| name | gf-dma-health-index |
| description | Use when the user provides a ticker or asks for GF-DMA scoring, valuation/trend health, moving-average support, price-to-DMA divergence, ATR divergence, escape risk, estimate revisions, healthy momentum, or whether a rising/falling stock is fundamentally supported. |
GF-DMA Health Index
Core Idea
Evaluate whether a stock's current price trend is supported by fundamental speed and moving-average structure.
Use the index to answer:
Is the current price trend supported by revenue growth, profit growth, estimate revisions, and the 20/50/100/200DMA system?
Treat results as research analysis, not investment advice. For latest/current scoring, verify data from current sources before calculating.
Required Inputs
Collect the newest available data before scoring:
- Price/technical data: latest price, 20DMA, 50DMA, 100DMA, 200DMA, ATR20, 5-day price change, and 20/50/100/200-day price changes or historical prices.
- Fundamental data: latest quarterly revenue, EPS, gross margin or gross profit, next-quarter company guidance, consensus revenue/EPS estimates, and 30-day estimate revisions.
- Preferred sources: company IR releases/presentations, earnings calls, Yahoo Finance historical prices/analysis, TradingView technicals/estimates, Barchart technical analysis, Seeking Alpha estimates, Koyfin, FactSet, Bloomberg, TIKR, or Visible Alpha.
For U.S.-listed companies, SEC filings can improve the fundamental side of the score. edgartools is an optional helper for retrieving the latest 10-K, 10-Q, 8-K, XBRL financial statements, filing text, insider transactions, and ownership filings.
If the environment does not already have it, install with pip install edgartools or uv pip install edgartools. The import package is edgar, not edgartools. SEC access requires an identity; set EDGAR_IDENTITY="Name email@example.com" in the environment or call from edgar import set_identity; set_identity("name@example.com") before requests.
Minimal usage pattern:
from edgar import Company
company = Company("AAPL")
financials = company.get_financials()
income = financials.income_statement()
filings = company.get_filings(form="8-K")
Use SEC data for:
- reported quarterly revenue, gross profit, EPS, cash flow, balance sheet, share count, and historical trend baselines
- management language on demand, backlog, pricing, capacity, inventory, customer concentration, and risks
- 8-K earnings releases or guidance disclosures when they contain the newest company-provided numbers
Do not use SEC data for the technical module or revision module. Price, 20/50/100/200DMA, ATR20, 5-day price slope, consensus estimates, and 30-day estimate revisions still require market-data and estimate sources. When SEC data is used, state the filing form and filing date so the user can judge freshness.
If a required field is unavailable, say which field is missing and use the simplified formula only when appropriate.
Calculation Workflow
1. Fundamental Speed
Calculate:
G_f = 0.35G_Revenue + 0.25G_GrossProfit + 0.30G_EPS + 0.10G_Revision
Where:
G_Revenue = next-quarter revenue guidance / latest-quarter revenue - 1G_GrossProfit = next-quarter gross profit / latest-quarter gross profit - 1G_EPS = next-quarter EPS guidance / latest-quarter EPS - 1G_Revision = 30-day consensus estimate revision
Fallbacks:
- If gross profit or EPS is missing:
G_f = 0.5G_Revenue + 0.5G_EPS
- If only revenue guidance is available:
G_f = G_Revenue
2. DMA Speed
Calculate quarterly annualized-equivalent moving-average speed for each DMA:
G_DMAx = ((SMA_x(t) - SMA_x(t-k)) / SMA_x(t-k)) * (63 / k)
Use k = 5 or 10 trading days by default. If only price-change data is available, approximate:
DailySlope_x ~= (P_t - P_t-x) / x
G_DMAx ~= DailySlope_x * 63 / P_t
Compute G_DMA20, G_DMA50, G_DMA100, and G_DMA200.
3. Fundamental-DMA Match
Calculate:
R_x = G_DMAx / G_f
Interpret R_50 and R_100 first:
| R_x | Status |
|---|
| < 0.5 | Trend clearly below fundamental speed |
| 0.5-0.8 | Under-reflected or cheap versus trend |
| 0.8-1.3 | Healthy match |
| 1.3-2.0 | Hot but potentially explainable |
| > 2.0 | Overheated / FOMO escape risk |
Core DMA emphasis:
| Stock type | Key DMA |
|---|
| Mega-cap growth leaders like NVDA, AVGO, MSFT | 50DMA |
| Memory/cyclical semis like MU, SNDK | 100DMA |
| High-elasticity optical names like LITE, AAOI | 20DMA + 50DMA |
| Industrial AI/power names like ETN, VRT, TEL | 100DMA + 200DMA |
| Small-cap hard-manufacturing names like SIVE, CPSH | 20DMA + ATR divergence |
| Semiconductor ETFs like SOXX, SMH | 50DMA + 100DMA |
4. Price-DMA Divergence
Calculate:
D_x = P_t / SMA_x(t) - 1
Z_x = (P_t - SMA_x) / ATR20
Interpretation:
| Signal | Status |
|---|
| 0%-5% above 20DMA | Healthy close-to-line trend |
| 5%-12% above 20DMA | Strong trend, mild valuation stretch |
| 12%-20% above 20DMA | Hot; divergence score should fall |
| >20% above 20DMA | Short-term escape; divergence score should fall sharply |
| >30% above 50DMA | Medium-term overheat |
| >50% above 100DMA | Major repricing |
| >100% above 200DMA | Extreme long-cycle repricing |
| 0%-5% below 20/50DMA with stable fundamentals | Healthy pullback; divergence score can rise |
| 5%-15% below 50DMA with stable/improving fundamentals | Better valuation entry, but verify trend damage separately |
| Below 100/200DMA with deteriorating fundamentals | Trend damage; do not treat as cheap automatically |
ATR divergence is asymmetric:
| Z_x | Status |
|---|
| 0 to 2 | Healthy |
| 2 to 3 | Hot |
| 3 to 4 | Very hot |
| >4 | Escape; reduce divergence score sharply |
| -1 to 0 with stable fundamentals | Mild pullback; can improve valuation-health score |
| -3 to -1 with stable/improving fundamentals | Discounted pullback; score can be high, but check trend parallelism |
| < -3 or below key long DMA with estimate cuts | Possible breakdown; score should fall |
Important: S_Divergence is a valuation-health score, not a pure momentum score. Upward price-DMA divergence lowers the score because the stock is more stretched. Downward divergence raises the score only when fundamental speed and revision confirmation are stable or improving; if fundamentals are deteriorating, downward divergence is trend damage rather than an opportunity.
5. Trend Parallelism / Escape Ratio
Calculate:
EscapeRatio = 5-day price slope / 50DMA daily slope
Interpretation:
| EscapeRatio | Status |
|---|
| 0.8-1.2 | Price and 50DMA are parallel; healthy |
| 1.2-1.8 | Short-term acceleration; acceptable |
| 1.8-2.5 | Clearly hot |
| >2.5 | FOMO escape |
| 0-0.5 | Momentum decay |
| <0 | Short-term reversal; trend damage |
6. Revision Confirmation
Score estimate revisions:
| Revision state | Score |
|---|
| Revenue and EPS estimates rising; company guide above consensus | 85-100 |
| Mild upward revisions; guide slightly above consensus | 70-85 |
| Stable expectations; limited upward revision | 55-70 |
| Revisions starting to fall | 35-55 |
| Guide below consensus; analysts cutting estimates | <35 |
Divergence Module Scoring
Use asymmetric scoring for S_Divergence:
| State | Score |
|---|
| Price close to 20/50DMA, above 100/200DMA | 80-95 |
| Stable/improving fundamentals; price below 20DMA but near 50DMA | 85-100 |
| Stable/improving fundamentals; price 5%-15% below 50DMA while long DMAs remain healthy | 75-95 |
| Price 5%-12% above 20DMA | 65-80 |
| Price 12%-20% above 20DMA | 50-70 |
| Price >20% above 20DMA or >30% above 50DMA | 25-55 |
| Price below 50DMA with weakening fundamentals or estimate cuts | 35-60 |
| Price below 100DMA with estimate cuts | 15-45 |
| Price below 200DMA with fundamental deterioration | 0-30 |
When price is below key DMAs, explicitly state whether the lower price is a healthy pullback or a breakdown. The deciding gate is fundamental speed plus revision confirmation.
Final Scoring
Calculate total score out of 100:
HealthScore = 40S_GrowthMatch + 25S_Divergence + 20S_Parallel + 15S_Revision
Module scoring:
| Module | Weight |
|---|
| Fundamental speed match | 40% |
| Price-DMA divergence / pullback opportunity | 25% |
| Trend parallelism | 20% |
| Revision confirmation | 15% |
Final interpretation:
| Score | State | Meaning |
|---|
| 85-100 | Healthy Momentum | Healthy main uptrend |
| 75-85 | Strong but Watch | Strong trend; continue monitoring |
| 65-75 | Hot but Supported | Hot, but fundamentals can still support it |
| 55-65 | Damaged / Overheated | Trend damage or local overheat |
| 40-55 | High Risk | Risk clearly rising |
| <40 | Broken / Escaping | Broken trend or post-escape pullback |
Output Format
Use this structure for every ticker:
# TICKER: GF-DMA Health Index 评分
最终评分：XX / 100
状态：Healthy Momentum / Strong but Watch / Hot but Supported / Damaged / High Risk / Broken
一句话判断：
...
1. 基本面速度
- 最新季度营收：
- 下一季度营收指引：
- 营收 QoQ：
- EPS QoQ：
- 毛利润 QoQ：
- Fundamental Speed：
2. 均线速度匹配
| 均线 | 季度化斜率 | 相对基本面速度 | 判断 |
|---|---:|---:|---|
| 20DMA | | | |
| 50DMA | | | |
| 100DMA | | | |
| 200DMA | | | |
3. 股价-均线背离
| 指标 | 当前背离 | 判断 |
|---|---:|---|
| P / 20DMA - 1 | | |
| P / 50DMA - 1 | | |
| P / 100DMA - 1 | | |
| P / 200DMA - 1 | | |
4. 趋势平行度
- Escape Ratio：
- 判断：
5. 预期上修确认
- 公司指引 vs 市场预期：
- 过去 30 天预期变化：
- 判断：
6. 综合评分
| 模块 | 权重 | 分数 |
|---|---:|---:|
| 基本面速度匹配 | 40% | |
| 股价-均线背离 | 25% | |
| 趋势平行度 | 20% | |
| 预期上修确认 | 15% | |
结论：
...
Detailed Reference
Read references/original-framework.md when a task needs the full Chinese framework text, examples, source priority list, or scoring tables in their original form.
