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Estimate Analysis Skill
Deep-dives into analyst estimates and revision trends using Yahoo Finance data via 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.
Important: Data is for research and educational purposes only. Not financial advice. yfinance is not affiliated with Yahoo, Inc.
Step 1: Ensure yfinance Is Available
Current environment status:
!`python3 -c "import yfinance; print('yfinance ' + yfinance.__version__ + ' installed')" 2>/dev/null || echo "YFINANCE_NOT_INSTALLED"`
If YFINANCE_NOT_INSTALLED, install it:
import subprocess, sys
subprocess.check_call([sys.executable, "-m", "pip", "install", "-q", "yfinance"])
If already installed, skip to the next step.
Step 2: Identify the Ticker and Gather Estimate Data
Extract the ticker from the user's request. Fetch all estimate-related data in one script.
import yfinance as yf
import pandas as pd
ticker = yf.Ticker("AAPL") # replace with actual ticker
# --- Estimate data ---
earnings_est = ticker.earnings_estimate # EPS estimates by period
revenue_est = ticker.revenue_estimate # Revenue estimates by period
eps_trend = ticker.eps_trend # EPS estimate changes over time
eps_revisions = ticker.eps_revisions # Up/down revision counts
growth_est = ticker.growth_estimates # Growth rate estimates
# --- Historical context ---
earnings_hist = ticker.earnings_history # Track record
info = ticker.info # Company basics
quarterly_income = ticker.quarterly_income_stmt # Recent actuals
What each data source provides
Data Source
What It Shows
Why It Matters
earnings_estimate
Current EPS consensus by period (0q, +1q, 0y, +1y)
The estimate levels — what analysts expect
revenue_estimate
Current revenue consensus by period
Top-line expectations
eps_trend
How the EPS estimate has changed (7d, 30d, 60d, 90d ago)
Revision direction — rising or falling expectations
eps_revisions
Count of upward vs downward revisions (7d, 30d)
Revision breadth — are most analysts raising or cutting?
growth_estimates
Growth rate estimates vs peers and sector
Relative positioning
earnings_history
Actual vs estimated for last 4 quarters
Calibration — how good are these estimates historically?
Step 3: Route Based on User Intent
The user might want different levels of analysis. Route accordingly:
User Request
Focus Area
Key Sections
General estimate analysis
Full analysis
All sections
"How have estimates changed"
Revision trends
EPS Trend + Revisions
"What are analysts expecting"
Current consensus
Estimate overview
"Growth estimates"
Growth projections
Growth Estimates
"Bull vs bear case"
Estimate range
High/low spread analysis
Compare estimates across periods
Multi-period
Period comparison table
When in doubt, provide the full analysis — more context is better.
Step 4: Build the Estimate Analysis
Section 1: Estimate Overview
Present the current consensus for all available periods from earnings_estimate and revenue_estimate:
EPS Estimates:
Period
Consensus
Low
High
Range Width
# Analysts
YoY Growth
Current Qtr (0q)
$1.42
$1.35
$1.50
$0.15 (10.6%)
28
+12.7%
Next Qtr (+1q)
$1.58
$1.48
$1.68
$0.20 (12.7%)
25
+8.3%
Current Year (0y)
$6.70
$6.50
$6.95
$0.45 (6.7%)
30
+10.2%
Next Year (+1y)
$7.45
$7.10
$7.85
$0.75 (10.1%)
28
+11.2%
Revenue Estimates:
Period
Consensus
Low
High
# Analysts
YoY Growth
Current Qtr
$94.3B
$92.1B
$96.8B
25
+5.4%
Next Qtr
$102.1B
$99.5B
$105.0B
22
+6.1%
Calculate and flag:
Range width as % of consensus — wide ranges (>15%) signal high uncertainty
Analyst coverage — fewer than 5 analysts means thin coverage, note this
Growth trajectory — is growth accelerating or decelerating across periods?
Section 2: Revision Trends (EPS Trend)
This is often the most actionable section. From eps_trend, show how estimates have moved:
Period
Current
7 Days Ago
30 Days Ago
60 Days Ago
90 Days Ago
Current Qtr
$1.42
$1.41
$1.40
$1.38
$1.35
Next Qtr
$1.58
$1.57
$1.56
$1.55
$1.54
Current Year
$6.70
$6.68
$6.65
$6.58
$6.50
Next Year
$7.45
$7.43
$7.40
$7.35
$7.28
Summarize the trend: "Current quarter EPS estimates have risen 5.2% over the last 90 days, with most of the increase in the last 30 days — accelerating upward revision momentum."
Key interpretation:
Rising estimates ahead of earnings = positive setup (the bar is rising)
Falling estimates = analysts cutting numbers, often a negative signal
Flat estimates = no new information being priced in
Recent acceleration/deceleration matters more than the total move
Section 3: Revision Breadth (EPS Revisions)
From eps_revisions, show the up vs. down count:
Period
Up (last 7d)
Down (last 7d)
Up (last 30d)
Down (last 30d)
Current Qtr
5
1
12
3
Next Qtr
3
2
8
5
Calculate a revision ratio: Up / (Up + Down). Ratios above 0.7 are strongly bullish; below 0.3 are bearish.
Section 4: Growth Estimates
From growth_estimates, compare the company's expected growth to benchmarks:
Entity
Current Qtr
Next Qtr
Current Year
Next Year
Past 5Y Annual
AAPL
+12.7%
+8.3%
+10.2%
+11.2%
+14.5%
Industry
+9.1%
+7.0%
+8.5%
+9.0%
—
Sector
+11.3%
+8.8%
+10.0%
+10.5%
—
S&P 500
+7.5%
+6.2%
+8.0%
+8.5%
—
Highlight whether the company is expected to grow faster or slower than its peers.
Section 5: Historical Estimate Accuracy
From earnings_history, assess how reliable estimates have been:
Quarter
Estimate
Actual
Surprise %
Direction
Q3 2024
$1.35
$1.40
+3.7%
Beat
Q2 2024
$1.30
$1.33
+2.3%
Beat
Q1 2024
$1.52
$1.53
+0.7%
Beat
Q4 2023
$2.10
$2.18
+3.8%
Beat
Calculate:
Beat rate: X of 4 quarters
Average surprise: magnitude and direction
Trend in surprise: Are beats getting bigger or smaller? A shrinking surprise with rising estimates could mean the bar is catching up to reality.
Step 5: Synthesize and Respond
Present the analysis with clear structure:
Lead with the key insight: "AAPL estimates are trending higher across all periods, with positive revision breadth (80% of recent revisions are upward)."
Show the tables for each section the user cares about
Provide interpretive context:
Is the revision trend confirming or contradicting the stock's recent price action?
How does the growth outlook compare to what's priced into the current P/E?
What's the relationship between estimate accuracy history and current estimate levels?
Flag risks and nuances:
Estimates cluster around consensus — the "real" distribution of outcomes is wider than low/high suggests
Revision momentum can reverse quickly on a single data point (guidance change, macro event)
Yahoo Finance estimates may lag behind real-time consensus providers by hours or days
Growth estimates for out-years (+1y) are inherently less reliable
Caveats to always include
Analyst estimates reflect a consensus view, not certainty
Estimate revisions are a signal but not a guarantee of future performance
This is not financial advice
Reference Files
references/api_reference.md — Detailed yfinance API reference for all estimate-related methods
Read the reference file when you need exact return formats or edge case handling.don't have the plugin yet? install it then click "run inline in claude" again.