How WARN Act Filings Can Signal Stock Moves 60 Days Early

The 60-Day Head Start Nobody Talks About

Here's something most retail traders don't know: when a company is about to lay off hundreds of employees, they're legally required to tell the government 60 days in advance.

It's not a secret. It's not insider information. It's a public filing that anyone can access.

The problem? Most people don't know where to look, and the data is scattered across dozens of state websites in messy Excel files.

That's where the edge is.

What Is the WARN Act?

The Worker Adjustment and Retraining Notification (WARN) Act is a federal law passed in 1988. It requires employers with 100+ employees to provide 60 calendar days advance notice before:

• Mass layoffs (50+ employees at a single site)
• Plant closures
• Major relocations

The notice goes to:
1. Affected employees
2. State dislocated worker units
3. Local government officials

And here's the key: state agencies publish these filings publicly.

Why Layoffs Move Stocks

Layoffs are a leading indicator of financial distress. When a company announces mass layoffs, it typically signals:

• Revenue decline — They're cutting costs because sales are down
• Margin pressure — They can't maintain profitability at current headcount
• Strategic retreat — They're exiting markets or shutting down product lines
• Cash flow problems — Payroll is often the largest expense

The market reaction is usually negative. But by the time the layoffs hit the news, the stock has often already moved.

With WARN filings, you see the signal before the announcement.

The Timeline Advantage

Let's walk through how this works:

By the time CNBC is talking about layoffs, you've known for two months.

What We Track

AlphaSignal monitors WARN filings from multiple states:

California alone accounts for ~12% of U.S. GDP and includes most major tech companies' headquarters.

How We Turn Filings Into Signals

Raw WARN data is messy. Company names don't match ticker symbols. Some filings are for subsidiaries. Some are for tiny facilities that don't matter.

Here's how we filter the noise:

Step 1: Entity Resolution

WARN filings use legal entity names, not ticker symbols. "Meta Platforms, Inc." might be filed as "Facebook Technologies, LLC" (a subsidiary).

We use fuzzy matching and subsidiary mapping to connect filings to the correct ticker.

Step 2: Materiality Scoring

Not all layoffs are equal. 50 people at a 50,000-employee company is a rounding error. 500 people at a 2,000-employee company is a crisis.

We calculate layoff percentage:

Layoff % = (Employees Affected / Total Workforce) × 100

Higher percentages get higher confidence scores.

Step 3: Location Analysis

Is the layoff at headquarters or a remote facility? HQ layoffs are more significant—they often indicate company-wide problems, not just a single underperforming location.

Step 4: Pattern Detection

Is this the first WARN filing, or the third in 30 days? Multiple filings in a short window suggest accelerating distress.

Confidence Score Calculation

Our WARN signals use this scoring model:

A small-cap company filing its second WARN notice in a month, affecting 10% of its workforce at HQ? That's a high-confidence bearish signal.

Signal Types

We categorize WARN filings by type:

Closures are the most bearish—they indicate permanent capacity reduction, not temporary belt-tightening.

Real-World Example

Let's say Company XYZ files a WARN notice on January 15:

• Notice Date: January 15, 2025
• Effective Date: March 16, 2025 (60 days later)
• Layoffs: 800 employees
• Total Workforce: 5,000
• Location: Corporate HQ

Our Signal:
- Type: warn_layoff
- Direction: Bearish
- Layoff %: 16%
- Confidence Boost: +20% (≥10%) + 10% (HQ) = 80% total

This signal appears in AlphaSignal on January 15—the day the filing is published.

The company might not issue a press release until February. The stock might not react until March when layoffs hit.

You had 60 days of lead time.

Why Competitors Don't Cover This

Most trading platforms ignore WARN data because:

1. It's labor-intensive — Data is scattered across 50 state websites in different formats
2. Entity resolution is hard — Matching "Acme Holdings LLC" to $ACME requires sophisticated NLP
3. Low volume — Only ~2,000 filings per year nationally (vs. millions of options trades)
4. Not flashy — Congressional trades and options flow get more attention

But that's exactly why it works. The edge exists where others don't look.

Limitations to Understand

WARN signals aren't perfect. Some caveats:

• Not all states require disclosure — Federal WARN only covers employers with 100+ employees. Some states have lower thresholds; others don't publish at all.
• Delayed publication — States may take days to publish filings after receipt
• False positives — Some filings are precautionary and get rescinded
• Subsidiaries — A subsidiary layoff might not affect the parent company's stock
• Market conditions — In a bull market, even bad news gets shrugged off

That's why WARN signals are part of our fusion system, not standalone alerts. They're weighted alongside 13 other data sources.

How to Use WARN Signals

As confirmation: If you're already bearish on a stock and see a WARN filing, it validates your thesis.

As early warning: Set alerts for tickers you own. A WARN filing might be the first sign to reduce exposure.

For short ideas: High-confidence WARN signals on small-caps can be compelling short candidates.

With other signals: WARN + insider selling + deteriorating technicals = high-conviction bearish setup.

The Bottom Line

The WARN Act creates a legal requirement for transparency. Companies must telegraph their distress 60 days before acting on it.

Most traders ignore this data because it's hard to collect and harder to interpret.

AlphaSignal does the work:
- Aggregates filings from multiple states
- Matches filings to ticker symbols
- Calculates materiality scores
- Integrates with our signal fusion engine

The result? Bearish signals that appear weeks before the news cycle catches up.

That's not a tip. That's regulatory alpha.