gf-dma-health-index

name

gf-dma-health-index

description

Score a stock's current valuation/trend health using the GF-DMA Health Index, combining fundamental growth speed, 20/50/100/200DMA trend speed, price-to-DMA divergence, ATR divergence, escape ratio, and estimate revisions. Use when the user provides a ticker or asks for GF-DMA scoring, valuation health, trend health, healthy momentum, overheated/escape risk, 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 [e-mail]" in the environment or call from edgar import set_identity; set_identity("[e-mail]") 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 - 1
• G_GrossProfit = next-quarter gross profit / latest-quarter gross profit - 1
• G_EPS = next-quarter EPS guidance / latest-quarter EPS - 1
• G_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.