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Mark Minervini engagement report

@markminervini - 767K followers on X

Measured over 36 original posts from a 30-day window, last computed on September 29, 2026.

Engagement

Middle of its size range
Per follower
0.073%
of 767K followers
Per impression
0.571%
98K views on a typical post
Reach
12.8%
of its followers see a post
Typical post
558
interactions (median)
Saved
0.097%
95 bookmarks on a typical post
Posting rate
2.77/day
active 77% of days
Peak time
14:00 UTC
Tuesday

A typical post picks up 558 interactions against 767K followers, an engagement rate of 0.073%. Measured over 36 original posts, its engagement rate beats 66% of 20,444 tracked accounts of a similar size, which puts it in the middle of its size range rather than at either end. Posts are seen about 98K times each, and 0.571% of those impressions turn into an interaction. That is about 12.7% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 2.8 posts a day over the last 30 days, with activity on roughly 77% of days. Most posts go out around 14:00 UTC, and Tuesday is the busiest day of the week. Of the 36 posts sampled, 50% carry an image or video, 6% are part of a thread and 47% link out. The account's strongest tracked post pulled 6.5K interactions, about 12x its own typical post.

Measured over 36 original posts from a 30-day window, last computed on September 29, 2026.

Compared with accounts its own size

Mark Minervini's engagement rate beats 66% of the tracked X accounts closest to it in follower count (20,444 accounts, accounts of similar size (decile 10 of 10)). A percentile is spread evenly by construction, so 50 really is the middle of that group and 90 really is its top tenth.

On engagement per impression rather than per follower it beats 34% of the same group. When those two numbers disagree, the gap is about how far its posts travel rather than how people react to them.

Where this sits in the catalog

At 0.073%, Mark Minervini sits above the 25th percentile of the 204,694 accounts in this comparison. That places it in the below the median band, which runs 0.024% to 0.143%.

p100.004%
p250.024%
p50 (median)0.143%
p750.677%
p902.55%
p9982.4%
Engagement rate as a share of followers, across the 204,694 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 22,880 times apart and a linear axis would flatten everything below the median into a single point.
Show the percentile table
Engagement rate percentiles
PercentileEngagement rate
10th percentile0.004%
25th percentile0.024%
50th percentile0.143%
75th percentile0.677%
90th percentile2.55%
99th percentile82.4%

This ruler is the whole measured catalog, not a size-matched group: it shows where the raw rate falls across every account we can measure, all of which are large. For a like-for-like comparison, read the size-band percentile above instead. See how the bands are built

Posting timing

This account posts most often around 14:00 UTC, and Tuesday is its busiest day of the week. The bars below are the catalog-wide pattern, with this account's own busiest slot marked. They do not show how this account performs at each hour: we keep one aggregate per account, not one per hour, so that measurement does not exist in our data.

Engagement by hour posted, UTCTwenty-four bars, one per UTC hour. Each bar shows how posts published in that hour compare with their own authors' median engagement. Bars above the centre line ran higher than the median, bars below ran lower. A marker flags Busiest hour: 14:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 111%Busiest hour: 14:00 UTC
Show engagement by hour posted, utc as a table
Engagement by hour posted, UTC
Hour (UTC)Vs author medianPosts
00:00 UTC-1%89K
01:00 UTC-2%90K
02:00 UTC-3%88K
03:00 UTC-4%94K
04:00 UTC-5%76K
05:00 UTC-4%75K
06:00 UTC-5%86K
07:00 UTC-5%93K
08:00 UTC-4%108K
09:00 UTC-4%124K
10:00 UTC-3%129K
11:00 UTC-3%141K
12:00 UTC-3%154K
13:00 UTC-3%167K
14:00 UTC-4%173K
15:00 UTC-2%176K
16:00 UTC-3%171K
17:00 UTC-3%159K
18:00 UTC-2%149K
19:00 UTC-2%141K
20:00 UTC-1%131K
21:00 UTC0%116K
22:00 UTC-2%100K
23:00 UTC-1%90K
Engagement by day of weekSeven bars, one per weekday, Sunday first. Each bar shows how posts published on that day compare with their own authors' median engagement. Bars above the centre line ran higher than the median, bars below ran lower. A marker flags Busiest day: Tuesday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 111%Busiest day: Tuesday
Show engagement by day of week as a table
Engagement by day of week
DayVs author medianPosts
Sunday+5%393K
Monday+1%483K
Tuesday-2%520K
Wednesday-3%472K
Thursday-2%430K
Friday-3%447K
Saturday+2%393K
See what moves engagement across the whole catalogWhat counts as a good engagement rate at this size

Formats this account uses

Its own posting mix on the left, and what each of those formats does across every account we track on the right. Only formats where the effect clears our publish test appear here, so an empty row is a format we could not measure rather than one that does nothing.

This account's posting mix compared with catalog-wide effects
FormatThis accountCatalog effect95% intervalAccounts behind it
Image or video50% of posts+111%+108% to +115%34K
Outbound link47% of posts-41%-42% to -40%32K
Typical length-+15%+14% to +16%32K
  • 50% of this account's sampled posts carry an image or video. Across the catalog, posts with an image or video run 111% above the same accounts' other posts.
  • 47% of its posts carry a link off X. Across the catalog, posts with an outbound link run 41% below the same accounts' other posts, so a large share of this account's output sits in the weakest bucket we measure.
  • Its average post runs 705 characters, which falls in the over 280 characters band. Across the catalog, posts over 280 characters run 15% above the same accounts' other posts.

These are catalog-wide differences applied to this account's own posting mix, not a measurement of how each format performs for this account specifically. We keep one median per account, not one per format per account, so the second thing is not something this data can tell you.

Best tweets

  • Sep 1, 202612x their median

    I've been a stock trader for 43 years. Based on my experience, the market will never outsmart me and take my capital during bear markets or sky rocket without me onbosrd for the ride during bull markets. That sounds very arrogant, doesn't it. But wait until you hear the reason why. Because I never try to outsmart the market. What i have learned is humility. The market is always right. And if I am yielding to its message, I can never be outsmarted by the very force I am respecting and staying in gear with. There's a fortune in this one paragraph.

    5.9K46515742547K viewsView on X
  • Sep 21, 20267.1x their median

    I’ve had this on the wall in my office for almost 20 years, and I still read it every morning https://t.co/lgBA5pIzoo

    3.5K3676623203K viewsView on X
  • Sep 1, 20266.4x their median

    If you want to succeed in life, you need to learn to think and act independently of the good opinion of others. No one cares about your future as much as you do. No one is coming to make you successful. No one is going to make you rich. That’s your responsibility. You have to make decisions based on your own passions, your own dreams, your own goals, and your own tolerance for risk—not based on what someone else thinks you should do. And yes, that includes your parents, your kids, your spouse, your friends—and society. Listen to advice. Consider opinions. Learn from people you respect. But ultimately, you have to live your life—not the life other people have chosen for you. If you want uncommon results, you have to be willing to make decisions that other people may not understand, approve of, or agree with. Your life. Your decisions. Your consequences. Your future.

    3.0K4376130163K viewsView on X
  • Sep 3, 20265.8x their median

    I have two major trading rules: 1. No forced trades. 2. No big losses.

    2.9K2246514152K viewsView on X
  • Sep 25, 20265.5x their median

    If AI can trade stocks so well, why are all these AI-managed portfolios at Fidelity, Schwab and elsewhere struggling to even beat the S&P 500? And where are the AI portfolios winning the U.S. Investing Championship? Backtests and predictions are easy. Show me the audited, real-money results. That’s where the bullshit stops. The answer is because it can't. There is zero evidence of any enduring or consistent results from purely AI or computer manager portfolios that can even outperform the S&P 500. Fact.

    2.6K21618549387K viewsView on X
  • Oct 14, 20204.3x their median

    The 5 biggest mistakes I made when I first started trading https://t.co/scg1vLp2WJ

    1.9K4214038View on X
  • Jan 19, 20234.1x their median

    Quote of the day... https://t.co/Y8pmyAyuUm

    1.9K3323322284K viewsView on X
  • Aug 27, 20264.0x their median

    Quote of the Day In trading, closing many trades that would have gone higher if you had held is a necessary part of succeeding. When you reach a crossroads and have to decide whether to hold or fold, amateurs tend to roll the dice and hold. Pros usually play it safe and fold. — Mark Minervini

    2.0K1685231189K viewsView on X
  • Aug 19, 20263.5x their median

    The hard rotation in technology is wreaking havoc on many recent breakout names. A number of former leaders that suffered significant declines rallied quickly back up their right sides, but that rapid recovery created another problem: technical time compression combined with substantial overhead supply. When a stock suffers a large decline and then races back up in a quick V recovery, it may look strong on the surface, but the structure underneath can still be vulnerable to sharp volatility. There simply hasn't been enough time for the stock to properly repair the technical damage, shake out weak holders, and work through the supply created during the prior decline. We're seeing the consequences of that now as some of these stocks experience sharp pullbacks. The question is what happens next. Do these former leaders find support, tighten up and begin constructing legitimate right sides to their bases? Or is the current weakness the beginning of another leg lower and a continuation of the correction? At this stage, there is no reason to guess. The best course of action is to avoid questionable structures that haven't had sufficient time to develop proper pivots. A stock moving rapidly back toward its highs does not automatically mean it has built a sound base or offers a low-risk entry. Particular caution should be exercised with stocks that have suffered declines of 45% or greater in a relatively short period and then rallied rapidly back into overhead supply. These situations can produce powerful rebounds, but they can also create significant volatility as trapped shareholders use the strength to get out near breakeven. Let the stocks prove themselves. The strongest names will absorb the supply, hold important support levels, tighten their price action and eventually present properly developed setups. If they can't do that, there is no reason to force the trade and play right into the hands of volatility. Time is an important ingredient in technical repair. Don't confuse a fast recovery with a completed base, and don't confuse volatility with alpha. https://t.co/FfBnR93ojq https://t.co/TFyCpPHZis https://t.co/JXzFFTmMtn

    1.7K1866621320K viewsView on X
  • Sep 3, 20263.5x their median

    When the best setups don't work, you don't go to the worst setups... you go to cash.

    1.8K115015103K viewsView on X

Ranked by total interactions across everything we have tracked for this account, which is a longer history than the 30-day window the rates above use. The multiple compares each post to this account's own median.

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Reading these numbers

A typical post picks up 558 interactions against 767K followers, an engagement rate of 0.073%. Measured over 36 original posts, its engagement rate beats 66% of 20,444 tracked accounts of a similar size, which puts it in the middle of its size range rather than at either end. Posts are seen about 98K times each, and 0.571% of those impressions turn into an interaction. That is about 12.7% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 2.8 posts a day over the last 30 days, with activity on roughly 77% of days. Most posts go out around 14:00 UTC, and Tuesday is the busiest day of the week. Of the 36 posts sampled, 50% carry an image or video, 6% are part of a thread and 47% link out. The account's strongest tracked post pulled 6.5K interactions, about 12x its own typical post.

What is Mark Minervini's engagement rate on X?
Mark Minervini (@markminervini) has an engagement rate of 0.073%, based on the median interactions across 36 original posts from the last 30 days against 767,193 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.073%, Mark Minervini sits above the 25th percentile of the 204,694 accounts in this comparison. Those comparison accounts are all large ones, because our scanning cadence is weighted towards big accounts, so this is a ranking among peers of similar scale rather than a ranking across X.
Does @markminervini have real engagement?
Its engagement rate beats 66% of the tracked X accounts closest to it in follower count (20,444 accounts), which puts it in the middle of its size range group. Ranking inside a size band matters because engagement rate falls as accounts grow, so a raw rate would mostly re-measure the follower count. It is a starting point for a look at follower quality, not a verdict on it.
When does @markminervini post?
Most posts go out around 14:00 UTC, and Tuesday is its busiest day, at roughly 2.77 posts per day across the measured window.

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