baladengale Fundamental Trend Analysis — Composite Buy/Sell Signal Engine
Plain-language guide for generating a comprehensive stock analysis that combines fundamental scoring (financial health, valuation, profitability, growth) with technical trend signals (moving averages, momentum, price action) to produce a clear 6-tier rating from Must Buy (✅✅✅) to Must Sell (❌❌❌).
This skill is inspired by proven quantitative frameworks: Piotroski F-Score, Altman Z-Score, and composite scoring systems used by Danelfin, Tickeron, and institutional quant desks.
When to Activate
Activate when the user asks about:
- Stock analysis, fundamental analysis, should I buy/sell
- Stock rating, stock score, stock signal
- Fundamental trend, composite score
- Buy signal, sell signal, strong buy, must buy
- Is [TICKER] a good buy, rate this stock
- Analyze [TICKER] fundamentals
Architecture Overview
┌─────────────────────────────────────────────────────┐
│ COMPOSITE SIGNAL ENGINE │
│ │
│ ┌──────────────────┐ ┌──────────────────────┐ │
│ │ FUNDAMENTAL │ │ TECHNICAL TREND │ │
│ │ SCORE (0-100) │ │ SCORE (0-100) │ │
│ │ │ │ │ │
│ │ Profitability 25 │ │ MA Alignment 25 │ │
│ │ Valuation 25 │ │ Momentum 25 │ │
│ │ Financial Hlth 25│ │ Price Action 25 │ │
│ │ Growth 25 │ │ Volume Trend 25 │ │
│ └────────┬──────────┘ └───────────┬───────────┘ │
│ │ │ │
│ └─────────┬─────────────────┘ │
│ ▼ │
│ ┌──────────────────┐ │
│ │ COMPOSITE SCORE │ │
│ │ Fundamental × 60%│ │
│ │ Technical × 40%│ │
│ └────────┬─────────┘ │
│ ▼ │
│ ✅✅✅ Must Buy · ✅✅ Strong Buy · ✅ Buy │
│ ⚪ Hold · ❌ Sell · ❌❌ Strong Sell │
│ ❌❌❌ Must Sell │
└─────────────────────────────────────────────────────┘
Step 1 — Fetch Fundamental Data from Yahoo Finance
Fetch all fundamental data needed for scoring in a single call:
# Fetch comprehensive fundamentals for a ticker
TICKER="NVDA"
curl -s "https://query2.finance.yahoo.com/v10/finance/quoteSummary/${TICKER}?modules=financialData,defaultKeyStatistics,summaryDetail,incomeStatementHistory,incomeStatementHistoryQuarterly,balanceSheetHistory,balanceSheetHistoryQuarterly,cashflowStatementHistory,earnings,earningsTrend" \
-H "User-Agent: Mozilla/5.0" | jq '.quoteSummary.result[0]'
Key fields to extract:
| Category | Fields | Source Module |
|---|---|---|
| Profitability | returnOnEquity, returnOnAssets, profitMargins, operatingCashflow, netIncomeToCommon |
financialData |
| Valuation | trailingPE, forwardPE, priceToBook, pegRatio, enterpriseToEbitda |
defaultKeyStatistics, summaryDetail |
| Financial Health | debtToEquity, currentRatio, quickRatio, totalDebt, totalCash |
financialData |
| Growth | revenueGrowth, earningsGrowth, earningsQuarterlyGrowth |
financialData, earningsTrend |
| Price Context | fiftyTwoWeekHigh, fiftyTwoWeekLow, fiftyDayAverage, twoHundredDayAverage |
summaryDetail |
Step 2 — Fetch Technical / Price Data
# Historical price data — 1 year daily for MA/momentum calculations
curl -s "https://query2.finance.yahoo.com/v8/finance/chart/${TICKER}?range=1y&interval=1d" \
-H "User-Agent: Mozilla/5.0" | jq '{
closes: .chart.result[0].indicators.quote[0].close,
volumes: .chart.result[0].indicators.quote[0].volume,
highs: .chart.result[0].indicators.quote[0].high,
lows: .chart.result[0].indicators.quote[0].low,
timestamps: .chart.result[0].timestamp
}'
# Current quote for latest price and change
curl -s "https://query2.finance.yahoo.com/v7/finance/quote?symbols=${TICKER}" \
-H "User-Agent: Mozilla/5.0" | jq '.quoteResponse.result[0] | {
regularMarketPrice,
regularMarketChangePercent,
regularMarketVolume,
averageDailyVolume3Month,
fiftyDayAverage,
twoHundredDayAverage,
fiftyTwoWeekHigh,
fiftyTwoWeekLow
}'
Step 3 — Calculate Fundamental Score (0–100)
The fundamental score is divided into 4 pillars, each worth 25 points max.
Pillar 1: Profitability (0–25 points)
Based on the Piotroski F-Score profitability criteria, extended with margin quality.
| Metric | Condition | Points |
|---|---|---|
| Return on Equity (ROE) | > 15% = 7pts, > 10% = 5pts, > 5% = 3pts, > 0% = 1pt | 0–7 |
| Return on Assets (ROA) | > 10% = 6pts, > 5% = 4pts, > 2% = 2pts, > 0% = 1pt | 0–6 |
| Profit Margin | > 20% = 6pts, > 10% = 4pts, > 5% = 2pts, > 0% = 1pt | 0–6 |
| Operating Cash Flow Positive | Yes = 3pts, and OCF > Net Income = +3pts | 0–6 |
| Pillar Total | 0–25 |
Scoring logic:
profitability_score = 0
# ROE scoring
if roe > 0.15: profitability_score += 7
elif roe > 0.10: profitability_score += 5
elif roe > 0.05: profitability_score += 3
elif roe > 0: profitability_score += 1
# ROA scoring
if roa > 0.10: profitability_score += 6
elif roa > 0.05: profitability_score += 4
elif roa > 0.02: profitability_score += 2
elif roa > 0: profitability_score += 1
# Profit margin scoring
if profit_margin > 0.20: profitability_score += 6
elif profit_margin > 0.10: profitability_score += 4
elif profit_margin > 0.05: profitability_score += 2
elif profit_margin > 0: profitability_score += 1
# Cash flow quality
if operating_cashflow > 0: profitability_score += 3
if operating_cashflow > net_income: profitability_score += 3
profitability_score = min(profitability_score, 25)
Pillar 2: Valuation (0–25 points)
Measures whether the stock is fairly priced relative to its earnings, book value, and growth.
| Metric | Condition | Points |
|---|---|---|
| Trailing P/E | < 15 = 7pts, < 20 = 5pts, < 30 = 3pts, < 50 = 1pt, ≥ 50 or negative = 0 | 0–7 |
| Forward P/E | < Trailing P/E (improving) = 4pts, within 10% = 2pts | 0–4 |
| Price-to-Book | < 1.5 = 5pts, < 3 = 3pts, < 5 = 2pts, < 10 = 1pt | 0–5 |
| PEG Ratio | < 1.0 = 5pts, < 1.5 = 3pts, < 2.0 = 2pts, < 3.0 = 1pt | 0–5 |
| EV/EBITDA | < 10 = 4pts, < 15 = 3pts, < 20 = 2pts, < 30 = 1pt | 0–4 |
| Pillar Total | 0–25 |
Scoring logic:
valuation_score = 0
# Trailing P/E (lower is better for value)
if 0 < trailing_pe < 15: valuation_score += 7
elif trailing_pe < 20: valuation_score += 5
elif trailing_pe < 30: valuation_score += 3
elif trailing_pe < 50: valuation_score += 1
# Forward P/E improvement (earnings expected to grow)
if forward_pe > 0 and trailing_pe > 0:
if forward_pe < trailing_pe * 0.90: valuation_score += 4
elif forward_pe < trailing_pe: valuation_score += 2
# Price-to-Book
if 0 < price_to_book < 1.5: valuation_score += 5
elif price_to_book < 3: valuation_score += 3
elif price_to_book < 5: valuation_score += 2
elif price_to_book < 10: valuation_score += 1
# PEG Ratio (growth-adjusted P/E)
if 0 < peg < 1.0: valuation_score += 5
elif peg < 1.5: valuation_score += 3
elif peg < 2.0: valuation_score += 2
elif peg < 3.0: valuation_score += 1
# EV/EBITDA
if 0 < ev_ebitda < 10: valuation_score += 4
elif ev_ebitda < 15: valuation_score += 3
elif ev_ebitda < 20: valuation_score += 2
elif ev_ebitda < 30: valuation_score += 1
valuation_score = min(valuation_score, 25)
Pillar 3: Financial Health (0–25 points)
Measures balance sheet strength, leverage risk, and solvency. Incorporates Altman Z-Score concepts.
| Metric | Condition | Points |
|---|---|---|
| Debt-to-Equity | < 0.3 = 7pts, < 0.5 = 5pts, < 1.0 = 3pts, < 2.0 = 1pt | 0–7 |
| Current Ratio | > 2.0 = 6pts, > 1.5 = 4pts, > 1.0 = 2pts | 0–6 |
| Cash-to-Debt Ratio | cash/debt > 1.0 = 6pts, > 0.5 = 4pts, > 0.25 = 2pts, > 0 = 1pt | 0–6 |
| Interest Coverage* | > 10x = 6pts, > 5x = 4pts, > 2x = 2pts, > 1x = 1pt | 0–6 |
| Pillar Total | 0–25 |
Interest Coverage = EBIT / Interest Expense (from income statement)
Scoring logic:
health_score = 0
# Debt-to-Equity (lower is safer — Buffett prefers < 0.5)
if debt_to_equity < 30: health_score += 7 # Yahoo returns as percentage
elif debt_to_equity < 50: health_score += 5
elif debt_to_equity < 100: health_score += 3
elif debt_to_equity < 200: health_score += 1
# Current Ratio (ability to pay short-term obligations)
if current_ratio > 2.0: health_score += 6
elif current_ratio > 1.5: health_score += 4
elif current_ratio > 1.0: health_score += 2
# Cash-to-Debt Ratio
if total_debt > 0:
cash_ratio = total_cash / total_debt
if cash_ratio > 1.0: health_score += 6
elif cash_ratio > 0.5: health_score += 4
elif cash_ratio > 0.25: health_score += 2
elif cash_ratio > 0: health_score += 1
else:
health_score += 6 # no debt = perfect
# Interest Coverage (from income statement if available)
if interest_expense > 0:
coverage = ebit / interest_expense
if coverage > 10: health_score += 6
elif coverage > 5: health_score += 4
elif coverage > 2: health_score += 2
elif coverage > 1: health_score += 1
else:
health_score += 4 # no interest expense (assume manageable)
health_score = min(health_score, 25)
Pillar 4: Growth (0–25 points)
Measures revenue trajectory, earnings momentum, and forward growth expectations.
| Metric | Condition | Points |
|---|---|---|
| Revenue Growth (YoY) | > 25% = 7pts, > 15% = 5pts, > 5% = 3pts, > 0% = 1pt | 0–7 |
| Earnings Growth (YoY) | > 25% = 6pts, > 15% = 4pts, > 5% = 2pts, > 0% = 1pt | 0–6 |
| Quarterly Earnings Growth | > 20% = 6pts, > 10% = 4pts, > 0% = 2pt, negative = 0 | 0–6 |
| Analyst Growth Est (Next 5Y) | > 20% = 6pts, > 15% = 4pts, > 10% = 3pts, > 5% = 2pts, > 0% = 1pt | 0–6 |
| Pillar Total | 0–25 |
Scoring logic:
growth_score = 0
# Revenue Growth YoY
if revenue_growth > 0.25: growth_score += 7
elif revenue_growth > 0.15: growth_score += 5
elif revenue_growth > 0.05: growth_score += 3
elif revenue_growth > 0: growth_score += 1
# Earnings Growth YoY
if earnings_growth > 0.25: growth_score += 6
elif earnings_growth > 0.15: growth_score += 4
elif earnings_growth > 0.05: growth_score += 2
elif earnings_growth > 0: growth_score += 1
# Quarterly Earnings Growth
if quarterly_earnings_growth > 0.20: growth_score += 6
elif quarterly_earnings_growth > 0.10: growth_score += 4
elif quarterly_earnings_growth > 0: growth_score += 2
# Analyst Forward Estimates (earningsTrend: +5y growth)
if analyst_5y_growth > 0.20: growth_score += 6
elif analyst_5y_growth > 0.15: growth_score += 4
elif analyst_5y_growth > 0.10: growth_score += 3
elif analyst_5y_growth > 0.05: growth_score += 2
elif analyst_5y_growth > 0: growth_score += 1
growth_score = min(growth_score, 25)
Total Fundamental Score
FUNDAMENTAL_SCORE = profitability_score + valuation_score + health_score + growth_score
# Range: 0–100
Step 4 — Calculate Technical Trend Score (0–100)
The technical score uses price history to assess trend strength and momentum.
Pillar A: Moving Average Alignment (0–25 points)
| Signal | Condition | Points |
|---|---|---|
| Price > 50-day SMA | Yes | +5 |
| Price > 200-day SMA | Yes | +5 |
| 50-day SMA > 200-day SMA | Yes (Golden Cross territory) | +7 |
| Price > 20-day SMA | Yes (short-term trend up) | +4 |
| 50-day SMA slope positive | Rising over last 20 days | +4 |
| Pillar Total | 0–25 |
Calculation:
ma_score = 0
price = current_price
sma_20 = average(closes[-20:])
sma_50 = average(closes[-50:])
sma_200 = average(closes[-200:])
sma_50_prev = average(closes[-70:-20]) # 50-day SMA from 20 days ago
if price > sma_50: ma_score += 5
if price > sma_200: ma_score += 5
if sma_50 > sma_200: ma_score += 7 # Golden Cross territory
if price > sma_20: ma_score += 4
if sma_50 > sma_50_prev: ma_score += 4 # 50-day trending up
ma_score = min(ma_score, 25)
Pillar B: Momentum (0–25 points)
| Signal | Condition | Points |
|---|---|---|
| RSI(14) | 50-70 = 7pts (healthy uptrend), 40-50 = 4pts (neutral), 30-40 = 2pts (oversold bounce possible), <30 = 1pt (deeply oversold), >70 = 3pts (overbought risk) | 0–7 |
| MACD above signal | Bullish crossover | +6 |
| MACD histogram rising | Momentum accelerating | +6 |
| Price Rate of Change (20d) | > 5% = 6pts, > 0% = 3pts, < 0% = 0pts | 0–6 |
| Pillar Total | 0–25 |
RSI Calculation:
# RSI(14) — standard Wilder's smoothing
changes = [closes[i] - closes[i-1] for i in range(1, len(closes))]
gains = [max(c, 0) for c in changes]
losses = [abs(min(c, 0)) for c in changes]
avg_gain = wilder_smooth(gains, 14)
avg_loss = wilder_smooth(losses, 14)
rs = avg_gain / avg_loss
rsi = 100 - (100 / (1 + rs))
MACD Calculation:
# MACD(12, 26, 9)
ema_12 = exponential_moving_average(closes, 12)
ema_26 = exponential_moving_average(closes, 26)
macd_line = ema_12 - ema_26
signal_line = exponential_moving_average(macd_line, 9)
histogram = macd_line - signal_line
momentum_score = 0
# RSI scoring
if 50 <= rsi <= 70: momentum_score += 7
elif 40 <= rsi < 50: momentum_score += 4
elif 30 <= rsi < 40: momentum_score += 2
elif rsi < 30: momentum_score += 1
elif rsi > 70: momentum_score += 3
# MACD
if macd_line > signal_line: momentum_score += 6
if histogram > histogram_prev: momentum_score += 6
# Rate of Change
roc_20 = (price - closes[-20]) / closes[-20]
if roc_20 > 0.05: momentum_score += 6
elif roc_20 > 0: momentum_score += 3
momentum_score = min(momentum_score, 25)
Pillar C: Price Action (0–25 points)
| Signal | Condition | Points |
|---|---|---|
| 52-Week Position | Top 20% = 7pts, Top 40% = 5pts, Mid = 3pts, Bottom 40% = 1pt, Bottom 20% = 0 | 0–7 |
| Distance from 52W High | Within 5% = 6pts, within 10% = 4pts, within 20% = 2pts | 0–6 |
| 1-Month Trend | Up > 5% = 6pts, Up > 0% = 3pts, Down = 0 | 0–6 |
| Higher Lows (20d) | Recent low > prior low (uptrend structure) | +6 |
| Pillar Total | 0–25 |
Scoring logic:
price_action_score = 0
# 52-week position (where price sits in the range)
week52_range = fifty_two_week_high - fifty_two_week_low
position = (price - fifty_two_week_low) / week52_range # 0.0 to 1.0
if position > 0.80: price_action_score += 7
elif position > 0.60: price_action_score += 5
elif position > 0.40: price_action_score += 3
elif position > 0.20: price_action_score += 1
# Distance from 52-week high
distance_from_high = (fifty_two_week_high - price) / fifty_two_week_high
if distance_from_high < 0.05: price_action_score += 6
elif distance_from_high < 0.10: price_action_score += 4
elif distance_from_high < 0.20: price_action_score += 2
# 1-month trend
month_ago_price = closes[-22] # ~22 trading days
monthly_change = (price - month_ago_price) / month_ago_price
if monthly_change > 0.05: price_action_score += 6
elif monthly_change > 0: price_action_score += 3
# Higher lows check (uptrend structure)
recent_low = min(lows[-10:])
prior_low = min(lows[-20:-10])
if recent_low > prior_low: price_action_score += 6
price_action_score = min(price_action_score, 25)
Pillar D: Volume Trend (0–25 points)
| Signal | Condition | Points |
|---|---|---|
| Volume vs 3M Average | Above avg on up days = 8pts | 0–8 |
| Volume Trend (20d) | Rising volume = 6pts, stable = 3pts | 0–6 |
| Accumulation Pattern | Up days volume > down days volume (20d) = 6pts | 0–6 |
| On-Balance Volume trend | OBV rising over 20d | +5 |
| Pillar Total | 0–25 |
Scoring logic:
volume_score = 0
# Current volume vs 3-month average
if current_volume > avg_volume_3m * 1.2:
# High volume — check if it's on an up day
if price_change_today > 0: volume_score += 8
else: volume_score += 2 # high volume selling is bearish signal
elif current_volume > avg_volume_3m * 0.8:
volume_score += 4 # normal volume
# Volume trend over 20 days
avg_vol_recent = average(volumes[-10:])
avg_vol_prior = average(volumes[-20:-10])
if avg_vol_recent > avg_vol_prior * 1.1: volume_score += 6
elif avg_vol_recent > avg_vol_prior * 0.9: volume_score += 3
# Accumulation: compare volume on up days vs down days
up_day_volume = sum(v for v, c in zip(volumes[-20:], changes[-20:]) if c > 0)
down_day_volume = sum(v for v, c in zip(volumes[-20:], changes[-20:]) if c < 0)
if up_day_volume > down_day_volume * 1.2: volume_score += 6
elif up_day_volume > down_day_volume: volume_score += 3
# On-Balance Volume (OBV) trend
obv = calculate_obv(closes, volumes)
obv_sma = average(obv[-20:])
obv_sma_prev = average(obv[-40:-20])
if obv_sma > obv_sma_prev: volume_score += 5
volume_score = min(volume_score, 25)
Total Technical Score
TECHNICAL_SCORE = ma_score + momentum_score + price_action_score + volume_score
# Range: 0–100
Step 5 — Calculate Composite Score and Signal
Composite Weighting
Fundamentals are weighted more heavily because they drive long-term value:
COMPOSITE_SCORE = (FUNDAMENTAL_SCORE × 0.60) + (TECHNICAL_SCORE × 0.40)
# Range: 0–100
Signal Mapping — 7-Tier Rating
| Composite Score | Signal | Label | Description |
|---|---|---|---|
| 85–100 | ✅✅✅ | MUST BUY | Exceptional fundamentals + strong uptrend. Rare — act decisively. |
| 70–84 | ✅✅ | STRONG BUY | Very good fundamentals with confirming trend. High conviction entry. |
| 55–69 | ✅ | BUY | Solid fundamentals, acceptable trend. Good entry on dips. |
| 40–54 | ⚪ | HOLD | Mixed signals. Hold existing positions, wait for clarity. |
| 25–39 | ❌ | SELL | Weakening fundamentals or broken trend. Consider reducing. |
| 10–24 | ❌❌ | STRONG SELL | Poor fundamentals with downtrend. Exit most positions. |
| 0–9 | ❌❌❌ | MUST SELL | Severely distressed. Financial health at risk. Exit immediately. |
Trend Arrow Enhancement
The trend direction from the technical score adds context to the signal:
| Technical Score | Trend Arrow | Meaning |
|---|---|---|
| 75–100 | ▲▲ | Strong uptrend |
| 50–74 | ▲ | Uptrend |
| 40–49 | ► | Sideways / neutral |
| 25–39 | ▼ | Downtrend |
| 0–24 | ▼▼ | Strong downtrend |
Step 6 — Output Format
Single Stock Analysis
╔══════════════════════════════════════════════════════════════╗
║ 📊 FUNDAMENTAL TREND ANALYSIS — NVDA ║
║ NVIDIA Corporation ║
║ Price: $875.40 ▲ +2.34% | {date} ║
╠══════════════════════════════════════════════════════════════╣
║ ║
║ ══ SIGNAL ══ ║
║ ║
║ ✅✅ STRONG BUY ║
║ Composite Score: 76/100 | Trend: ▲▲ Strong Uptrend ║
║ ║
╠══════════════════════════════════════════════════════════════╣
║ ║
║ ══ FUNDAMENTAL SCORE: 72/100 ══ ║
║ ║
║ Profitability ████████████████████░░░░░ 20/25 ║
║ ROE: 91.2% (7) ROA: 54.1% (6) ║
║ Margin: 55.0% (6) OCF Quality (6) ║
║ ║
║ Valuation ██████████░░░░░░░░░░░░░░░ 10/25 ║
║ P/E: 65.2 (1) Fwd P/E: 38.1 (4) ║
║ P/B: 45.8 (0) PEG: 1.2 (3) EV/EBITDA: 52 (0) ║
║ ║
║ Financial Health ██████████████████████░░░ 22/25 ║
║ D/E: 17.2% (7) Current: 4.2 (6) ║
║ Cash/Debt: 2.1 (6) Coverage: 85x (6) ║
║ ║
║ Growth ████████████████████░░░░░ 20/25 ║
║ Rev Growth: 122% (7) EPS Growth: 581% (6) ║
║ Qtr Growth: 109% (6) Analyst 5Y: 35% (6) ║
║ ║
╠══════════════════════════════════════════════════════════════╣
║ ║
║ ══ TECHNICAL SCORE: 82/100 ══ ║
║ ║
║ MA Alignment ██████████████████████████ 25/25 ║
║ Price > SMA20 ✓ Price > SMA50 ✓ Price > SMA200 ✓ ║
║ SMA50 > SMA200 ✓ (Golden Cross) SMA50 Rising ✓ ║
║ ║
║ Momentum █████████████████████░░░░ 21/25 ║
║ RSI(14): 62 (7) MACD: Bullish (6) ║
║ Histogram: Rising (6) ROC(20d): +3.2% (3) ║
║ ║
║ Price Action ████████████████████░░░░░ 20/25 ║
║ 52W Position: 85% (7) From High: -4% (6) ║
║ 1M Trend: +8.2% (6) Higher Lows: No (0) ║
║ ║
║ Volume ████████████████░░░░░░░░░ 16/25 ║
║ Vol vs Avg: 1.3x ↑ (8) Trend: Stable (3) ║
║ Accumulation: Yes (6) OBV: Flat (0) ║
║ ║
╠══════════════════════════════════════════════════════════════╣
║ ══ COMPOSITE BREAKDOWN ══ ║
║ Fundamental: 72 × 0.60 = 43.2 ║
║ Technical: 82 × 0.40 = 32.8 ║
║ COMPOSITE: 76.0 / 100 ║
║ ║
║ ⚠ Note: High growth but elevated valuation. Strong trend ║
║ confirms momentum. Watch for P/E compression risk. ║
╚══════════════════════════════════════════════════════════════╝
Multi-Stock Comparison Table
When analyzing multiple tickers (e.g., a portfolio):
╔═══════════════════════════════════════════════════════════════════════════════╗
║ 📊 PORTFOLIO ANALYSIS — Fundamental + Trend Scores ║
║ {date} ║
╠═══════╦════════╦══════╦══════╦══════╦══════╦══════╦══════╦═══════════════════╣
║ TICKER║ PRICE ║ FUND ║ TECH ║ COMP ║ TREND║SIGNAL║ ║ KEY FACTOR ║
╠═══════╬════════╬══════╬══════╬══════╬══════╬══════╬══════╬═══════════════════╣
║ NVDA ║ 875.40 ║ 72 ║ 82 ║ 76 ║ ▲▲ ║ ✅✅ ║ STRG ║ Growth monster ║
║ MSFT ║ 420.15 ║ 78 ║ 65 ║ 73 ║ ▲ ║ ✅✅ ║ STRG ║ Cash machine ║
║ AAPL ║ 182.30 ║ 75 ║ 52 ║ 66 ║ ▲ ║ ✅ ║ BUY ║ Stable margins ║
║ GOOGL ║ 155.80 ║ 70 ║ 58 ║ 65 ║ ▲ ║ ✅ ║ BUY ║ Value + growth ║
║ TSLA ║ 175.20 ║ 45 ║ 71 ║ 55 ║ ▲▲ ║ ✅ ║ BUY ║ Trend > fundmntl ║
║ META ║ 505.30 ║ 80 ║ 74 ║ 78 ║ ▲▲ ║ ✅✅ ║ STRG ║ Top value+growth ║
║ V ║ 280.10 ║ 82 ║ 60 ║ 73 ║ ▲ ║ ✅✅ ║ STRG ║ Quality leader ║
║ AMD ║ 165.40 ║ 48 ║ 42 ║ 46 ║ ► ║ ⚪ ║ HOLD ║ Valuation stretch║
║ AMZN ║ 186.90 ║ 65 ║ 68 ║ 66 ║ ▲ ║ ✅ ║ BUY ║ Margin expansion ║
║ AVGO ║ 1520.0 ║ 74 ║ 78 ║ 76 ║ ▲▲ ║ ✅✅ ║ STRG ║ AI + dividends ║
╠═══════╩════════╩══════╩══════╩══════╩══════╩══════╩══════╩═══════════════════╣
║ Legend: FUND=Fundamental(0-100) TECH=Technical(0-100) COMP=Composite(0-100) ║
║ Signals: ✅✅✅ Must Buy ✅✅ Strong Buy ✅ Buy ⚪ Hold ║
║ ❌ Sell ❌❌ Strong Sell ❌❌❌ Must Sell ║
║ Trend: ▲▲ Strong Up ▲ Up ► Sideways ▼ Down ▼▼ Strong Down ║
╚═══════════════════════════════════════════════════════════════════════════════╝
Step 7 — Contextual Notes Generation
After computing scores, generate 1–2 lines of context based on the score pattern:
| Pattern | Note |
|---|---|
| High Fundamental + Low Technical | "Strong company in a downtrend — potential value opportunity. Wait for trend reversal." |
| Low Fundamental + High Technical | "Momentum play with weak fundamentals — high risk. Use tight stop-loss." |
| High Fundamental + High Technical | "Quality + trend alignment — high conviction entry." |
| Low Fundamental + Low Technical | "Avoid — deteriorating business with no trend support." |
| High Valuation + High Growth | "Premium valuation justified by growth — watch for deceleration." |
| Low D/E + High ROE | "Capital-efficient compounder — Buffett-style quality." |
| Negative Earnings Growth + High P/E | "Market pricing in turnaround — high risk if recovery doesn't materialize." |
Sector-Aware Adjustments
Different sectors have different "normal" ranges for metrics. Apply these adjustments before scoring:
| Sector | P/E Adjustment | D/E Adjustment | Growth Adj | Notes |
|---|---|---|---|---|
| Technology | P/E thresholds × 1.5 | Standard | Growth thresholds × 1.3 | Higher multiples normal |
| Financials | Standard | D/E thresholds × 3.0 | Standard | Banks carry more leverage |
| Utilities | P/E thresholds × 0.8 | D/E thresholds × 1.5 | Growth thresholds × 0.5 | Slow growth, regulated |
| Healthcare | P/E thresholds × 1.3 | Standard | Standard | Pipeline optionality |
| REITs | Skip P/E, use P/FFO | D/E thresholds × 2.0 | Growth thresholds × 0.7 | Leverage is structural |
| Consumer Staples | Standard | Standard | Growth thresholds × 0.7 | Defensive, lower growth |
| Energy | P/E thresholds × 0.8 | Standard | Standard | Cyclical earnings |
To detect sector, use the assetProfile module:
curl -s "https://query2.finance.yahoo.com/v10/finance/quoteSummary/${TICKER}?modules=assetProfile" \
-H "User-Agent: Mozilla/5.0" | jq '.quoteSummary.result[0].assetProfile.sector'
Batch Analysis — Multiple Tickers
For portfolio analysis, fetch quotes in batch and fundamentals per-ticker:
# Batch quotes (up to 100 tickers)
TICKERS="NVDA,MSFT,AAPL,GOOGL,TSLA,META,V,AMD,AMZN,AVGO"
curl -s "https://query2.finance.yahoo.com/v7/finance/quote?symbols=${TICKERS}" \
-H "User-Agent: Mozilla/5.0" | jq '.quoteResponse.result[]'
# Then for each ticker, fetch fundamentals (can be done concurrently)
for TICKER in NVDA MSFT AAPL GOOGL TSLA META V AMD AMZN AVGO; do
curl -s "https://query2.finance.yahoo.com/v10/finance/quoteSummary/${TICKER}?modules=financialData,defaultKeyStatistics,summaryDetail,earningsTrend,assetProfile" \
-H "User-Agent: Mozilla/5.0" > "/tmp/${TICKER}_fundamentals.json" &
done
wait
Quick Reference — Scoring Thresholds
Fundamental Metrics Cheat Sheet
| Metric | Excellent | Good | Fair | Poor |
|---|---|---|---|---|
| ROE | > 15% | 10-15% | 5-10% | < 5% |
| ROA | > 10% | 5-10% | 2-5% | < 2% |
| Profit Margin | > 20% | 10-20% | 5-10% | < 5% |
| P/E Ratio | < 15 | 15-20 | 20-30 | > 30 |
| PEG Ratio | < 1.0 | 1.0-1.5 | 1.5-2.0 | > 2.0 |
| Debt/Equity | < 30% | 30-50% | 50-100% | > 100% |
| Current Ratio | > 2.0 | 1.5-2.0 | 1.0-1.5 | < 1.0 |
| Revenue Growth | > 25% | 15-25% | 5-15% | < 5% |
Technical Signals Cheat Sheet
| Indicator | Bullish | Neutral | Bearish |
|---|---|---|---|
| Price vs SMA200 | Above | At | Below |
| SMA50 vs SMA200 | Golden Cross | Converging | Death Cross |
| RSI(14) | 50-70 | 40-50 | < 30 or > 70 |
| MACD | Above signal | At signal | Below signal |
| Volume | Rising on up days | Average | Rising on down days |
Interpreting Results
High composite scores (70+) indicate alignment between business quality and market momentum — these are the highest conviction opportunities.
Divergence between fundamental and technical scores is informative:
- Fundamental ≫ Technical: Value trap risk or turnaround candidate. The business is strong but the market disagrees. Look for catalysts.
- Technical ≫ Fundamental: Momentum play. The market is running ahead of fundamentals. Risk of mean reversion. Use trailing stops.
Best opportunities often emerge when:
- Fundamental score > 65 AND technical score was < 40 but is now rising (trend reversal on a quality name)
- Both scores > 70 (quality + momentum alignment)
- Fundamental score improving quarter-over-quarter (business inflection)
Worst situations (must sell territory):
- Both scores < 25 (deteriorating business in a downtrend)
- Financial health score < 5 (potential bankruptcy risk — Altman Z-Score territory)
- Fundamental declining AND technical breaking key support levels
Limitations and Disclaimers
- Not financial advice. This is a quantitative screening tool. Always do your own research.
- Backward-looking. Fundamentals are based on reported financials (1–3 months lag). Markets are forward-looking.
- Sector differences. A P/E of 30 is expensive for a utility but cheap for a high-growth tech company. The sector adjustments help but aren't perfect.
- Data availability. Some metrics may be missing for newer companies, ADRs, or small caps. Score only on available data and note missing pillars.
- No macro overlay. This model doesn't account for interest rates, geopolitical risk, or market-wide conditions. Combine with market-overview skill for context.
References
- Piotroski F-Score (Wikipedia) — Original 9-criteria financial strength scoring
- Altman Z-Score — Bankruptcy prediction model
- Schwab: Five Key Financial Ratios — Core ratio analysis
- Danelfin AI Score — AI-powered fundamental scoring system
- Tickeron AI Ratings — Combined fundamental + technical scoring
- Financial Modeling Prep API — Free fundamental data APIs
- Yahoo Finance — Data source for all calculations