Stock Evaluator

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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.

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

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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

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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)

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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)

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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

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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

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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]

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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 4-6, 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 }) => (
    
absolute ${position} flex flex-col items-center}>
      
w-6 h-6 rounded-full ${getPersonaColor(score)} flex items-center justify-center text-white text-[8px] font-bold}>
        {score.toFixed(1)}
      
      
{name}
    
  );
  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 (
      
${bgColor} border p-1.5 flex flex-col justify-center items-center}>
        
{value}
        
{label}
        {benchmark && 
{benchmark}
}
      
    );
  };
  const SectionHeader = ({ title, bgColor }) => (
    
${bgColor} px-2 py-1 text-[10px] font-bold text-gray-700}>
      {title}
    
  );
  return (
    

      {/* Header */}
      

        {ticker} - {companyName}
      
      {/* TOP NEWS - Pipe separated with dates at END */}
      

        TOP NEWS:
        
{topNewsString}
      
      {/* Top 4 sections */}
      

        {/* Price & Valuation - Updated with dual PEG */}
        

          
          

            €${metrics.price}} />
            
            
            (${metrics.subsectorTypicalPE})} isGood={metrics.forwardPE < metrics.subsectorTypicalPE} />
            
            
            
          
        
        {/* Financial Performance */}
        

          
          

            ${metrics.roe}%} benchmark="(>20%)" isGood={metrics.roe >= 20 ? true : metrics.roe >= 10 ? 'neutral' : false} />
            ${metrics.roa}%} benchmark="(>10%)" isGood={metrics.roa >= 10} />
            ${metrics.profitMargin}%} benchmark="(>20%)" isGood={metrics.profitMargin >= 20 ? true : metrics.profitMargin >= 10 ? 'neutral' : false} />
            ${metrics.opMargin}%} benchmark="(>20%)" isGood={metrics.opMargin >= 20} />
            ${metrics.grossMargin}%} benchmark="(>40%)" isGood={metrics.grossMargin >= 40} />
            ${metrics.roic}%} benchmark="(>15%)" isGood={metrics.roic >= 15} />
          
        
      
      {/* Next 4 sections */}
      

        {/* Growth Metrics */}
        

          
          

            ${metrics.revGrowth}%} benchmark="(>10%)" isGood={metrics.revGrowth >= 10} />
            ${metrics.earnGrowth}%} benchmark="(>0%)" isGood={metrics.earnGrowth >= 0} />
            €${metrics.epsTTM}} />
            €${metrics.forwardEPS}} isGood={metrics.forwardEPS > metrics.epsTTM} />
            Capped: ${metrics.growthCapped}%} benchmark={Uncapped: ${metrics.growthUncapped}%} />
            €${metrics.analystTarget}} />
          
        
        {/* Risk Indicators */}
        

          
          

            
            
            = 7 ? true : metrics.fScore >= 4 ? 'neutral' : false} />
            = 2.99 ? true : metrics.zScore >= 1.81 ? 'neutral' : false} />
            
            ${metrics.valueTrapScore} (${metrics.valueTrapLabel})} isGood={metrics.valueTrapScore < 40 ? true : metrics.valueTrapScore < 60 ? 'neutral' : false} />
          
        
      
      {/* Next 4 sections */}
      

        {/* Liquidity & Free Cash Flow */}
        

          
          

            = 1 && metrics.currentRatio <= 2 ? true : 'neutral'} />
            
            
            ${metrics.fcfGrowth5Y}%} benchmark="(>5%)" isGood={metrics.fcfGrowth5Y >= 5} />
            ${metrics.fcfYield}%} benchmark="(>4%)" isGood={metrics.fcfYield >= 4} />
            ${metrics.fcfMargin}%} benchmark="(>15%)" isGood={metrics.fcfMargin >= 15 ? true : metrics.fcfMargin >= 10 ? 'neutral' : false} />
            ${metrics.payoutRatio}%} benchmark="(<50%)" isGood={metrics.payoutRatio < 50} />
          
        
        {/* Insider & Sentiment & Class */}
        

          
          

             metrics.insSells} />
            
            
            ${metrics.shortInterest}%} isGood={metrics.shortInterest < 5 ? true : metrics.shortInterest < 10 ? 'neutral' : false} />
            ${metrics.newsSentiment > 0 ? '+' : ''}${metrics.newsSentiment.toFixed(3)} / ${metrics.newsArticleCount}} benchmark={metrics.newsSentiment > 0 ? '(Positive)' : '(Negative)'} isGood={metrics.newsSentiment > 0} />
            Stock: ${metrics.stockType}} value={Div Yield: ${metrics.divYield}%} />
            ${metrics.sector} /} benchmark={metrics.industry} />
          
        
      
      {/* Last 2 sections */}
      

        {/* Quality Scores */}
        

          
          

            = 70 ? true : metrics.cqvs >= 50 ? 'neutral' : false} />
            
            = 70} />
            = 70 ? true : metrics.quality >= 50 ? 'neutral' : false} />
            = 70} />
            = 70 ? true : metrics.integrity >= 50 ? 'neutral' : false} />
          
        
        {/* Moat & Other */}
        

          
          

            = 7 ? true : metrics.buffettMoat >= 4 ? 'neutral' : false} />
            EY: ${metrics.greenblattEY}%} benchmark={metrics.greenblattROC ? ROC: ${metrics.greenblattROC}% : 'ROC: N/A'} isGood={metrics.greenblattEY >= 8 ? true : metrics.greenblattEY >= 4 ? 'neutral' : false} />
            Beta: ${metrics.beta}} value={Vol 1Y: ${metrics.vol1Y}%} isGood={metrics.beta < 1 ? true : metrics.beta < 1.5 ? 'neutral' : false} />
            ${metrics.earningsPredict}%} benchmark="(>80%)" isGood={metrics.earningsPredict >= 80 ? true : metrics.earningsPredict >= 60 ? 'neutral' : false} />
            ${metrics.maxDrawdown}%} benchmark={metrics.maxDrawdown > -30 ? '(Low)' : metrics.maxDrawdown > -50 ? '(Mid)' : '(High)'} isGood={metrics.maxDrawdown > -30 ? true : metrics.maxDrawdown > -50 ? 'neutral' : false} />
            Completeness: ${metrics.completeness}%} value={Data Quality: ${metrics.dataQuality}} isGood={metrics.dataQuality === 'High' ? true : metrics.dataQuality === 'Medium' ? 'neutral' : false} />
          
        
      
      {/* Charts Section - Enhanced with Legends */}
      

        {/* Linear Price Chart + MACD */}
        

          
LINEAR PRICE CHART (10Y)
          

            — Close Price — Total Return

            - - Market Value (Current): €{metrics.marketValueCurrent}

            - - Intrinsic Value (Current): €{metrics.intrinsicValueCurrent}

            - - Analyst Target: €{metrics.analystTarget}
          
          
            
              
              
              
              
              
              
              
              
            
          
          
MACD
          
            
              
              
              
              
              
              
              
            
          
        
        {/* Radar + Investor Personas + Forecast */}
        

          

            
              
                
                
                
                
              
            
            {/* Investor Persona Badges */}
            
            
            
            
            
            
            
            
          
          

            
              Advice: {recommendation} (CQVS: {metrics.cqvs.toFixed(1)})
            
          
          
1Y PRICE + 6-MONTH FORECAST
          
— Close — 50-Day MA — 200-Day MA ▒ Bollinger Bands - - Forecast
          
            
              
              
              
              
              
              
              
              
              
              
            
          
          {/* Valuation Indicator */}
          
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}%)
          
        
        {/* Log Price + RSI */}
        

          
LOG PRICE CHART (10Y)
          

            — Close Price — Total Return

            - - Unrestr. Market Value (Current): €{metrics.unrestrictedMarketValueCurrent}

            - - Unrestr. Market Value (Next Year): €{metrics.unrestrictedMarketValueNextYear}
          
          
            
              
              
              
              
              
              
              
              
            
          
          
RSI (14) = {rsiData[rsiData.length - 1].rsi}
          
            
              
              
              
              
              
              
              
            
          
        
      
      {/* NEW: Ichimoku Cloud Chart */}
      

        
ICHIMOKU CLOUD
        

          — Close Price
          — Tenkan-sen (9)
          — Kijun-sen (26)
          — Chikou Span
          ▒ Senkou Span A/B (Cloud)
          ◆ TK Cross
          ◆ Kumo Twist
        
        
          
            
            
            
            
            
            
            
            
            
            
            
            
          
        
        

          {ichimokuSignals.tkCross}
          {ichimokuSignals.kumoTwist}
          {ichimokuSignals.priceVsCloud}
        
      
      {/* Key Notes (Expandable) */}
      

         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"
        >
          {showKeyNotes ? '▼' : '▶'} Key Notes (Click to Expand)
        
        {showKeyNotes && (
          

            

              {/* Bull Case */}
              

                
BULL CASE ({bullCase.target})
                

                  {bullCase.points.map((point, i) => 
{point}
)}
                
              
              {/* Bear Case */}
              

                
BEAR CASE ({bearCase.target})
                

                  {bearCase.points.map((point, i) => 
{point}
)}
                
              
              {/* Entry/Exit Strategy */}
              

                
ENTRY/EXIT STRATEGY
                

                  
Ideal Entry: {entryStrategy.idealEntry}
                  
Current: {entryStrategy.currentEntry}
                  
Target: {entryStrategy.target}
                  
Stop Loss: {entryStrategy.stopLoss}
                  
Position Size: {entryStrategy.positionSize}
                
              
            
          
        )}
      
      {/* Footer */}
      

        Analysis Date: {analysisDate} | Sources: SEC Filings, Company Reports | 
        {recommendation}
      
    
  );
};
export default QuantDashboard;

Implementation Instructions

CRITICAL STEPS:

1. Calculate all metrics during the comprehensive text analysis 2. Store metrics in variables as you calculate them 3. After completing full text analysis, create the React artifact 4. Replace ALL placeholder values in the template with actual calculated data 5. Use the EXACT template structure - do not modify the component code 6. 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)

6. 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

7. 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)

8. Growth metrics: - Use REPORTED revenue growth (not underlying/organic) - Use REPORTED earnings growth (not adjusted EPS growth)

9. 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

1. Start with company filings (10-K, 10-Q) - NOT news articles 2. Go back 5-10 years - Understand evolution, not just current state 3. Compare to 3-5 peers - Apples to apples comparison 4. Multiple valuation methods - Don't rely on single approach 5. Present both sides - Bull and bear cases fairly 6. 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)

1. ✅ Every numeric metric has a cited source from web search? 2. ✅ No insider activity fabricated? (SEC Form 4 or N/A) 3. ✅ No short interest fabricated? (FINRA/exchange or N/A) 4. ✅ ROE benchmark correct? (>20% = green, 10-20% = yellow, <10% = red) 5. ✅ Standardized metric labels used? (e.g., "Operative Margin", not "Operating") 6. ✅ All unavailable data shows "N/A"? (NEVER zeros or estimates) 7. ✅ TOP NEWS format correct? (pipe-separated, dates at END in brackets) 8. ✅ Valuation indicator displayed below forecast? (Undervalued/Fairly Valued/Overvalued +/- %) 9. ✅ Beta + Vol 1Y combined in one cell? 10. ✅ Sector/Industry combined in one cell?

ANALYSIS COMPLETENESS CHECKS

11. ✅ All mandatory deliverables completed? 12. ✅ Multiple valuation methods used? 13. ✅ Both bull and bear cases presented? 14. ✅ Clear BUY/HOLD/SELL recommendation? 15. ✅ Specific entry price and position size? 16. ✅ 3-5 peer companies compared? 17. ✅ 5-10 year financial trends analyzed? 18. ✅ Research based on company filings, not news? 19. ✅ Margin of safety calculated? 20. ✅ Risk level assessed? 21. ✅ If SELL: 3-5 alternatives provided? 22. ✅ Technical entry points identified? 23. ✅ Advanced metrics calculated (Piotroski F, Altman Z, Beneish M, Max Drawdown)? 24. ✅ All monetary values in € (Euro)? 25. ✅ Revenue/Earnings growth using REPORTED (not underlying/adjusted) figures? 26. ✅ Value Trap Score calculated (0-100, LOWER = genuine)? 27. ✅ All 8 Investor Persona Scores calculated (0-10)? 28. ✅ PEG ratio calculated? 29. ✅ FCF Margin calculated? 30. ✅ Greenblatt Magic Formula metrics (EY, ROC)? 31. ✅ News sentiment and short interest researched? 32. ✅ Ichimoku Cloud data gathered with signal markers? 33. ✅ TOP NEWS section populated (5 recent headlines)? 34. ✅ 10-year price history with valuation lines available? 35. ✅ 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.

Research Approach

1. Start with company filings (10-K, 10-Q) - NOT news articles 2. Go back 5-10 years - Understand evolution, not just current state 3. Compare to 3-5 peers - Apples to apples comparison 4. Multiple valuation methods - Don't rely on single approach 5. Present both sides - Bull and bear cases fairly 6. 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

---