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What is a Pre-Earnings Preview?

A pre-earnings preview is a research note published before a company reports its quarterly results. Its purpose is to frame expectations: what does the market expect, what are the key metrics to watch, and what scenarios could play out for the stock? This is essential preparation for both the analyst (who needs to react quickly once results drop) and the portfolio manager (who needs to decide whether to adjust positioning ahead of the event). The core insight behind earnings previews is that stock price reactions are driven by surprise, not absolute performance. A company can report 20% revenue growth and see its stock fall if the market expected 25%. Conversely, a company in decline can rally if results are “less bad” than feared. Understanding the consensus expectation — and where it might be wrong — is the key to anticipating the stock’s reaction. Earnings previews are published 1-5 days before a company reports. At sell-side firms like Goldman Sachs or Barclays, they are distributed to institutional clients. At buy-side firms like Citadel or Millennium, they are prepared internally to inform portfolio positioning.

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Why It Matters

Earnings events are the most concentrated sources of stock volatility. On average, a stock moves 5-8% on earnings day — more than in any normal trading week. For options traders, the “implied move” priced into options tells you exactly how much movement the market expects. If your analysis suggests the actual move will be larger or smaller, there is a trading opportunity. Who uses earnings previews:
  • Portfolio managers deciding whether to add, reduce, or hedge ahead of the report
  • Options traders evaluating whether implied volatility is fairly priced
  • Sales teams preparing talking points for client calls during earnings week
  • The analyst preparing their own reaction framework so they can publish quickly after results

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Key Concepts

TermDefinition
Consensus EstimatesAverage of all sell-side analysts’ forecasts, aggregated by Bloomberg/FactSet
Whisper NumberUnofficial buy-side expectation that may differ from published consensus
Options-Implied MoveThe stock price swing the options market is pricing in for the earnings event
GuidanceManagement’s own forecast, which may differ from consensus
Buy-side SurveyInformal polls of institutional investors on their expectations
Beat RateHistorical percentage of quarters where the company has beaten consensus
Pre-announceWhen a company discloses results (positive or negative) ahead of the scheduled date

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How It Works

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Step 1: Gather Context

Identify the company, reporting quarter, and earnings date/time (pre-market vs. after-hours). Pull consensus estimates via web search for revenue, EPS, and key segment metrics. Review the prior quarter’s earnings call for guidance or commentary that set current expectations.
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Step 2: Build the Key Metrics Framework

Identify the 3-5 metrics that will determine the stock’s reaction, ranked by importance. These vary by sector: for SaaS companies, net retention and RPO matter most; for retailers, same-store sales and inventory levels; for banks, net interest margin and credit quality. Financial metrics (revenue, EPS, margins) always matter, but the operational metrics are often what drive the surprise.
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Step 3: Build Scenario Analysis

Construct bull/base/bear scenarios with specific revenue and EPS ranges, the key driver for each scenario, and the expected stock price reaction. Use historical context — how has the stock moved on similar beats or misses in prior quarters?
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Step 4: Create the Catalyst Checklist

Identify the 3-5 specific things that will determine the stock’s post-earnings direction. For example: “Guidance for next quarter above $X would signal demand acceleration” or “If gross margin falls below X%, it confirms pricing pressure.” This is the most actionable part of the preview.
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Step 5: Produce the One-Page Output

Compile into a single-page preview: company/quarter/date, consensus estimates table, key metrics to watch (ranked), bull/base/bear scenario table, catalyst checklist, and trading setup (recent stock performance, implied move).
Sector-Specific Operational Metrics:
ARR, net retention, RPO, customer count, net new ARR, gross margin
Same-store sales, traffic, basket size, inventory levels, e-commerce penetration
Backlog, book-to-bill ratio, price vs. volume growth, capacity utilization
Net interest margin, credit quality (NPLs, charge-offs), loan growth, fee income
Scripts, patient volumes, pipeline updates, reimbursement rate changes

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How to Add to Your Local Context

# Install the plugin
claude plugin install equity-research@financial-services-plugins
Customizing for your firm: If your firm has a specific preview template or requires additional sections (e.g., options analysis, ownership data), edit the skill file: 
open ~/.claude/skills/equity-research/earnings-preview.md
Connecting to live data: To pull real-time consensus estimates and options-implied moves, configure your data provider in .mcp.json: 
{
  "mcpServers": {
    "factset": {
      "command": "factset-mcp-server",
      "args": ["--credentials", "path/to/creds.json"]
    }
  }
}

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Best Practices

  • Note the source and date of estimates: Consensus estimates change daily during earnings week. Always timestamp which consensus you used.
  • Include the options-implied move: This tells you what the market expects. If you think the actual move will be 10% but options imply 5%, that is a meaningful insight.
  • Study historical reactions: Search for “[company] earnings reaction history” to calibrate expectations. Some companies consistently beat-and-raise; others beat on revenue but miss on margins.
  • Distinguish consensus from buy-side expectations: Published consensus and what large investors actually expect can diverge significantly. If available, include buy-side survey data.
  • Flag pre-announce risk: Some companies have a history of pre-announcing. Track this pattern.
  • Time your publication: If writing early (6am), note that pre-market moves may change by open.