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.

⚠️ 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.

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"

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	>0%	-10% to 0%	<-10%

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

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

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

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

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

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)

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)

Bull vs. Bear Case Analysis

MANDATORY: Every analysis must present both sides fairly.

Bull Case (Optimistic Scenario)

Potential Upside: +X% to €X.XX

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

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

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:

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
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
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
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
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?]

### Management Quality Assessment
**Overall Rating: [Excellent / Good / Adequate / Concerning]**

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

### Competitive Position

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

**Key Competitors:** [List 3-5 direct peers]

**Peer Comparison:**
| 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] |

**Competitive Assessment:** [Is this the best company in the sector?]

---

## 📈 Financial Health Analysis

### Quality Metrics vs. Benchmarks

| 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 | [✓/✗] |

### Advanced Financial Health Scores

**Piotroski F-Score: X/9** [Excellent 8-9 / Good 6-7 / Adequate 4-5 / Weak 0-3]

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

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

*Efficiency:* X/2
- Margin improving: [✓/✗]
- Turnover improving: [✓/✗]

**Assessment:** [Detailed interpretation of F-Score]

**Altman Z-Score: X.XX** [Safe >2.99 / Grey 1.81-2.99 / Distress <1.81]
- **Bankruptcy Risk:** [Low / Moderate / High]
- **Interpretation:** [Explanation of Z-Score and financial stability]

**Beneish M-Score: X.XX** [Clean <-1.78 / Warning >-1.78]
- **Earnings Quality:** [High / Moderate / Questionable]
- **Red Flags:** [List any concerning indicators or state "None"]

**Max Drawdown (5Y): -X%** [Low <20% / Moderate 20-40% / High 40-60% / Extreme >60%]
- **Volatility Assessment:** [Low/Moderate/High volatility explanation]
- **Peak price:** €X.XX ([Date])
- **Trough price:** €X.XX ([Date])

### Consolidated Scores

**Strength Score: X/100** (Financial power and market position)
**Integrity Score: X/100** (Earnings quality and transparency)
**Predictability Score: X/100** (Business consistency)
**Data Quality Score: X/100** (Information completeness)

**Overall Quality Rating: [Elite / Strong / Good / Adequate / Weak]**

### Financial Trends (5-10 Year View)

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

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

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

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

### 🚩 Red Flags
[List any concerning trends or issues, or state "None identified"]

---

## 📉 Technical Analysis & Entry Timing

### Price Action (Last 30-60 Days)
- **Current Price**: €X.XX
- **52-Week Range**: €X.XX - €X.XX
- **30-day Change**: [+/-X%]
- **Trend**: [Uptrend / Downtrend / Range-bound]
- **Volume**: [Increasing / Decreasing / Normal]

### Key Technical Levels

**Support Levels:**
- **Primary Support: €X.XX** - [Significance/reason]
- **Secondary Support: €X.XX** - [Significance/reason]

**Resistance Levels:**
- **Primary Resistance: €X.XX** - [Significance/reason]
- **Secondary Resistance: €X.XX** - [Significance/reason]

### Technical Indicators

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

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

### Entry Assessment

**Technical Setup: [Bullish / Neutral / Bearish]**

**Optimal Entry Strategy:**
- [Buy now at market / Wait for pullback to €X.XX / Buy on breakout above €X.XX]
- **Ideal Entry Range: €X.XX - €X.XX**
- **Maximum Buy Price: €X.XX** (avoid above this)

**Momentum: [Strong Bullish / Bullish / Neutral / Bearish / Strong Bearish]**

---

## ⚖️ Bull vs. Bear Case

### 🐂 Bull Case
**Potential Upside: €X.XX (+X%)**

1. **[Bull Argument 1]**: [Specific evidence and reasoning]
2. **[Bull Argument 2]**: [Specific evidence and reasoning]
3. **[Bull Argument 3]**: [Specific evidence and reasoning]

**For this to play out:**
- [Required condition 1]
- [Required condition 2]

**Probability: [High / Moderate / Low]**

### 🐻 Bear Case
**Potential Downside: €X.XX (-X%)**

1. **[Bear Argument 1]**: [Specific risk and reasoning]
2. **[Bear Argument 2]**: [Specific risk and reasoning]
3. **[Bear Argument 3]**: [Specific risk and reasoning]

**This happens if:**
- [Risk trigger 1]
- [Risk trigger 2]

**Probability: [High / Moderate / Low]**

### ⚖️ Balance Assessment

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

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

---

## ⚠️ Risk Analysis

**Overall Risk Level: [Low / Moderate / High]**

### Key Risks

**1. [Risk Category - e.g., Competition Risk]**: 
[Specific risk and potential impact. Probability: High/Medium/Low]

**2. [Risk Category - e.g., Execution Risk]**: 
[Specific risk and potential impact. Probability: High/Medium/Low]

**3. [Risk Category - e.g., Valuation Risk]**: 
[Specific risk and potential impact. Probability: High/Medium/Low]

**4. [Risk Category - e.g., Macro Risk]**: 
[Specific risk and potential impact. Probability: High/Medium/Low]

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

---

## 🎯 Catalysts & Timeline

### Near-Term (0-6 months)
- **[Date]**: [Specific catalyst - earnings, product launch, etc.]
- **[Date]**: [Specific catalyst]

### Medium-Term (6-18 months)
- [Expected development 1]
- [Expected development 2]

### Long-Term (18+ months)
- [Structural trend 1]
- [Structural trend 2]

**Expected Timeline to Target**: [6-12 months / 1-3 years / 3-5+ years]

---

## 💡 Investment Recommendation

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

### Rationale
[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?]

---

## 📍 Entry Strategy (if BUY)

**Ideal Entry Price: €X.XX - €X.XX**
- Reasoning: [Why this range?]

**Maximum Acceptable Price: €X.XX**
- Above this: Risk/reward unfavorable

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

**DO NOT BUY IF:**
- Price exceeds €X.XX without fundamental improvement
- [Other specific condition]

---

## 🎯 Exit Strategy

### Price Targets (12-Month Horizon)
- **Conservative**: €X.XX (+X%)
- **Base Case**: €X.XX (+X%)
- **Optimistic**: €X.XX (+X%)

### Stop Loss
**Stop Loss: €X.XX (-X% maximum loss)**
- Technical: Below €X.XX support
- Fundamental: If [thesis-breaking condition]

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

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

---

## 📏 Position Sizing

### Recommended Allocation: X-X% of portfolio
**Specific Recommendation: X%**

**Rationale:**
- 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?]

**Maximum Allocation: X%**
- Risk management limit
- Don't exceed even if highly convicted

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

---

## 🔑 Key Takeaways

### Top 3 Reasons to Invest
1. [Most compelling positive factor]
2. [Second most compelling positive factor]
3. [Third most compelling positive factor]

### Top 3 Concerns
1. [Biggest risk or concern]
2. [Second biggest risk or concern]
3. [Third biggest risk or concern]

### One-Sentence Investment Thesis
[Single sentence capturing the complete investment case - why buy or avoid]

---

## 📚 Research Documentation

**Sources Consulted:**
- 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]

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

**Confidence Level: [High / Medium / Low]**
- **Based on**: [Quality and completeness of available data]
- **Gaps**: [Any areas where information is limited or unavailable]
- **Limitations**: [Any constraints in the analysis]

---

## 🔄 Alternative Candidates (Required if SELL/AVOID)

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

### Alternative 1: [Symbol] - [Company Name]
**Why it's better**: [1-2 paragraph comparison]
**Quick metrics**: [Valuation, growth, margins]

### Alternative 2: [Symbol] - [Company Name]
**Why it's better**: [1-2 paragraph comparison]
**Quick metrics**: [Valuation, growth, margins]

### Alternative 3: [Symbol] - [Company Name]
**Why it's better**: [1-2 paragraph comparison]
**Quick metrics**: [Valuation, growth, margins]

[Continue for 4-5 alternatives if SELL recommendation]

---

**Analysis Date**: [Current Date]
**Next Review**: [Suggested review date based on catalysts or timeline]
**Analyst**: Claude Stock Evaluator

---

## 📊 Quant-Style Dashboard

**FINAL MANDATORY STEP**: Create a React artifact using the standardized quant-style dashboard template with:

**Required Data to Populate:**
- ✅ 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)

**Use the EXACT template code provided in the skill instructions above.**
**DO NOT use placeholder values - populate with actual calculated data from this analysis.**

[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)

Revenue Growth (normalize: X% growth → scale to 100 for 20%+)
Operating Margin (normalize: X% → 100 for 30%+)
Gross Margin (normalize: X% → 100 for 60%+)
Profit Margin (normalize: X% → 100 for 25%+)
ROE (normalize: X% → 100 for 30%+)
Risk Score (inverse of consolidated risk: 100 - risk*100)
Beta Score (inverse: 100 for beta=0.5, 50 for beta=1.5, 0 for beta=2.5+)
P/Market Discount (100 = deeply undervalued, 50 = fair, 0 = overvalued)
Moat Score (moat rating * 10)
FCF Yield (X% → 100 for 8%+)
ROA (X% → 100 for 20%+)
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 4-6, RSI 30-70, Moat 5-7, Quality 50-70
Beta 1.5-2.0, Predictability 50-70%

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: 100.00,
    marketCap: '€10B',
    trailingPE: 20.0,
    forwardPE: 18.0,
    subsectorTypicalPE: 25.0,
    peg1Y: 1.2,           // NEW: 1-Year Forward PEG
    peg5Y: 2.5,           // NEW: 5-Year PEG

    // Financial Performance - from 5-10 year analysis
    roe: 25.0,
    roa: 12.0,
    profitMargin: 20.0,
    opMargin: 25.0,
    grossMargin: 50.0,
    roic: 18.0,

    // Growth Metrics - from historical trends (USE REPORTED, not underlying)
    revGrowth: 15.0,      // REPORTED revenue growth YoY
    earnGrowth: 20.0,     // REPORTED earnings growth YoY
    epsTTM: 5.00,
    forwardEPS: 5.50,
    growthCapped: 10.0,   // NEW: Capped sustainable growth estimate
    growthUncapped: 22.0, // NEW: Headline analyst growth estimate
    analystTarget: 120.00,

    // Risk Indicators - from advanced metrics section
    crs: 0.40,            // Consolidated Risk Score (0-1 scale)
    debtEquity: 0.50,
    fScore: 7,            // Piotroski F-Score
    zScore: 4.0,          // Altman Z-Score
    mScore: -2.5,         // Beneish M-Score
    valueTrapScore: 25,   // NEW: 0-100, LOWER = genuine, HIGHER = trap
    valueTrapLabel: 'Genuine', // NEW: Genuine/Caution/Trap
    maxDrawdown: -30.0,   // 5-year max drawdown %

    // Liquidity & FCF - from cash flow analysis
    currentRatio: 1.5,
    totalCash: '€2B',
    totalDebt: '€1B',
    fcfGrowth5Y: 12.0,    // 5-year smoothed growth
    fcfYield: 5.0,
    fcfMargin: 18.5,      // NEW: FCF / Revenue %
    payoutRatio: 30.0,

    // Insider & Sentiment - from SEC Form 4 or use "N/A" if unavailable
    insBuys: 0,           // From SEC Form 4 - use actual count or "N/A"
    insSells: 0,          // From SEC Form 4 - use actual count or "N/A"
    netShares: 'N/A',     // From SEC Form 4 - use actual or "N/A"
    shortInterest: 2.5,   // From FINRA/exchange - use actual or "N/A"
    newsSentiment: 0.25,  // -1 to +1 scale
    newsArticleCount: 15, // Recent article count

    // Beta & Volatility
    beta: 1.0,            // Stock beta
    vol1Y: 25.0,          // 1-Year volatility %

    // Quality Scores - from consolidated scoring
    cqvs: 75.0,           // Consolidated Quality & Valuation Score
    label: 'Quality Growth', // Elite/Compounder/Quality Growth/etc
    valuation: 70.0,      // 0-100
    quality: 80.0,        // 0-100
    strength: 75.0,       // 0-100
    integrity: 85.0,      // 0-100

    // Moat & Other
    buffettMoat: 8,       // 0-10 scale (renamed from moat)
    greenblattEY: 6.5,    // NEW: Earnings Yield %
    greenblattROC: 22.0,  // NEW: Return on Capital %
    earningsPredict: 70,  // Earnings Predictability 0-100
    completeness: 85,     // Data completeness 0-100
    dataQuality: 'High',  // High/Medium/Low
    divYield: 1.5,
    stockType: 'Growth',  // Growth/Value/Cyclical/Defensive
    sector: 'Technology',
    industry: 'Software',

    // NEW: Investor Persona Scores (0-10 scale each)
    buffettScore: 7.5,    // Durable competitive advantage seeker
    mungerScore: 6.8,     // Inversion thinker, risk avoider
    dalioScore: 7.2,      // All-weather, cycle resilient
    lynchScore: 8.0,      // GARP - Growth at Reasonable Price
    grahamScore: 5.5,     // Deep value, margin of safety
    greenblattScore: 6.0, // Magic Formula (EY + ROC)
    templetonScore: 4.5,  // Contrarian, global value
    sorosScore: 3.0,      // Reflexivity, macro trends

    // NEW: Valuation Lines for Charts
    marketValueCurrent: 95.00,
    intrinsicValueCurrent: 110.00,
    marketValueNextYear: 105.00,
    intrinsicValueNextYear: 120.00,
    unrestrictedMarketValueCurrent: 125.00,
    unrestrictedMarketValueNextYear: 140.00,

    // Valuation Assessment (for indicator below forecast)
    valuationPercent: 15,       // Positive = undervalued, negative = overvalued
    valuationLabel: 'Undervalued', // Undervalued/Fairly Valued/Overvalued
  };

  // TOP NEWS Headlines - Format: pipe-separated with dates at END in brackets
  const topNews = [
    { headline: 'Company announces Q4 guidance above expectations', date: '05 Dec 2025' },
    { headline: 'New product launch receives positive analyst coverage', date: '28 Nov 2025' },
    { headline: 'Strategic partnership announced with major cloud provider', date: '15 Nov 2025' },
    { headline: 'Q3 earnings beat estimates, revenue up 18% YoY', date: '02 Nov 2025' },
    { headline: 'Management presents at investor conference, reaffirms outlook', date: '20 Oct 2025' },
  ];

  // Format TOP NEWS as pipe-separated string with dates at END
  const topNewsString = topNews.map(n => `${n.headline} [${n.date}]`).join(' | ');

  // Historical Price Data (10 years with multiple valuation lines)
  const priceHistory = [
    { date: '2016', price: 25, totalReturn: 28, marketValueCurrent: 27, intrinsicValueCurrent: 30, marketValueNextYear: 29, intrinsicValueNextYear: 32, analystTarget: 30, unrestrictedCurrent: 28, unrestrictedNextYear: 31 },
    { date: '2017', price: 35, totalReturn: 40, marketValueCurrent: 38, intrinsicValueCurrent: 42, marketValueNextYear: 40, intrinsicValueNextYear: 45, analystTarget: 42, unrestrictedCurrent: 40, unrestrictedNextYear: 44 },
    { date: '2018', price: 45, totalReturn: 52, marketValueCurrent: 48, intrinsicValueCurrent: 55, marketValueNextYear: 52, intrinsicValueNextYear: 60, analystTarget: 55, unrestrictedCurrent: 52, unrestrictedNextYear: 58 },
    { date: '2019', price: 55, totalReturn: 65, marketValueCurrent: 58, intrinsicValueCurrent: 68, marketValueNextYear: 62, intrinsicValueNextYear: 72, analystTarget: 65, unrestrictedCurrent: 65, unrestrictedNextYear: 72 },
    { date: '2020', price: 50, totalReturn: 62, marketValueCurrent: 55, intrinsicValueCurrent: 65, marketValueNextYear: 60, intrinsicValueNextYear: 70, analystTarget: 62, unrestrictedCurrent: 62, unrestrictedNextYear: 70 },
    { date: '2021', price: 75, totalReturn: 95, marketValueCurrent: 80, intrinsicValueCurrent: 90, marketValueNextYear: 85, intrinsicValueNextYear: 98, analystTarget: 90, unrestrictedCurrent: 92, unrestrictedNextYear: 105 },
    { date: '2022', price: 65, totalReturn: 85, marketValueCurrent: 72, intrinsicValueCurrent: 85, marketValueNextYear: 78, intrinsicValueNextYear: 92, analystTarget: 82, unrestrictedCurrent: 85, unrestrictedNextYear: 95 },
    { date: '2023', price: 80, totalReturn: 105, marketValueCurrent: 85, intrinsicValueCurrent: 100, marketValueNextYear: 92, intrinsicValueNextYear: 108, analystTarget: 98, unrestrictedCurrent: 100, unrestrictedNextYear: 115 },
    { date: '2024', price: 95, totalReturn: 125, marketValueCurrent: 100, intrinsicValueCurrent: 115, marketValueNextYear: 108, intrinsicValueNextYear: 125, analystTarget: 115, unrestrictedCurrent: 120, unrestrictedNextYear: 135 },
    { date: '2025', price: 100, totalReturn: 135, marketValueCurrent: 105, intrinsicValueCurrent: 120, marketValueNextYear: 115, intrinsicValueNextYear: 132, analystTarget: 125, unrestrictedCurrent: 130, unrestrictedNextYear: 145 },
  ];

  // 1 Year Price with 6-Month Forecast, MAs, and Bollinger Bands
  const oneYearData = [
    { date: "Jan'25", price: 90, ma50: 88, ma200: 85, upperBand: 98, lowerBand: 82, forecast: null, ci95Upper: null, ci95Lower: null },
    { date: "Mar'25", price: 88, ma50: 89, ma200: 86, upperBand: 96, lowerBand: 80, forecast: null, ci95Upper: null, ci95Lower: null },
    { date: "May'25", price: 95, ma50: 91, ma200: 87, upperBand: 102, lowerBand: 84, forecast: null, ci95Upper: null, ci95Lower: null },
    { date: "Jul'25", price: 92, ma50: 92, ma200: 88, upperBand: 100, lowerBand: 84, forecast: null, ci95Upper: null, ci95Lower: null },
    { date: "Sep'25", price: 98, ma50: 94, ma200: 90, upperBand: 106, lowerBand: 86, forecast: null, ci95Upper: null, ci95Lower: null },
    { date: "Nov'25", price: 100, ma50: 96, ma200: 92, upperBand: 108, lowerBand: 88, forecast: 100, ci95Upper: 108, ci95Lower: 92 },
    { date: "Jan'26", price: null, ma50: null, ma200: null, upperBand: null, lowerBand: null, forecast: 108, ci95Upper: 120, ci95Lower: 96 },
    { date: "Mar'26", price: null, ma50: null, ma200: null, upperBand: null, lowerBand: null, forecast: 115, ci95Upper: 130, ci95Lower: 100 },
  ];

  // NEW: Ichimoku Cloud Data (6-month view with signal markers)
  const ichimokuData = [
    { date: 'Jun', price: 88, tenkan: 87, kijun: 85, senkouA: 84, senkouB: 82, chikou: 85, tkCrossMarker: null, kumoTwistMarker: null },
    { date: 'Jul', price: 92, tenkan: 90, kijun: 87, senkouA: 86, senkouB: 84, chikou: 90, tkCrossMarker: 92, kumoTwistMarker: null }, // TK Bullish Cross
    { date: 'Aug', price: 95, tenkan: 93, kijun: 90, senkouA: 89, senkouB: 86, chikou: 93, tkCrossMarker: null, kumoTwistMarker: null },
    { date: 'Sep', price: 98, tenkan: 96, kijun: 93, senkouA: 92, senkouB: 88, chikou: 96, tkCrossMarker: null, kumoTwistMarker: 92 }, // Kumo Twist Bullish
    { date: 'Oct', price: 96, tenkan: 97, kijun: 95, senkouA: 94, senkouB: 90, chikou: 94, tkCrossMarker: null, kumoTwistMarker: null },
    { date: 'Nov', price: 100, tenkan: 98, kijun: 96, senkouA: 95, senkouB: 92, chikou: 98, tkCrossMarker: null, kumoTwistMarker: null },
  ];

  // NEW: Ichimoku Signals Summary
  const ichimokuSignals = {
    tkCross: 'TK Bullish Cross',
    kumoTwist: 'Kumo Twist Bullish',
    priceVsCloud: 'Above Cloud (Bullish)',
  };

  // MACD Data (recent 6 months)
  const macdData = [
    { date: 'Jun', macd: 0.5, signal: 0.3, histogram: 0.2 },
    { date: 'Jul', macd: 1.2, signal: 0.6, histogram: 0.6 },
    { date: 'Aug', macd: 1.5, signal: 1.0, histogram: 0.5 },
    { date: 'Sep', macd: 1.8, signal: 1.3, histogram: 0.5 },
    { date: 'Oct', macd: 1.2, signal: 1.4, histogram: -0.2 },
    { date: 'Nov', macd: 0.8, signal: 1.2, histogram: -0.4 },
  ];

  // RSI Data (recent 6 months)
  const rsiData = [
    { date: 'Jun', rsi: 45 },
    { date: 'Jul', rsi: 55 },
    { date: 'Aug', rsi: 62 },
    { date: 'Sep', rsi: 68 },
    { date: 'Oct', rsi: 58 },
    { date: 'Nov', rsi: 55 },
  ];

  // Radar Chart Data (normalize all to 0-100 scale)
  const radarData = [
    { metric: 'Rev Growth', value: 70, fullMark: 100 },
    { metric: 'Op Margin', value: 75, fullMark: 100 },
    { metric: 'Gross Margin', value: 65, fullMark: 100 },
    { metric: 'Profit Margin', value: 60, fullMark: 100 },
    { metric: 'ROE', value: 70, fullMark: 100 },
    { metric: 'Risk (CRS)', value: 60, fullMark: 100 },
    { metric: 'Beta Score', value: 70, fullMark: 100 },
    { metric: 'P/Market Disc', value: 50, fullMark: 100 },
    { metric: 'Moat', value: 80, fullMark: 100 },
    { metric: 'FCF Growth', value: 55, fullMark: 100 },
    { metric: 'ROA', value: 65, fullMark: 100 },
    { metric: 'Earn Growth', value: 75, fullMark: 100 },
  ];

  // Key Notes Content - from Bull/Bear case analysis
  const bullCase = {
    target: "€130-150",  // Bull case price target
    points: [
      "Strong revenue growth momentum",
      "Expanding margins",
      "Market leadership position",
      "Favorable industry tailwinds",
      "Strong balance sheet"
    ]
  };

  const bearCase = {
    target: "€70-80",  // Bear case price target
    points: [
      "Valuation compression risk",
      "Competitive pressures",
      "Macro sensitivity",
      "Execution risks",
      "Key person dependency"
    ]
  };

  const entryStrategy = {
    idealEntry: "€90-95",  // From Entry Strategy section
    currentEntry: "€100 acceptable",
    target: "€120 (+20%)",  // 12-month target
    stopLoss: "€85 (-15%)",  // Stop loss
    positionSize: "2-3%"  // Recommended allocation
  };

  // ============================================================
  // COMPONENT CODE (Standard - use as-is)
  // ============================================================

  // Helper: Value Trap color (LOWER = genuine = green, HIGHER = trap = red)
  const getValueTrapColor = (score) => {
    if (score < 40) return 'bg-green-100 border-green-400 text-green-800';
    if (score < 60) return 'bg-yellow-100 border-yellow-400 text-yellow-800';
    return 'bg-red-100 border-red-400 text-red-800';
  };

  // Helper: Get label for Value Trap score
  const getValueTrapLabel = (score) => {
    if (score < 20) return 'Genuine';
    if (score < 40) return 'Probably Genuine';
    if (score < 60) return 'Caution';
    if (score < 80) return 'Likely Trap';
    return 'Strong Trap';
  };

  // Helper: Persona score color
  const getPersonaColor = (score) => {
    if (score >= 7) return 'bg-green-500';
    if (score >= 4) return 'bg-yellow-500';
    return 'bg-red-500';
  };

  // Helper: News sentiment color
  const getSentimentColor = (sentiment) => {
    if (sentiment > 0.3) return 'text-green-600';
    if (sentiment > 0) return 'text-green-500';
    if (sentiment > -0.3) return 'text-yellow-600';
    return 'text-red-600';
  };

  // Persona Badge Component
  const PersonaBadge = ({ name, score, position }) => (
    <div className={`absolute ${position} flex flex-col items-center`}>
      <div className={`w-6 h-6 rounded-full ${getPersonaColor(score)} flex items-center justify-center text-white text-[8px] font-bold`}>
        {score.toFixed(1)}
      </div>
      <div className="text-[7px] text-gray-600 mt-0.5">{name}</div>
    </div>
  );

  const MetricBox = ({ label, value, benchmark, isGood, size = 'normal' }) => {
    let bgColor = 'bg-gray-50';
    if (isGood === true) bgColor = 'bg-green-50 border-green-200';
    if (isGood === false) bgColor = 'bg-red-50 border-red-200';
    if (isGood === 'neutral') bgColor = 'bg-yellow-50 border-yellow-200';

    return (
      <div className={`${bgColor} border p-1.5 flex flex-col justify-center items-center`}>
        <div className="text-base font-bold text-gray-900">{value}</div>
        <div className="text-[9px] text-gray-600 text-center leading-tight">{label}</div>
        {benchmark && <div className="text-[8px] text-gray-400">{benchmark}</div>}
      </div>
    );
  };

  const SectionHeader = ({ title, bgColor }) => (
    <div className={`${bgColor} px-2 py-1 text-[10px] font-bold text-gray-700`}>
      {title}
    </div>
  );

  return (
    <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}>
            <LineChart data={priceHistory}>
              <CartesianGrid strokeDasharray="3 3" stroke="#e0e0e0" />
              <XAxis dataKey="date" tick={{ fontSize: 7 }} />
              <YAxis tick={{ fontSize: 7 }} scale="log" domain={['auto', 'auto']} />
              <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="unrestrictedCurrent" stroke="#dc2626" strokeWidth={1} strokeDasharray="5 5" dot={false} name="Unrestr Current" />
              <Line type="monotone" dataKey="unrestrictedNextYear" stroke="#f97316" strokeWidth={1} strokeDasharray="5 5" dot={false} name="Unrestr Next" />
            </LineChart>
          </ResponsiveContainer>
          <div className="text-xs font-bold mt-1 mb-1 text-center">RSI (14) = {rsiData[rsiData.length - 1].rsi}</div>
          <ResponsiveContainer width="100%" height={55}>
            <LineChart data={rsiData}>
              <CartesianGrid strokeDasharray="3 3" stroke="#e0e0e0" />
              <XAxis dataKey="date" tick={{ fontSize: 6 }} />
              <YAxis tick={{ fontSize: 6 }} domain={[0, 100]} />
              <Tooltip contentStyle={{ fontSize: 7 }} />
              <ReferenceLine y={70} stroke="#ef4444" strokeDasharray="2 2" />
              <ReferenceLine y={30} stroke="#22c55e" strokeDasharray="2 2" />
              <Line type="monotone" dataKey="rsi" stroke="#f59e0b" strokeWidth={1.5} dot={false} />
            </LineChart>
          </ResponsiveContainer>
        </div>
      </div>

      {/* NEW: Ichimoku Cloud Chart */}
      <div className="border border-gray-300 rounded p-2 mb-3">
        <div className="text-sm font-bold mb-1 text-center">ICHIMOKU CLOUD</div>
        <div className="flex gap-4 text-[7px] justify-center mb-1">
          <span>— Close Price</span>
          <span className="text-blue-500">— Tenkan-sen (9)</span>
          <span className="text-red-500">— Kijun-sen (26)</span>
          <span className="text-gray-400">— Chikou Span</span>
          <span className="text-green-500">▒ Senkou Span A/B (Cloud)</span>
          <span className="ml-2 font-bold text-yellow-600">◆ TK Cross</span>
          <span className="text-purple-600">◆ Kumo Twist</span>
        </div>
        <ResponsiveContainer width="100%" height={100}>
          <ComposedChart data={ichimokuData}>
            <CartesianGrid strokeDasharray="3 3" stroke="#e0e0e0" />
            <XAxis dataKey="date" tick={{ fontSize: 7 }} />
            <YAxis tick={{ fontSize: 7 }} domain={['auto', 'auto']} />
            <Tooltip contentStyle={{ fontSize: 8 }} />
            <Area type="monotone" dataKey="senkouA" stroke="none" fill="#86efac" fillOpacity={0.3} />
            <Area type="monotone" dataKey="senkouB" stroke="none" fill="#fca5a5" fillOpacity={0.3} />
            <Line type="monotone" dataKey="price" stroke="#1f2937" strokeWidth={2} dot={false} name="Price" />
            <Line type="monotone" dataKey="tenkan" stroke="#3b82f6" strokeWidth={1} dot={false} name="Tenkan" />
            <Line type="monotone" dataKey="kijun" stroke="#dc2626" strokeWidth={1} dot={false} name="Kijun" />
            <Line type="monotone" dataKey="chikou" stroke="#9ca3af" strokeWidth={1} strokeDasharray="3 3" dot={false} name="Chikou" />
            <Scatter dataKey="tkCrossMarker" fill="#9333ea" shape="diamond" name="TK Cross" />
            <Scatter dataKey="kumoTwistMarker" fill="#dc2626" shape="diamond" name="Kumo Twist" />
          </ComposedChart>
        </ResponsiveContainer>
        <div className="flex gap-4 text-[8px] justify-center mt-1">
          <span className="bg-green-100 px-2 rounded">{ichimokuSignals.tkCross}</span>
          <span className="bg-green-100 px-2 rounded">{ichimokuSignals.kumoTwist}</span>
          <span className="bg-green-100 px-2 rounded">{ichimokuSignals.priceVsCloud}</span>
        </div>
      </div>

      {/* Key Notes (Expandable) */}
      <div className="border border-gray-300 rounded overflow-hidden">
        <button 
          onClick={() => setShowKeyNotes(!showKeyNotes)}
          className="w-full bg-gray-100 px-3 py-2 text-left text-sm font-bold flex items-center hover:bg-gray-200"
        >
          <span className="mr-2">{showKeyNotes ? '▼' : '▶'}</span> Key Notes (Click to Expand)
        </button>
        {showKeyNotes && (
          <div className="p-3 bg-gray-50">
            <div className="grid grid-cols-3 gap-4 text-xs">
              {/* Bull Case */}
              <div>
                <div className="font-bold text-green-700 mb-2 text-sm">BULL CASE ({bullCase.target})</div>
                <ul className="list-disc list-inside space-y-1">
                  {bullCase.points.map((point, i) => <li key={i}>{point}</li>)}
                </ul>
              </div>
              {/* Bear Case */}
              <div>
                <div className="font-bold text-red-700 mb-2 text-sm">BEAR CASE ({bearCase.target})</div>
                <ul className="list-disc list-inside space-y-1">
                  {bearCase.points.map((point, i) => <li key={i}>{point}</li>)}
                </ul>
              </div>
              {/* Entry/Exit Strategy */}
              <div>
                <div className="font-bold text-blue-700 mb-2 text-sm">ENTRY/EXIT STRATEGY</div>
                <ul className="list-disc list-inside space-y-1">
                  <li><strong>Ideal Entry:</strong> {entryStrategy.idealEntry}</li>
                  <li><strong>Current:</strong> {entryStrategy.currentEntry}</li>
                  <li><strong>Target:</strong> {entryStrategy.target}</li>
                  <li><strong>Stop Loss:</strong> {entryStrategy.stopLoss}</li>
                  <li><strong>Position Size:</strong> {entryStrategy.positionSize}</li>
                </ul>
              </div>
            </div>
          </div>
        )}
      </div>

      {/* Footer */}
      <div className="text-xs text-gray-500 text-center mt-3">
        Analysis Date: {analysisDate} | Sources: SEC Filings, Company Reports | 
        <span className="font-bold text-blue-600 ml-1">{recommendation}</span>
      </div>
    </div>
  );
};

export default QuantDashboard;

Implementation Instructions

CRITICAL STEPS:

Calculate all metrics during the comprehensive text analysis
Store metrics in variables as you calculate them
After completing full text analysis, create the React artifact
Replace ALL placeholder values in the template with actual calculated data
Use the EXACT template structure - do not modify the component code
Populate these specific data arrays:
- metrics object (60+ values including investor persona scores)
- topNews array (5 recent headlines with dates)
- priceHistory array (10-year data with multiple valuation lines)
- oneYearData array (with MAs, Bollinger Bands, forecast)
- ichimokuData array (6-month with signal markers)
- ichimokuSignals object (TK cross, Kumo twist, price vs cloud)
- macdData array (6 recent points with histogram)
- rsiData array (6 recent points)
- radarData array (12 metrics, normalized 0-100)
- bullCase.points (5 points from bull case analysis)
- bearCase.points (5 points from bear case analysis)
- entryStrategy (5 values from entry/exit strategy)
Normalize radar chart values properly:
- Each metric on 0-100 scale
- Higher is always better (invert risk/beta if needed)
- Use scaling formulas provided above
Format values correctly:
- Currency: "€100.00" (Euro is the default - use € not $)
- Large numbers: "€10B", "€2.5M"
- Percentages: 15.0 (number, not string with %)
- Ratios: 1.25 (number)
- Scores: 7 (integer) or 75.0 (float)
Growth metrics:
- Use REPORTED revenue growth (not underlying/organic)
- Use REPORTED earnings growth (not adjusted EPS growth)
DO NOT:
- Leave placeholder values
- Modify the component structure
- Skip any sections
- Use estimated/guessed data

This is the ONLY accepted dashboard format. All other dashboard styles are deprecated.

Integration with Project Context

Portfolio Awareness

Access portfolio data from project knowledge
Check if stock is already owned (if so, suggest using Portfolio Analyst)
Assess fit with existing holdings (sector exposure, correlation)
Consider position sizing in context of current allocations

Investment Profile

User's investment timeline, risk tolerance, preferences in project instructions
Tailor recommendations to user's profile
Consider tax implications from user's context
Adjust position sizing based on portfolio size and risk tolerance

Avoiding Duplication

If stock is already in portfolio: - Acknowledge: "You already own [SYMBOL]. For analysis of your existing position, use the Portfolio Analyst skill." - Still provide evaluation if user wants fresh assessment - Frame as "Should you add more?" rather than initial purchase

When to Use This Skill

Use Stock Evaluator when: - User asks "Should I buy [stock]?" - User wants evaluation of watchlist candidates - User requests stock recommendations - User asks "Is [stock] a good investment?" - User wants to compare multiple potential investments - User asks for alternatives to a stock they're considering - User wants entry price and position sizing guidance - User requests a "quant-style dashboard" or "stock visualization"

Do NOT use this skill when: - User wants to review existing portfolio positions → Use Portfolio Analyst - User wants general market commentary → Regular knowledge - User wants stock screening/discovery → Different workflow - User asks about options, derivatives, crypto → Out of scope

Output includes: - Comprehensive text analysis (all sections above) - Quant-style React dashboard artifact (standardized visual format)

Best Practices

Research Approach

Start with company filings (10-K, 10-Q) - NOT news articles
Go back 5-10 years - Understand evolution, not just current state
Compare to 3-5 peers - Apples to apples comparison
Multiple valuation methods - Don't rely on single approach
Present both sides - Bull and bear cases fairly
Be specific - Use actual data, not generalities

Valuation Discipline

Always require minimum 15% margin of safety
Use conservative assumptions in DCF
Weight multiple valuation methods
Consider industry-specific norms
Don't overpay for growth

Risk Awareness

Explicitly identify and quantify risks
Consider probability and impact
Acknowledge unknowns honestly
Don't just focus on upside

Communication

Lead with clear recommendation
Support every claim with evidence
Use specific numbers and dates
Explain reasoning, don't just state conclusions
Make recommendations unmistakable

Common Patterns to Recognize

Quality Companies

Consistent profitability over full cycle (5-10 years)
Strong balance sheet (low debt, high cash)
Competitive moats (wide or narrow)
Shareholder-friendly capital allocation
Predictable business model

Value Traps (AVOID)

Cheap for a reason (declining business)
High debt with weak cash flow
Losing market share consistently
No competitive advantages
Poor management capital allocation

Growth at Reasonable Price (GARP)

Strong revenue growth (15-25%+)
Expanding margins
Large addressable market
Competitive advantages
Reasonable valuation (PEG < 1.5)

Turnaround Candidates

New management with track record
Improving key metrics quarter-over-quarter
Catalyst for change
Deep value with margin of safety
Reduced debt or improved cash flow

Quality Checks Before Finalizing

Before presenting analysis, verify:

DATA INTEGRITY CHECKS (CRITICAL - CHECK FIRST)

✅ Every numeric metric has a cited source from web search?
✅ No insider activity fabricated? (SEC Form 4 or N/A)
✅ No short interest fabricated? (FINRA/exchange or N/A)
✅ ROE benchmark correct? (>20% = green, 10-20% = yellow, <10% = red)
✅ Standardized metric labels used? (e.g., "Operative Margin", not "Operating")
✅ All unavailable data shows "N/A"? (NEVER zeros or estimates)
✅ TOP NEWS format correct? (pipe-separated, dates at END in brackets)
✅ Valuation indicator displayed below forecast? (Undervalued/Fairly Valued/Overvalued +/- %)
✅ Beta + Vol 1Y combined in one cell?
✅ Sector/Industry combined in one cell?

ANALYSIS COMPLETENESS CHECKS

✅ All mandatory deliverables completed?
✅ Multiple valuation methods used?
✅ Both bull and bear cases presented?
✅ Clear BUY/HOLD/SELL recommendation?
✅ Specific entry price and position size?
✅ 3-5 peer companies compared?
✅ 5-10 year financial trends analyzed?
✅ Research based on company filings, not news?
✅ Margin of safety calculated?
✅ Risk level assessed?
✅ If SELL: 3-5 alternatives provided?
✅ Technical entry points identified?
✅ Advanced metrics calculated (Piotroski F, Altman Z, Beneish M, Max Drawdown)?
✅ All monetary values in € (Euro)?
✅ Revenue/Earnings growth using REPORTED (not underlying/adjusted) figures?
✅ Value Trap Score calculated (0-100, LOWER = genuine)?
✅ All 8 Investor Persona Scores calculated (0-10)?
✅ PEG ratio calculated?
✅ FCF Margin calculated?
✅ Greenblatt Magic Formula metrics (EY, ROC)?
✅ News sentiment and short interest researched?
✅ Ichimoku Cloud data gathered with signal markers?
✅ TOP NEWS section populated (5 recent headlines)?
✅ 10-year price history with valuation lines available?
✅ Enhanced dashboard created with ALL 60+ metrics populated?

FINAL VALIDATION QUESTIONS

Can you cite source for EVERY number in the dashboard?
Did any metric come from training knowledge alone? (If yes, search again or use N/A)
Are insider buys/sells from SEC Form 4 specifically? (If not found, use N/A)

If any checklist item incomplete: STOP and gather more information. If data genuinely unavailable after searching: Use "N/A" - never fabricate.

Example Evaluation Structure

[See complete example in EVALUATION-WORKFLOWS.md for detailed walkthrough]

Continuous Improvement

After each evaluation: - Track recommendation outcomes - Learn from what worked/didn't work - Refine valuation assumptions - Improve pattern recognition - Update industry knowledge

The goal is to discover genuinely attractive investment opportunities that fit the user's profile with adequate margin of safety and acceptable risk.