Two major analyses recently asked whether insider buying works, and both found a weak, short-lived signal. Both reached the right conclusion about the wrong dataset: when every insider purchase is treated as equal, the noise drowns out the signal. Our own decade-long backtest of filtered insider buying returns shows how different the picture looks when each trade is scored first.

In February 2026, the Wall Street Journal published an analysis of roughly 1,400 insider purchases across S&P 500 companies over five years. The headline finding: insider buying produced a median gain of 2% at 30 days, but the signal faded quickly after that. Only 15% of stocks fully rebounded from prior declines. The head of research at Verity, the data firm that provided the underlying dataset, summarized it bluntly: the bullish signal "sort of wears off."

In April 2026, an independent researcher on Reddit's r/ValueInvesting community published their own analysis using a much larger dataset: 906,000 Form 4 filings, from which they isolated 3,236 C-suite purchases of $100,000 or more. Their findings were similar. Statistically significant outperformance at 5 to 10 days, but the signal faded by 30 days and underperformed the S&P 500 at the 60 to 90 day mark.

Two independent analyses with two different datasets reached the same conclusion: insider buying, treated as a binary event, is a weak and short-lived signal. Both are sound as far as they go, and both share the same blind spot.

The problem with treating all buys equally

Both the WSJ analysis and the Reddit backtest treat insider buying as a yes-or-no question: did an insider buy? If yes, measure what happened next. This is a reasonable starting point, but it collapses a huge amount of variation into a single binary signal.

Consider the difference between these two filings, both classified as "insider purchases":

A director buys $25,000 of stock on a quarterly schedule through a pre-arranged 10b5-1 plan. They've made the same purchase every quarter for three years. Their total position is worth $15 million. This is administrative portfolio maintenance.

A CEO buys $10 million of stock on the open market three days after a 35% price decline, with no 10b5-1 plan, doubling their personal stake. This is a deliberate, conviction-driven bet.

Any analysis that treats these two events as equivalent will find a weak signal, because the first type of transaction is far more common than the second, and it's noise. The second type is rare and potentially informative. Averaging them together means the result mostly measures the noise.

The WSJ implicitly acknowledged this. Their analysis found that "cluster buys" (multiple insiders purchasing within the same window) performed better than single purchases. But this finding was buried in the middle of the article, not reflected in the headline.

What the data shows when you filter

The Reddit backtest, despite its binary framing, surfaced the same pattern in more detail. When the researcher isolated cluster buys, where multiple executives purchase within a short window, the 10-day return jumped to +2.41%, compared to +0.50% for single purchases. That's nearly a 5x difference, and it was statistically significant.

Sector mattered too. Healthcare and biotech insider purchases returned +4.8% at 5 days. Real estate was roughly flat. The signal isn't uniform; it concentrates in sectors where insiders have larger information asymmetry. This aligns with earlier findings by Seyhun (1986) and Lakonishok and Lee (2001), who showed that the informational content of insider trades varies significantly by the insider's proximity to operations.

The WSJ found that 69% of insider purchases occurred after the stock had already declined in the prior 30 days. This is important context. Most insider buying is contrarian: executives tend to buy after price drops, not at all-time highs. That means the post-purchase "recovery" the data measures is often a reversion trade, not a momentum signal. And reversion trades are inherently time-limited, which explains why the signal fades.

None of this means insider buying is useless. It means the question "did an insider buy?" is the wrong question. The right questions are: which insider? How much? In what context? Was it planned or discretionary? Was it isolated or part of a cluster? How does this trade compare to the historical baseline for this type of transaction?

Real examples from recent filings

Three recent filings show how much variation hides inside the single category of "insider purchase."

In early 2026, Palo Alto Networks CEO Nikesh Arora purchased roughly $10 million in company stock during what the market was calling the "SaaS apocalypse," a broad selloff across enterprise software names driven by fears that generative AI would displace incumbents. The trade reached Strong tier in our model, well above the baseline for CEO purchases. Looking back, the stock subsequently recovered. That doesn't mean the tier predicted the recovery; it means the model identified this as an unusually high-conviction purchase at the time it was filed.

Around the same period, AMD's CTO made repeat open-market purchases totaling approximately $1 million across multiple transactions, each reaching Elite tier. These weren't scheduled transactions. They were discretionary buys from the person closest to AMD's product roadmap, made during a period of price weakness.

Contrast that with Reddit Inc. (RDDT), where multiple C-suite insiders have made regular purchases that consistently fall into Caution tier, the lowest classification. These are routine, small-scale buys consistent with compensation-related activity or scheduled plans. They technically count as "insider purchases" and would be included in any binary analysis, but they carry minimal informational content.

A study that counts the PANW and AMD trades the same as the RDDT trades will find a weak average signal. The weak average doesn't show that insider buying fails; it shows the analysis isn't separating signal from noise.

Why the signal "wears off"

The Verity researcher's observation that the signal "wears off" deserves a closer look, because it points to something the WSJ article didn't explore.

Insider buying is disclosed through Form 4, which must be filed within two business days of the transaction. In theory, the market has access to this information almost immediately. In practice, most retail investors discover insider buys days or weeks later, through screeners, newsletters, or financial media coverage. For European investors, the lag is often even longer, since most EU-focused finance media doesn't cover individual SEC filings at all.

By the time the average investor sees an insider purchase, the initial momentum from the disclosure has already been absorbed. The signal hasn't "worn off" in some fundamental sense. It's been priced in by faster participants. The WSJ measured the signal starting from the filing date. Investors who find out a week later are starting from a different price.

This is a timing and access problem, not a signal quality problem. The information is public, but information that arrives late is worth less.

A different approach to the same data

Both the WSJ and the Reddit backtest confirm that insider buying contains information, at least in the short window immediately following the filing. The more useful question is whether you can systematically identify which insider purchases are most informative before the signal decays.

Scoring models attempt to answer that question. Instead of asking "did someone buy?", our model asks "is this buy unusual?" It evaluates each transaction against historical baselines for that role, that transaction size, and that market context. Anomalous trades, like a CEO making a purchase far larger than their historical pattern or multiple insiders buying simultaneously during a price decline, land in Elite or Strong tier. Routine trades, like a director's scheduled quarterly buy or a VP exercising options, land in Neutral or Caution tier.

The goal isn't to predict stock prices. It's to separate the filings that carry genuine informational content from the ones that are administrative noise. When the WSJ says the signal "wears off," we'd argue the noise never had a signal to begin with. The filings that actually carry conviction, top-tier trades from operationally involved insiders, tell a different story than the aggregate average.

What this means for investors

Insider buying is a real signal, but it's a filtered signal. The raw data (all filings, all insiders, all transaction types) produces the weak, short-lived pattern that the WSJ documented. The filtered data (discretionary purchases, high-conviction insiders, unusual transaction sizes, cluster patterns) produces something more useful.

The research community has spent decades establishing that insider buying "works" on average. The more productive question, the one both the WSJ and the Reddit analysis point toward without fully answering, is which insider buying works and why. That's where the analysis starts, not where it ends.

Related Reading

• What Happens When You Invest $100 in Every High-Conviction Insider Signal for a Decade: The full simulation showing what happens when you act only on filtered, top-tier signals.
• Does Insider Buying Beat the Market?: Why scored insider purchases outperformed while raw insider-following lagged.
• The Timing Edge: Why Speed Matters in Insider Trading Signals: A deeper look at the signal decay the WSJ measured and what it means for investors who act late.

For informational purposes only. Not investment advice.