fundamental-trend-analysis

Comprehensive stock analysis combining fundamental scoring (Piotroski F-Score, valuation, growth, financial health) with technical trend signals to produce a 6-tier buy/sell rating from Must Buy to Must Sell.

baladengale 1 Updated 3mo ago

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SKILL.md

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

fundamental-trend-analysis

Install

Fundamental Trend Analysis — Composite Buy/Sell Signal Engine

When to Activate

Architecture Overview

Step 1 — Fetch Fundamental Data from Yahoo Finance

Step 2 — Fetch Technical / Price Data

Step 3 — Calculate Fundamental Score (0–100)

Pillar 1: Profitability (0–25 points)

Pillar 2: Valuation (0–25 points)

Pillar 3: Financial Health (0–25 points)

Pillar 4: Growth (0–25 points)

Total Fundamental Score

Step 4 — Calculate Technical Trend Score (0–100)

Pillar A: Moving Average Alignment (0–25 points)

Pillar B: Momentum (0–25 points)

Pillar C: Price Action (0–25 points)

Pillar D: Volume Trend (0–25 points)

Total Technical Score

Step 5 — Calculate Composite Score and Signal

Composite Weighting

Signal Mapping — 7-Tier Rating

Trend Arrow Enhancement

Step 6 — Output Format

Single Stock Analysis

Multi-Stock Comparison Table

Step 7 — Contextual Notes Generation

Sector-Aware Adjustments

Batch Analysis — Multiple Tickers

Quick Reference — Scoring Thresholds

Fundamental Metrics Cheat Sheet

Technical Signals Cheat Sheet

Interpreting Results

Limitations and Disclaimers

References

Categories

Install

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