When Insider Buying Actually Works

Don't outsource your judgment

When does copying insider buying actually pay?

We took every meaningful open-market insider purchase since 2006 — 36,631 of them — and asked one simple question about each: if you had bought the same stock the day the filing became public and held it for three months, would you have beaten a plain index fund? This page is the answer, split by the kind of market it happened in and by industry — because it turns out those two things decide almost everything.

When and where insider buying has worked

Pick an industry, the kind of market, and a period. Green: insider buys, each held 3 months. Grey: the small-company index over the same dates. Where green pulls away, the buys beat the index. The boxes underneath are the evidence for exactly what you picked.

See today's stocks that match this →
Research chart, not an account curve: each point adds one month's average 3-month result, so overlapping holdings, position sizes and trading costs are not modelled (our costed account test is on the research hub). Rule: opportunistic open-market insider purchases, bought at the open of the second trading day after the filing, held 63 trading days, versus IWM on the same dates; one buy per company per month; price at least $3 and at least $1M traded a day. Stocks that were later delisted are included; a failed company counts as a total loss. Pink bands are stressed markets. Confidence counts months, not buys: Solid = very unlikely to be luck, Weak = could be luck, Unproven = treat as chance. Data 2026-09-14.
The verdict, plainly

Re-run 14 September 2026 without survivorship bias. The chart above now includes every stock, including the roughly one in three that later delisted (a bankruptcy counts as a total loss, a buyout at its final price), and buys at the open of the second trading day after the filing. Every table on this page has been rebuilt the same way. The edge is much smaller than we first published: +0.5% per buy overall, with the typical buy slightly behind the index. In months when the S&P was at least 10% below its high, buys did about +1.9% (confidence: weak); in calm months, about zero. Our earlier figures, such as +4.8% in the 2008 crisis, came from companies that survived and overstated the edge.

In most markets, you would likely have done about as well just buying an index fund. Once stocks that later went bust are counted, the edge from copying insider buys outside a crisis is under half a point over three months, before trading costs, and the typical buy trailed the index. The one place the edge has been clear is the 2008 crash and the recovery after it (+2.6% and +1.2%, both very unlikely to be luck). The later sell-offs of 2011, 2015, 2020 and 2022 did not repeat it. Insider buying is context worth checking in a frightening market, not an everyday replacement for an index fund.

Which state are we in right now?
NORMAL MARKET
The S&P 500 is 3.1% below its 1-year high (as of 2026-09-16).
Our published rule — simple on purpose, so it cannot be bent later: stress = S&P at least 10% below its 1-year high; borderline from 5%; normal otherwise. Every stress window in this study would have tripped it.
Which past months look most like today?
Matching today's measured conditions (3- and 6-month return, distance from the high, volatility) against every month since 2007, the closest matches are: 2007-02 (Late credit boom) · 2012-11 (Mid-cycle bull) · 2019-07 (Late-cycle bull) · 2021-11 (Stimulus melt-up) · 2026-01 (AI-led recovery (now))
1 of 5 nearest matches sit in the Late credit boom period — so by measured conditions, that is the era today most resembles.
This matches measured conditions, not chart shapes. We deliberately do not use Elliott-wave-style pattern matching — it has no out-of-sample evidence behind it. Resemblance is context, not a forecast.
The three things this page says, in one breath

1. It worked best in one frightened market: 2008. Buys during the financial crisis beat the index by +2.6% over 3 months, and +1.2% in the recovery after it. Later sell-offs did not repeat that; the 2022 rate shock was −1.6%.

2. The rest of the time the edge is close to zero — under half a point on average, before trading costs, and the typical buy trailed the index.

3. Industry matters, but less than it first looked. Only construction shows an edge that is very unlikely to be luck. Banks (one in seven buys) show none. Energy, utilities and food companies lagged in calm markets and only did well during sell-offs.

How to read every number on this page (there is only one measure)

Every percentage below answers the same question: how much better (or worse) did these buys do than a small-company index fund (the Russell 2000, via IWM) over the following 3 months?

Worked example: +2.6% means that if the index fund returned 0% over those 3 months, the insider-buy stocks returned +2.6% on average. If the fund fell 20%, they fell about 17.4%. The number is the gap, not the raw return.

Why compare to a small-company fund and not the S&P 500? Because insider buying happens mostly at small companies. Compare those to the S&P and you are really measuring company size, not stock-picking. (Since late 2022 the S&P has beaten small-caps by ~36 points — that alone would make any small-cap list look terrible.)

"Average" vs "typical": the average can be dragged up by a few huge winners. The typical (median) figure is what the middle trade did — when the two disagree a lot, most trades did worse than the average suggests, and we say so. Confidence is shown in words: Solid = very unlikely to be luck, Weak = could be luck, Unproven = treat as chance. (The raw statistics are in the fold at the bottom.)

1 · Eleven kinds of market, one test each

A single 20-year average would hide the whole story, because it would blend crashes into booms. So we split 2006–today into eleven periods by what the market was actually doing, and ran the identical test inside each. Amber rows are the stress periods. Bars to the right of the line = the buys beat the index fund; left = they lagged it.

Late credit boom
2006-01 → 2007-10 · 2,263 buys tested
-0.1%
Weak
Cheap credit, a housing market still rising, volatility near record lows. Everything worked, so a buy signal looks good without being informative.
Global financial crisis MARKET STRESS
2007-10 → 2009-03 · 3,821 buys tested
+2.6%
Solid
The S&P fell roughly 57% from peak to the March 2009 trough. Lehman and Washington Mutual failed. The hardest test there is — and the signal's best window. Insiders bought heavily into the decline and were right.
Post-crisis recovery
2009-03 → 2011-04 · 3,093 buys tested
+1.2%
Solid
A violent recovery off the March 2009 low, powered by the first rounds of quantitative easing. Beaten-down names rebounded hardest and insiders had been buying exactly those.
Euro crisis & US downgrade MARKET STRESS
2011-04 → 2011-10 · 1,049 buys tested
-0.1%
Unproven
The US lost its AAA rating; the eurozone debt crisis escalated. A fast ~19% drawdown with no recession behind it. A macro scare, not a solvency event — fundamentals were intact while prices fell. Exactly where insiders have an edge.
Mid-cycle bull
2011-10 → 2015-05 · 5,850 buys tested
-0.1%
Unproven
A long, low-volatility advance on expanding margins and near-zero rates. The base case — what the signal is worth in ordinary conditions.
Oil bust & industrial recession MARKET STRESS
2015-05 → 2016-02 · 1,543 buys tested
-0.1%
Unproven
Crude fell from about $60 to $26; energy and industrials went through an earnings recession. A sector-specific collapse — and the window where energy insiders proved most valuable.
Late-cycle bull
2016-02 → 2020-02 · 6,990 buys tested
+0.4%
Solid
Tax cuts, buybacks and rising megacap concentration carried the index to the pre-COVID peak. Narrow leadership. An equal-weighted signal is structurally underweight what worked.
COVID crash MARKET STRESS
2020-02 → 2020-03 · 649 buys tested
+0.7%
Unproven
A 34% fall in 23 trading days — the fastest bear market on record. Too fast for anyone to have an edge. The average is positive but the TYPICAL trade lost — a few huge winners carried it.
Stimulus melt-up
2020-03 → 2021-12 · 3,187 buys tested
+0.6%
Unproven
Emergency rate cuts, fiscal transfers and a retail-driven rally that lifted almost everything. The most permissive conditions in the sample — treat a strong number here with suspicion.
Inflation & rate shock MARKET STRESS
2022-01 → 2022-10 · 1,682 buys tested
-1.6%
Weak
The fastest tightening cycle since 1981. The index bottomed on 12 October 2022. A valuation reset rather than a solvency crisis — the discount rate changed, not the businesses. The signal was flat.
AI-led recovery (now)
2022-10 → today · 6,504 buys tested
+0.4%
Weak
A recovery led by a narrow group of very large technology companies. No measurable edge — statistically indistinguishable from zero. This matches the live 13-month backtest over the same window.

The pattern: the two clearly positive periods are the 2008 crisis and the recovery right after it. The other sell-offs were flat or negative, and in ordinary bull markets the edge is a fraction of a point. That is why we describe insider buying as a weak signal that has mattered mainly in a deep panic, not an everyday money machine. Anyone who quotes you one blended average for "insider buying beats the market" is leaning on 2008 and hoping you don't ask.

The exact trade we tested (and how you would follow it)

The rule: when an insider files a genuine open-market purchase — not a scheduled 10b5-1 plan, not a routine same-month-every-year habit — buy the same stock at the open of the second trading day after the filing appears, in an equal dollar amount, and sell after 63 trading days (~3 months). One buy per company per month; stocks priced at $3 or more with at least $1 million traded a day. No discretion, no exceptions. Every number on this page is that one rule, applied 36,631 times.

Where you would see these trades: the live signals feed is exactly this filter running in real time — each row is a qualifying filing, already screened the same way the study screened. What the study adds is the context: when (frightened markets) and where (which industries) that rule has actually paid, and when it has not.

Every strategy, in every kind of market

These are the same strategies the live scorecard tracks — run through the full 20 years instead of 13 months, one column per market period. Each cell: how much that strategy's buys beat (green) or lagged (red) the small-cap index over the next 3 months. Hover a cell for the trade count. The pattern to notice: almost every row is green in the 2008 crisis column and mostly red in the rate-shock column. The strategy you pick matters less than the market you are in. Many cells rest on a few hundred trades, so single cells are noisy.

Strategy Late credit boom2008 crisisPost-crisis recoveryEuro crisisMid-cycle bullOil bustLate-cycle bullCOVID crashStimulus melt-upRate shockNow (AI era)
All qualifying buys -0.1% +2.6% +1.2% -0.1% -0.1% -0.1% +0.4% +0.7% +0.6% -1.6% +0.4%
Cluster buys (>=3 insiders) -0.4% +4.8% 0.0% -1.2% -0.5% +0.4% +1.6% +3.9% -2.8% +2.6% -0.2%
Brand-new position -0.4% +2.2% +2.8% -0.8% -1.2% -0.4% +0.8% -1.1% -2.0% -1.4%
Grew stake 30-99% +0.1% +2.9% +2.5% -1.1% +0.5% +1.5% +0.9% +1.8% -1.1% -2.5% +1.7%
Grew stake 100%+ -0.7% +4.5% -0.6% -5.4% +0.1% -0.9% +0.6% +4.5% -0.6% +0.1% -2.0%
CFO / COO tier -0.9% +4.6% +3.5% -2.3% +0.9% 0.0% +0.5% +4.1% +1.4% -1.4% +0.2%
Directors -0.4% +2.0% +1.1% +0.7% -0.2% +1.3% +0.5% +0.4% +0.5% -0.6% +0.5%
Officers +0.2% +4.1% +2.1% -1.2% -0.1% -1.3% -0.1% +0.9% +1.4% -1.8% -0.3%
$100K+ buys +0.8% +2.7% +2.1% -1.3% +0.2% -0.3% +0.9% +2.0% +0.7% -2.6% +1.1%

Where are the Overreaction and below-insider-cost strategies? They cannot be reconstructed over 20 years, and we would rather leave a gap than fake one. Overreaction requires knowing that every seller was on a pre-scheduled 10b5-1 plan — the disclosure checkbox for that only exists since April 2023. Below-insider-cost requires the insider's own fill price compared to the market at scan time, which the historical record does not retain. Both remain on the live scorecard, where they are measured forward in real time — their strong 13-month numbers are promising and unproven at 20-year scale, and that is exactly how we label them.

2 · Where it works — by industry

Two definitions before the table (the two columns people ask about)

"In market stress" = the same test, restricted to buys made during the five dated windows below. "In normal markets" = every other time between 2006 and today.

  • Global financial crisis (Oct 2007 – Mar 2009) — S&P 500 fell ~57%; Lehman and Washington Mutual failed
  • Euro crisis & US downgrade (Apr – Oct 2011) — US lost its AAA rating; a fast ~19% drop
  • Oil bust (May 2015 – Feb 2016) — crude fell from ~$60 to $26; energy earnings collapsed
  • COVID crash (Feb – Mar 2020) — 34% fall in 23 trading days
  • Inflation & rate shock (Jan – Oct 2022) — fastest rate-hiking cycle since 1981

"This sector today" is live, not historical: we track each industry through a well-known sector fund (named in the table) and call it "being sold off" when that fund is at least 10% below its own 1-year high. Why it matters: for some industries the entire edge only exists in that condition.

Industry Edge vs index fund Average Typical trade Confidence In market stress In normal markets This sector today
Mining & metals
32 companies · 208 buys
+6.3% -3.2% Unproven -0.2% +8.4% 18% below its 1-yr high — being sold off now
tracked via XME
Construction
52 companies · 375 buys
+4.1% +2.1% Solid +6.6% +3.1% 25% below its 1-yr high — being sold off now
tracked via ITB
Healthcare services
78 companies · 350 buys
+3.3% +1.4% Weak -3.9% +5.6% 5% below its 1-yr high — normal
tracked via XLV
Tech hardware & semis
251 companies · 1,272 buys
+1.8% +0.0% Weak +4.2% +1.0% 18% below its 1-yr high — being sold off now
tracked via SMH
Transport & logistics
118 companies · 902 buys
+1.3% -0.1% Unproven +0.8% +1.4% 11% below its 1-yr high — being sold off now
tracked via IYT
Industrials & manufacturing
743 companies · 5,624 buys
+1.3% -0.1% Weak +1.0% +1.3% 10% below its 1-yr high — normal
tracked via XLI
Software & IT services
333 companies · 1,468 buys
+1.2% +0.1% Unproven +1.1% +1.2% 11% below its 1-yr high — being sold off now
tracked via IGV
Insurance
158 companies · 1,348 buys
+0.9% +0.0% Unproven +0.6% +1.0% 6% below its 1-yr high — normal
tracked via KIE
Biotech & pharma
582 companies · 3,003 buys
+0.7% -3.4% Unproven -0.2% +0.9% 9% below its 1-yr high — normal
tracked via XBI
Medical devices
165 companies · 789 buys
+0.6% -1.2% Weak +0.4% +0.7% 20% below its 1-yr high — being sold off now
tracked via IHI
Finance & real estate
180 companies · 1,304 buys
+0.6% -0.9% Unproven +0.2% +0.8% 5% below its 1-yr high — normal
tracked via XLF
Services
340 companies · 2,271 buys
+0.5% -0.1% Weak -0.9% +1.0% not tracked
Retail & consumer
253 companies · 2,147 buys
+0.3% -0.9% Unproven +2.5% -0.4% 12% below its 1-yr high — being sold off now
tracked via XLY
Telecom & media
75 companies · 503 buys
+0.1% -1.0% Unproven -0.5% +0.2% 6% below its 1-yr high — normal
tracked via XLC
Banks
356 companies · 5,022 buys
0.0% -0.6% Unproven +0.8% -0.3% 7% below its 1-yr high — normal
tracked via KRE
Other
210 companies · 1,621 buys
-0.3% -1.3% Weak -0.1% -0.4% not tracked
REITs
219 companies · 2,688 buys
-0.4% -0.4% Unproven -0.8% -0.3% 7% below its 1-yr high — normal
tracked via VNQ
Energy
270 companies · 2,376 buys
-0.5% -1.6% Solid +1.9% -1.2% 3% below its 1-yr high — normal
tracked via XLE
Food, drink & tobacco
91 companies · 685 buys
ONLY WORKS IN A SELLOFF
-0.5% -1.0% Unproven +3.3% -1.6% 7% below its 1-yr high — normal
tracked via XLP
Utilities
99 companies · 1,179 buys
-0.5% -0.3% Weak +2.2% -1.4% 13% below its 1-yr high — being sold off now
tracked via XLU
Unknown
159 companies · 1,496 buys
-0.7% -0.3% Solid -0.1% -0.9% not tracked

What to actually take from that table

Banks are one in seven insider buys and carry no edge. Community-bank directors buy small amounts constantly — it is closer to a savings habit than a view on the business. They used to crowd the top of our live feed on sheer volume; we now rank them down, and every demoted signal on the feed says so and why.

Energy, utilities and food companies flip sign. Insider buying in energy beat the index by about +1.9% during the five stress windows and lagged it by about 1.2 points the rest of the time. Utilities (+2.2% against −1.4%) and food, drink & tobacco (+3.3% against −1.6%) show the same shape. The "This sector today" column above shows which of them is under pressure right now.

The biggest numbers are the least trustworthy. Mining & metals averages +6.3%, but the typical trade lost 3.2% and only about 200 buys stand behind it. Construction is the only industry where the edge is very unlikely to be luck (+4.1% across 375 buys). Industrials & manufacturing, the largest group with over 5,600 buys, shows +1.3% with weak confidence.

3 · What this page cannot tell you

No trading costs. These are small, often illiquid stocks; spreads and slippage could eat all of a half-point edge.
Delisted stocks are included, with simple rules. A bankruptcy counts as a total loss and a buyout is sold at the final traded price. A deregistration or an unexplained delisting keeps its final price, unless that price was under $1, in which case it counts as zero. Real buyout payments and bankruptcy recoveries can differ from these rules.
History, not prophecy. This describes 2006–today. The next crisis is under no obligation to look like the last five.
An average is not you. These are averages over thousands of trades. Any single trade can and does do anything.

For the statistically inclined — method & the raw numbers
Universe: all open-market purchases from SEC Form 3/4/5 bulk data 2006–present, priced with FirstRate Data histories that include companies later delisted, filtered to opportunistic buys via Cohen–Malloy–Pomorski (a purchase is "routine", and excluded, when the insider bought in the same calendar month in each of the prior 3 years). One event per company per month; price at least $3 and $1M median daily dollar volume. Industry = the SIC code on the company's latest SEC filing before entry. Entry at the open of the second session after the Form 4 was actually filed — not after the trade date; the real filing lag runs 0–7+ days, and assuming a fixed 1-day lag would be trading on information the public did not yet have in ~40% of cases. Horizon 63 trading days. Excess vs IWM (and vs SPY, shown below). t-statistics are clustered by company — one firm's 400 filings count as one observation, not 400 — because overlapping windows on the same stock are not independent; treat |t| ≥ 2 as significant.
Periodvs S&P 500vs small-caps% that beat the indexper-company meant (clustered)n
Late credit boom -1.54% -0.05% 48% +0.86% 1.7 2,263
Global financial crisis +3.71% +2.60% 52% +3.36% 5.4 3,821
Post-crisis recovery +3.19% +1.24% 48% +2.36% 3.7 3,093
Euro crisis & US downgrade -2.00% -0.12% 52% -0.22% -0.3 1,049
Mid-cycle bull +0.17% -0.07% 49% +0.34% 1.0 5,850
Oil bust & industrial recession -3.28% -0.10% 53% +0.27% 0.5 1,543
Late-cycle bull -0.26% +0.38% 48% +0.73% 2.0 6,990
COVID crash +0.84% +0.65% 42% +1.10% 0.7 649
Stimulus melt-up +1.53% +0.63% 47% -0.03% 0.0 3,187
Inflation & rate shock -0.91% -1.60% 47% -0.87% -1.3 1,682
AI-led recovery (now) -0.26% +0.41% 46% +0.73% 1.4 6,504

Study generated 2026-09-14 from SEC Form 3/4/5 data and FirstRate Data prices (delisted stocks included) · this same table drives the ranking of the live signals feed, so the two can never disagree. Educational, not investment advice. Disclosures.