  
   oneYearData = [
    { : , : , : , : , : , : , : , : , :  },
    { : , : , : , : , : , : , : , : , :  },
    { : , : , : , : , : , : , : , : , :  },
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   ichimokuData = [
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  ];

  
   ichimokuSignals = {
    : ,
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  };

  
   macdData = [
    { : , : , : , :  },
    { : , : , : , :  },
    { : , : , : , :  },
    { : , : , : , :  },
    { : , : , : , : - },
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  ];

  
   rsiData = [
    { : , :  },
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  ];

  
   radarData = [
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   bullCase = {
    : ,  
    : [
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    ]
  };

   bearCase = {
    : ,  
    : [
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  };

   entryStrategy = {
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  };

  
  
  

  
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  };

  
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  };

  
    = () => (
    
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    = () => {
     bgColor = ;
     (isGood === ) bgColor = ;
     (isGood === ) bgColor = ;
     (isGood === ) bgColor = ;
    
     (
      
    );
  };

    = () => (
    
  );

   (
    <div className="w-full max-w-7xl mx-auto p-3 bg-white text-xs">
      {/* Header */}
      <div className="bg-orange-500 text-white px-3 py-2 mb-1 text-lg font-bold text-center">
        {ticker} - {companyName}
      </div>

      {/* TOP NEWS - Pipe separated with dates at END */}
      <div className="border border-gray-300 rounded p-2 mb-3 bg-gray-50">
        <span className="font-bold text-[10px]">TOP NEWS:</span>
        <div className="text-[9px] mt-1">{topNewsString}</div>
      </div>

      {/* Top 4 sections */}
      <div className="grid grid-cols-2 gap-2 mb-3">
        {/* Price & Valuation - Updated with dual PEG */}
        <div className="border border-gray-300 rounded overflow-hidden">
          <SectionHeader title="PRICE & VALUATION" bgColor="bg-blue-100" />
          <div className="grid grid-cols-7 gap-px bg-gray-200">
            <MetricBox label="Price:" value={`€${metrics.price}`} />
            <MetricBox label="Market Cap:" value={metrics.marketCap} />
            <MetricBox label="Trailing P/E:" value={metrics.trailingPE} />
            <MetricBox label="Forward P/E:" value={metrics.forwardPE} benchmark={`(${metrics.subsectorTypicalPE})`} isGood={metrics.forwardPE < metrics.subsectorTypicalPE} />
            <MetricBox label="Subsector P/E:" value={metrics.subsectorTypicalPE} />
            <MetricBox label="PEG (1Y):" value={metrics.peg1Y} benchmark="(<1.5)" isGood={metrics.peg1Y < 1.5 ? true : metrics.peg1Y < 2 ? 'neutral' : false} />
            <MetricBox label="PEG (5Y):" value={metrics.peg5Y} benchmark="(<2)" isGood={metrics.peg5Y < 2 ? true : metrics.peg5Y < 3 ? 'neutral' : false} />
          </div>
        </div>

        {/* Financial Performance */}
        <div className="border border-gray-300 rounded overflow-hidden">
          <SectionHeader title="FINANCIAL PERFORMANCE" bgColor="bg-green-100" />
          <div className="grid grid-cols-6 gap-px bg-gray-200">
            <MetricBox label="ROE:" value={`${metrics.roe}%`} benchmark="(>20%)" isGood={metrics.roe >= 20 ? true : metrics.roe >= 10 ? 'neutral' : false} />
            <MetricBox label="ROA:" value={`${metrics.roa}%`} benchmark="(>10%)" isGood={metrics.roa >= 10} />
            <MetricBox label="Profit Margin:" value={`${metrics.profitMargin}%`} benchmark="(>20%)" isGood={metrics.profitMargin >= 20 ? true : metrics.profitMargin >= 10 ? 'neutral' : false} />
            <MetricBox label="Operative Margin:" value={`${metrics.opMargin}%`} benchmark="(>20%)" isGood={metrics.opMargin >= 20} />
            <MetricBox label="Gross Margin:" value={`${metrics.grossMargin}%`} benchmark="(>40%)" isGood={metrics.grossMargin >= 40} />
            <MetricBox label="ROIC:" value={`${metrics.roic}%`} benchmark="(>15%)" isGood={metrics.roic >= 15} />
          </div>
        </div>
      </div>

      {/* Next 4 sections */}
      <div className="grid grid-cols-2 gap-2 mb-3">
        {/* Growth Metrics */}
        <div className="border border-gray-300 rounded overflow-hidden">
          <SectionHeader title="GROWTH METRICS" bgColor="bg-emerald-100" />
          <div className="grid grid-cols-7 gap-px bg-gray-200">
            <MetricBox label="Revenue (YoY):" value={`${metrics.revGrowth}%`} benchmark="(>10%)" isGood={metrics.revGrowth >= 10} />
            <MetricBox label="Earning (YoY):" value={`${metrics.earnGrowth}%`} benchmark="(>0%)" isGood={metrics.earnGrowth >= 0} />
            <MetricBox label="EPS (TTM):" value={`€${metrics.epsTTM}`} />
            <MetricBox label="Forward EPS:" value={`€${metrics.forwardEPS}`} isGood={metrics.forwardEPS > metrics.epsTTM} />
            <MetricBox label="Growth Rates:" value={`Capped: ${metrics.growthCapped}%`} benchmark={`Uncapped: ${metrics.growthUncapped}%`} />
            <MetricBox label="Analyst Target:" value={`€${metrics.analystTarget}`} />
          </div>
        </div>

        {/* Risk Indicators */}
        <div className="border border-gray-300 rounded overflow-hidden">
          <SectionHeader title="RISK INDICATORS" bgColor="bg-red-100" />
          <div className="grid grid-cols-6 gap-px bg-gray-200">
            <MetricBox label="CRS (0-1):" value={metrics.crs.toFixed(2)} benchmark="(Medium)" isGood={metrics.crs < 0.4 ? true : metrics.crs < 0.6 ? 'neutral' : false} />
            <MetricBox label="Debt/Equity (mrq):" value={metrics.debtEquity} benchmark="(0.5-1)" isGood={metrics.debtEquity < 1 ? true : metrics.debtEquity < 2 ? 'neutral' : false} />
            <MetricBox label="Piotroski F:" value={metrics.fScore} benchmark="(≥7)" isGood={metrics.fScore >= 7 ? true : metrics.fScore >= 4 ? 'neutral' : false} />
            <MetricBox label="Altman Z:" value={metrics.zScore.toFixed(2)} benchmark="(>3)" isGood={metrics.zScore >= 2.99 ? true : metrics.zScore >= 1.81 ? 'neutral' : false} />
            <MetricBox label="Beneish M:" value={metrics.mScore.toFixed(2)} benchmark="(<-1.78)" isGood={metrics.mScore < -1.78} />
            <MetricBox label="Value Trap:" value={`${metrics.valueTrapScore} (${metrics.valueTrapLabel})`} isGood={metrics.valueTrapScore < 40 ? true : metrics.valueTrapScore < 60 ? 'neutral' : false} />
          </div>
        </div>
      </div>

      {/* Next 4 sections */}
      <div className="grid grid-cols-2 gap-2 mb-3">
        {/* Liquidity & Free Cash Flow */}
        <div className="border border-gray-300 rounded overflow-hidden">
          <SectionHeader title="LIQUIDITY & FREE CASH FLOW" bgColor="bg-cyan-100" />
          <div className="grid grid-cols-7 gap-px bg-gray-200">
            <MetricBox label="Current Ratio:" value={metrics.currentRatio.toFixed(2)} benchmark="(1-2)" isGood={metrics.currentRatio >= 1 && metrics.currentRatio <= 2 ? true : 'neutral'} />
            <MetricBox label="Cash:" value={metrics.totalCash} />
            <MetricBox label="Debt:" value={metrics.totalDebt} />
            <MetricBox label="FCF Growth 5Y:" value={`${metrics.fcfGrowth5Y}%`} benchmark="(>5%)" isGood={metrics.fcfGrowth5Y >= 5} />
            <MetricBox label="FCF Yield:" value={`${metrics.fcfYield}%`} benchmark="(>4%)" isGood={metrics.fcfYield >= 4} />
            <MetricBox label="FCF Margin:" value={`${metrics.fcfMargin}%`} benchmark="(>15%)" isGood={metrics.fcfMargin >= 15 ? true : metrics.fcfMargin >= 10 ? 'neutral' : false} />
            <MetricBox label="Payout Ratio:" value={`${metrics.payoutRatio}%`} benchmark="(<50%)" isGood={metrics.payoutRatio < 50} />
          </div>
        </div>

        {/* Insider & Sentiment & Class */}
        <div className="border border-gray-300 rounded overflow-hidden">
          <SectionHeader title="INSIDER & SENTIMENT & CLASS" bgColor="bg-purple-100" />
          <div className="grid grid-cols-7 gap-px bg-gray-200">
            <MetricBox label="Buys (12M):" value={metrics.insBuys} isGood={metrics.insBuys > metrics.insSells} />
            <MetricBox label="Sells (12M):" value={metrics.insSells} />
            <MetricBox label="Net Shares (12M):" value={metrics.netShares} />
            <MetricBox label="Short Int (%):" value={`${metrics.shortInterest}%`} isGood={metrics.shortInterest < 5 ? true : metrics.shortInterest < 10 ? 'neutral' : false} />
            <MetricBox label="Sentiment / Articles:" value={`${metrics.newsSentiment > 0 ? '+' : ''}${metrics.newsSentiment.toFixed(3)} / ${metrics.newsArticleCount}`} benchmark={metrics.newsSentiment > 0 ? '(Positive)' : '(Negative)'} isGood={metrics.newsSentiment > 0} />
            <MetricBox label={`Stock: ${metrics.stockType}`} value={`Div Yield: ${metrics.divYield}%`} />
            <MetricBox label="Sector/Industry:" value={`${metrics.sector} /`} benchmark={metrics.industry} />
          </div>
        </div>
      </div>

      {/* Last 2 sections */}
      <div className="grid grid-cols-2 gap-2 mb-3">
        {/* Quality Scores */}
        <div className="border border-gray-300 rounded overflow-hidden">
          <SectionHeader title="QUALITY SCORES" bgColor="bg-orange-100" />
          <div className="grid grid-cols-6 gap-px bg-gray-200">
            <MetricBox label="CQVS:" value={metrics.cqvs.toFixed(1)} benchmark="(>70)" isGood={metrics.cqvs >= 70 ? true : metrics.cqvs >= 50 ? 'neutral' : false} />
            <MetricBox label="Label:" value={metrics.label} />
            <MetricBox label="Valuation:" value={metrics.valuation} isGood={metrics.valuation >= 70} />
            <MetricBox label="Quality:" value={metrics.quality} isGood={metrics.quality >= 70 ? true : metrics.quality >= 50 ? 'neutral' : false} />
            <MetricBox label="Strength:" value={metrics.strength} isGood={metrics.strength >= 70} />
            <MetricBox label="Integrity:" value={metrics.integrity} isGood={metrics.integrity >= 70 ? true : metrics.integrity >= 50 ? 'neutral' : false} />
          </div>
        </div>

        {/* Moat & Other */}
        <div className="border border-gray-300 rounded overflow-hidden">
          <SectionHeader title="MOAT & OTHER" bgColor="bg-gray-200" />
          <div className="grid grid-cols-6 gap-px bg-gray-200">
            <MetricBox label="Buffett Moat:" value={metrics.buffettMoat} benchmark="(4-7)" isGood={metrics.buffettMoat >= 7 ? true : metrics.buffettMoat >= 4 ? 'neutral' : false} />
            <MetricBox label="Greenblatt (MF):" value={`EY: ${metrics.greenblattEY}%`} benchmark={metrics.greenblattROC ? `ROC: ${metrics.greenblattROC}%` : 'ROC: N/A'} isGood={metrics.greenblattEY >= 8 ? true : metrics.greenblattEY >= 4 ? 'neutral' : false} />
            <MetricBox label={`Beta: ${metrics.beta}`} value={`Vol 1Y: ${metrics.vol1Y}%`} isGood={metrics.beta < 1 ? true : metrics.beta < 1.5 ? 'neutral' : false} />
            <MetricBox label="Earnings Predict.:" value={`${metrics.earningsPredict}%`} benchmark="(>80%)" isGood={metrics.earningsPredict >= 80 ? true : metrics.earningsPredict >= 60 ? 'neutral' : false} />
            <MetricBox label="Drawdown (5Y):" value={`${metrics.maxDrawdown}%`} benchmark={metrics.maxDrawdown > -30 ? '(Low)' : metrics.maxDrawdown > -50 ? '(Mid)' : '(High)'} isGood={metrics.maxDrawdown > -30 ? true : metrics.maxDrawdown > -50 ? 'neutral' : false} />
            <MetricBox label={`Completeness: ${metrics.completeness}%`} value={`Data Quality: ${metrics.dataQuality}`} isGood={metrics.dataQuality === 'High' ? true : metrics.dataQuality === 'Medium' ? 'neutral' : false} />
          </div>
        </div>
      </div>

      {/* Charts Section - Enhanced with Legends */}
      <div className="grid grid-cols-3 gap-2 mb-3">
        {/* Linear Price Chart + MACD */}
        <div className="border border-gray-300 rounded p-2">
          <div className="text-sm font-bold mb-1 text-center">LINEAR PRICE CHART (10Y)</div>
          <div className="text-[7px] text-gray-500 mb-1 pl-1">
            — Close Price — Total Return<br/>
            - - Market Value (Current): €{metrics.marketValueCurrent}<br/>
            - - Intrinsic Value (Current): €{metrics.intrinsicValueCurrent}<br/>
            - - Analyst Target: €{metrics.analystTarget}
          </div>
          <ResponsiveContainer width="100%" height={130}>
            <LineChart data={priceHistory}>
              <CartesianGrid strokeDasharray="3 3" stroke="#e0e0e0" />
              <XAxis dataKey="date" tick={{ fontSize: 7 }} />
              <YAxis tick={{ fontSize: 7 }} />
              <Tooltip contentStyle={{ fontSize: 8 }} />
              <Line type="monotone" dataKey="price" stroke="#1f2937" strokeWidth={1.5} dot={false} name="Close" />
              <Line type="monotone" dataKey="totalReturn" stroke="#6b7280" strokeWidth={1} strokeDasharray="2 2" dot={false} name="Total Return" />
              <Line type="monotone" dataKey="intrinsicValueCurrent" stroke="#16a34a" strokeWidth={1} strokeDasharray="5 5" dot={false} name="IV Current" />
              <Line type="monotone" dataKey="analystTarget" stroke="#3b82f6" strokeWidth={1} strokeDasharray="3 3" dot={false} name="Target" />
            </LineChart>
          </ResponsiveContainer>
          <div className="text-xs font-bold mt-1 mb-1 text-center">MACD</div>
          <ResponsiveContainer width="100%" height={55}>
            <LineChart data={macdData}>
              <CartesianGrid strokeDasharray="3 3" stroke="#e0e0e0" />
              <XAxis dataKey="date" tick={{ fontSize: 6 }} />
              <YAxis tick={{ fontSize: 6 }} />
              <ReferenceLine y={0} stroke="#666" />
              <Tooltip contentStyle={{ fontSize: 7 }} />
              <Line type="monotone" dataKey="macd" stroke="#2563eb" strokeWidth={1} dot={false} name="MACD" />
              <Line type="monotone" dataKey="signal" stroke="#dc2626" strokeWidth={1} dot={false} name="Signal" />
            </LineChart>
          </ResponsiveContainer>
        </div>

        {/* Radar + Investor Personas + Forecast */}
        <div className="border border-gray-300 rounded p-2">
          <div className="relative">
            <ResponsiveContainer width="100%" height={140}>
              <RadarChart data={radarData}>
                <PolarGrid />
                <PolarAngleAxis dataKey="metric" tick={{ fontSize: 6 }} />
                <PolarRadiusAxis angle={30} domain={[0, 100]} tick={{ fontSize: 6 }} />
                <Radar name={ticker} dataKey="value" stroke="#2563eb" fill="#3b82f6" fillOpacity={0.3} />
              </RadarChart>
            </ResponsiveContainer>
            {/* Investor Persona Badges */}
            <PersonaBadge name="Buffett" score={metrics.buffettScore} position="top-0 left-1/4" />
            <PersonaBadge name="Lynch" score={metrics.lynchScore} position="top-0 right-1/4" />
            <PersonaBadge name="Munger" score={metrics.mungerScore} position="top-1/4 -left-2" />
            <PersonaBadge name="Greenblatt" score={metrics.greenblattScore} position="top-1/4 -right-2" />
            <PersonaBadge name="Dalio" score={metrics.dalioScore} position="bottom-1/4 -left-2" />
            <PersonaBadge name="Graham" score={metrics.grahamScore} position="bottom-1/4 -right-2" />
            <PersonaBadge name="Templeton" score={metrics.templetonScore} position="bottom-0 left-1/4" />
            <PersonaBadge name="Soros" score={metrics.sorosScore} position="bottom-0 right-1/4" />
          </div>
          <div className="text-center my-1">
            <span className="bg-green-200 px-2 py-0.5 text-[10px] font-bold rounded border border-green-400">
              Advice: {recommendation} (CQVS: {metrics.cqvs.toFixed(1)})
            </span>
          </div>
          <div className="text-[8px] font-bold mb-0.5 text-center">1Y PRICE + 6-MONTH FORECAST</div>
          <div className="text-[6px] text-gray-500 mb-0.5 text-center">— Close — 50-Day MA — 200-Day MA ▒ Bollinger Bands - - Forecast</div>
          <ResponsiveContainer width="100%" height={70}>
            <ComposedChart data={oneYearData}>
              <CartesianGrid strokeDasharray="3 3" stroke="#e0e0e0" />
              <XAxis dataKey="date" tick={{ fontSize: 6 }} />
              <YAxis tick={{ fontSize: 6 }} />
              <Tooltip contentStyle={{ fontSize: 7 }} />
              <Area type="monotone" dataKey="upperBand" stroke="none" fill="#e0e0e0" fillOpacity={0.5} />
              <Area type="monotone" dataKey="ci95Upper" stroke="none" fill="#dbeafe" fillOpacity={0.5} />
              <Line type="monotone" dataKey="price" stroke="#1f2937" strokeWidth={1.5} dot={false} />
              <Line type="monotone" dataKey="ma50" stroke="#f59e0b" strokeWidth={1} dot={false} />
              <Line type="monotone" dataKey="ma200" stroke="#ef4444" strokeWidth={1} dot={false} />
              <Line type="monotone" dataKey="forecast" stroke="#16a34a" strokeWidth={1.5} strokeDasharray="5 5" dot={false} />
            </ComposedChart>
          </ResponsiveContainer>
          {/* Valuation Indicator */}
          <div className={`text-center text-[10px] font-bold mt-1 ${metrics.valuationPercent > 10 ? 'text-green-600' : metrics.valuationPercent < -10 ? 'text-red-600' : 'text-yellow-600'}`}>
            {metrics.valuationLabel} ({metrics.valuationPercent > 0 ? '+' : ''}{metrics.valuationPercent}%)
          </div>
        </div>

        {/* Log Price + RSI */}
        <div className="border border-gray-300 rounded p-2">
          <div className="text-sm font-bold mb-1 text-center">LOG PRICE CHART (10Y)</div>
          <div className="text-[7px] text-gray-500 mb-1 pl-1">
            — Close Price — Total Return<br/>
            - - Unrestr. Market Value (Current): €{metrics.unrestrictedMarketValueCurrent}<br/>
            - - Unrestr. Market Value (Next Year): €{metrics.unrestrictedMarketValueNextYear}
          </div>
          <ResponsiveContainer width="100%" height={130}>