estimate-analysis

Name: estimate-analysis
Author: himself65

1.4kinstalls351forks

How to install estimate-analysis?

himself65/finance-skills/estimate-analysis

$npx -y skills add himself65/finance-skills --skill estimate-analysis

Installs into the current project.

Summary

Deep-dive into analyst estimates and revision trends for any stock using Yahoo Finance data. Use when the user wants to understand analyst estimate direction, how EPS or revenue forecasts changed over time, compare estimate distributions, or analyze growth projections across peri

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SKILL.md

1	# Estimate Analysis Skill
2
3	Deep-dives into analyst estimates and revision trends using Yahoo Finance data via [yfinance](https://github.com/ranaroussi/yfinance). Covers EPS and revenue estimate distributions, revision momentum, growth projections, and multi-period comparisons — the full picture of where the street thinks a company is heading.
4
5	Important: Data is for research and educational purposes only. Not financial advice. yfinance is not affiliated with Yahoo, Inc.
6
7	---
8
9	## Step 1: Ensure yfinance Is Available
10
11	Current environment status:
12
13	```
14	!`python3 -c "import yfinance; print('yfinance ' + yfinance.__version__ + ' installed')" 2>/dev/null \|\| echo "YFINANCE_NOT_INSTALLED"`
15	```
16
17	If `YFINANCE_NOT_INSTALLED`, install it:
18
19	```python
20	import subprocess, sys
21	subprocess.check_call([sys.executable, "-m", "pip", "install", "-q", "yfinance"])
22	```
23
24	If already installed, skip to the next step.
25
26	---
27
28	## Step 2: Identify the Ticker and Gather Estimate Data
29
30	Extract the ticker from the user's request. Fetch all estimate-related data in one script.
31
32	```python
33	import yfinance as yf
34	import pandas as pd
35
36	ticker = yf.Ticker("AAPL") # replace with actual ticker
37
38	# --- Estimate data ---
39	earnings_est = ticker.earnings_estimate # EPS estimates by period
40	revenue_est = ticker.revenue_estimate # Revenue estimates by period
41	eps_trend = ticker.eps_trend # EPS estimate changes over time
42	eps_revisions = ticker.eps_revisions # Up/down revision counts
43	growth_est = ticker.growth_estimates # Growth rate estimates
44
45	# --- Historical context ---
46	earnings_hist = ticker.earnings_history # Track record
47	info = ticker.info # Company basics
48	quarterly_income = ticker.quarterly_income_stmt # Recent actuals
49	```
50
51	### What each data source provides
52
53	\| Data Source \| What It Shows \| Why It Matters \|
54	\|---\|---\|---\|
55	\| `earnings_estimate` \| Current EPS consensus by period (0q, +1q, 0y, +1y) \| The estimate levels — what analysts expect \|
56	\| `revenue_estimate` \| Current revenue consensus by period \| Top-line expectations \|
57	\| `eps_trend` \| How the EPS estimate has changed (7d, 30d, 60d, 90d ago) \| Revision direction — rising or falling expectations \|
58	\| `eps_revisions` \| Count of upward vs downward revisions (7d, 30d) \| Revision breadth — are most analysts raising or cutting? \|
59	\| `growth_estimates` \| Growth rate estimates vs peers and sector \| Relative positioning \|
60	\| `earnings_history` \| Actual vs estimated for last 4 quarters \| Calibration — how good are these estimates historically? \|
61
62	---
63
64	## Step 3: Route Based on User Intent
65
66	The user might want different levels of analysis. Route accordingly:
67
68	\| User Request \| Focus Area \| Key Sections \|
69	\|---\|---\|---\|
70	\| General estimate analysis \| Full analysis \| All sections \|
71	\| "How have estimates changed" \| Revision trends \| EPS Trend + Revisions \|
72	\| "What are analysts expecting" \| Current consensus \| Estimate overview \|
73	\| "Growth estimates" \| Growth projections \| Growth Estimates \|
74	\| "Bull vs bear case" \| Estimate range \| High/low spread analysis \|
75	\| Compare estimates across periods \| Multi-period \| Period comparison table \|
76
77	When in doubt, provide the full analysis — more context is better.
78
79	---
80
81	## Step 4: Build the Estimate Analysis
82
83	### Section 1: Estimate Overview
84
85	Present the current consensus for all available periods from `earnings_estimate` and `revenue_estimate`:
86
87	EPS Estimates:
88
89	\| Period \| Consensus \| Low \| High \| Range Width \| # Analysts \| YoY Growth \|
90	\|---\|---\|---\|---\|---\|---\|---\|
91	\| Current Qtr (0q) \| $1.42 \| $1.35 \| $1.50 \| $0.15 (10.6%) \| 28 \| +12.7% \|
92	\| Next Qtr (+1q) \| $1.58 \| $1.48 \| $1.68 \| $0.20 (12.7%) \| 25 \| +8.3% \|
93	\| Current Year (0y) \| $6.70 \| $6.50 \| $6.95 \| $0.45 (6.7%) \| 30 \| +10.2% \|
94	\| Next Year (+1y) \| $7.45 \| $7.10 \| $7.85 \| $0.75 (10.1%) \| 28 \| +11.2% \|
95
96	Revenue Estimates:
97
98	\| Period \| Consensus \| Low \| High \| # Analysts \| YoY Growth \|
99	\|---\|---\|---\|---\|---\|---\|
100	\| Current Qtr \| $94.

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estimate-analysis

1.4kinstalls351forks

View on GitHub

How to install estimate-analysis?

himself65/finance-skills/estimate-analysis

$npx -y skills add himself65/finance-skills --skill estimate-analysis

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	# Estimate Analysis Skill
2
3	Deep-dives into analyst estimates and revision trends using Yahoo Finance data via [yfinance](https://github.com/ranaroussi/yfinance). Covers EPS and revenue estimate distributions, revision momentum, growth projections, and multi-period comparisons — the full picture of where the street thinks a company is heading.
4
5	Important: Data is for research and educational purposes only. Not financial advice. yfinance is not affiliated with Yahoo, Inc.
6
7	---
8
9	## Step 1: Ensure yfinance Is Available
10
11	Current environment status:
12
13	```
14	!`python3 -c "import yfinance; print('yfinance ' + yfinance.__version__ + ' installed')" 2>/dev/null \|\| echo "YFINANCE_NOT_INSTALLED"`
15	```
16
17	If `YFINANCE_NOT_INSTALLED`, install it:
18
19	```python
20	import subprocess, sys
21	subprocess.check_call([sys.executable, "-m", "pip", "install", "-q", "yfinance"])
22	```
23
24	If already installed, skip to the next step.
25
26	---
27
28	## Step 2: Identify the Ticker and Gather Estimate Data
29
30	Extract the ticker from the user's request. Fetch all estimate-related data in one script.
31
32	```python
33	import yfinance as yf
34	import pandas as pd
35
36	ticker = yf.Ticker("AAPL") # replace with actual ticker
37
38	# --- Estimate data ---
39	earnings_est = ticker.earnings_estimate # EPS estimates by period
40	revenue_est = ticker.revenue_estimate # Revenue estimates by period
41	eps_trend = ticker.eps_trend # EPS estimate changes over time
42	eps_revisions = ticker.eps_revisions # Up/down revision counts
43	growth_est = ticker.growth_estimates # Growth rate estimates
44
45	# --- Historical context ---
46	earnings_hist = ticker.earnings_history # Track record
47	info = ticker.info # Company basics
48	quarterly_income = ticker.quarterly_income_stmt # Recent actuals
49	```
50
51	### What each data source provides
52
53	\| Data Source \| What It Shows \| Why It Matters \|
54	\|---\|---\|---\|
55	\| `earnings_estimate` \| Current EPS consensus by period (0q, +1q, 0y, +1y) \| The estimate levels — what analysts expect \|
56	\| `revenue_estimate` \| Current revenue consensus by period \| Top-line expectations \|
57	\| `eps_trend` \| How the EPS estimate has changed (7d, 30d, 60d, 90d ago) \| Revision direction — rising or falling expectations \|
58	\| `eps_revisions` \| Count of upward vs downward revisions (7d, 30d) \| Revision breadth — are most analysts raising or cutting? \|
59	\| `growth_estimates` \| Growth rate estimates vs peers and sector \| Relative positioning \|
60	\| `earnings_history` \| Actual vs estimated for last 4 quarters \| Calibration — how good are these estimates historically? \|
61
62	---
63
64	## Step 3: Route Based on User Intent
65
66	The user might want different levels of analysis. Route accordingly:
67
68	\| User Request \| Focus Area \| Key Sections \|
69	\|---\|---\|---\|
70	\| General estimate analysis \| Full analysis \| All sections \|
71	\| "How have estimates changed" \| Revision trends \| EPS Trend + Revisions \|
72	\| "What are analysts expecting" \| Current consensus \| Estimate overview \|
73	\| "Growth estimates" \| Growth projections \| Growth Estimates \|
74	\| "Bull vs bear case" \| Estimate range \| High/low spread analysis \|
75	\| Compare estimates across periods \| Multi-period \| Period comparison table \|
76
77	When in doubt, provide the full analysis — more context is better.
78
79	---
80
81	## Step 4: Build the Estimate Analysis
82
83	### Section 1: Estimate Overview
84
85	Present the current consensus for all available periods from `earnings_estimate` and `revenue_estimate`:
86
87	EPS Estimates:
88
89	\| Period \| Consensus \| Low \| High \| Range Width \| # Analysts \| YoY Growth \|
90	\|---\|---\|---\|---\|---\|---\|---\|
91	\| Current Qtr (0q) \| $1.42 \| $1.35 \| $1.50 \| $0.15 (10.6%) \| 28 \| +12.7% \|
92	\| Next Qtr (+1q) \| $1.58 \| $1.48 \| $1.68 \| $0.20 (12.7%) \| 25 \| +8.3% \|
93	\| Current Year (0y) \| $6.70 \| $6.50 \| $6.95 \| $0.45 (6.7%) \| 30 \| +10.2% \|
94	\| Next Year (+1y) \| $7.45 \| $7.10 \| $7.85 \| $0.75 (10.1%) \| 28 \| +11.2% \|
95
96	Revenue Estimates:
97
98	\| Period \| Consensus \| Low \| High \| # Analysts \| YoY Growth \|
99	\|---\|---\|---\|---\|---\|---\|
100	\| Current Qtr \| $94.

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