forward-earnings

name	forward-earnings
description	Analyzes forward EPS revision direction and analyst consensus momentum across S&P 500 sectors. Use when user asks about earnings outlook, analyst revisions, sector momentum, or as part of Druckenmiller-style analysis. Triggers on: 'what are forward earnings doing', 'which sectors have earnings momentum', 'analyst revisions', 'run forward earnings analysis', 'earnings expectations', '盈利預期', '分析師修正方向', '板塊盈利動能', '前瞻盈利'.
version	2.0.0
author	howard
source_principle	Druckenmiller (New Market Wizards, 1992): 'What a company's been earning doesn't mean anything. What you have to look at is what people think it's going to earn. If you can see something in two years is going to be entirely different than the conventional wisdom, that's how you make money.'
outputs	[{"overall_score":"0-100 integer"},{"overall_direction":"beat | miss | neutral"},{"sector_ranking":"list of sectors sorted by forward EPS momentum"},{"summary_json":"reports/forward_earnings_YYYY-MM-DD.json"},{"summary_md":"reports/forward_earnings_YYYY-MM-DD.md"}]
api_keys_required	[]
data_source	Yahoo Finance via yfinance (free, no API key required)

Forward Earnings Analyzer

Purpose

Track whether analyst consensus EPS estimates are being revised up or down across S&P 500 sectors. Uses genuinely forward-looking analyst data, not historical actuals. This is the second input (25% weight) into conviction-synthesizer.

Theoretical basis: Druckenmiller explicitly said current earnings are irrelevant -- what matters is the direction consensus is moving over the next 18-24 months. Rising EPS revisions = market hasn't fully priced the move yet = opportunity.

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What This Skill Measures

Signal	Source	What it captures
EPS revisions (30d)	yf.Ticker.eps_revisions	Net analysts upgrading vs downgrading in last 30 days
EPS trend vs 30d ago	yf.Ticker.eps_trend	Direction consensus is moving
Next-year growth estimate	yf.Ticker.growth_estimates	Analyst forecast for next FY

All three are forward-looking. No historical EPS used. Coverage: 9 GICS sectors x 10 representative large-caps = 90 stocks.

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Execution

Step 1: Install yfinance (one time)

conda activate druck
pip install yfinance

Step 2: Run

cd druckenmiller-skills
python forward-earnings\scripts\forward_earnings.py --output-dir reports\

Runtime: ~4-5 minutes (90 stocks x 0.3s delay).

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Scoring Logic

For each ticker: revision_score = (up_30d - down_30d) / (up_30d + down_30d) trend_score = (current_eps - eps_30d_ago) / eps_30d_ago composite = revision_score * 0.5 + trend_score * 0.3 + growth_contribution * 0.2 direction = "up" if composite > 0.15 else "down" if < -0.15 else "neutral"

For each sector: breadth_score = 50 + (up_count - down_count) / total * 40 sector_score = breadth * 0.5 + revision * 0.3 + growth * 0.2

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Direction Classification

Direction	Condition	Implication
beat	6+ sectors = "up"	Consensus underestimating -- opportunity
miss	6+ sectors = "down"	Consensus too optimistic -- risk
neutral	Mixed	Use other signals as primary

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Known Limitations

• yfinance reflects Yahoo Finance consensus, not Bloomberg/FactSet
• Growth estimates > 200% are capped to prevent distortion from negative base EPS
• Delisted tickers (e.g. PXD) return warnings but do not break the run

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Integration with conviction-synthesizer

fwd = load_json("reports/forward_earnings_latest.json")
score      = fwd["overall_score"]        # 0-100
direction  = fwd["overall_direction"]    # beat / miss / neutral
top_sector = fwd["sector_ranking"][0]["sector"]

Weight in synthesizer: 25%