Lance Roberts engagement report
@LanceRoberts - 106K followers on X
Measured over 48 original posts from a 30-day window, last computed on October 13, 2026.
Engagement
A typical post picks up 21 interactions against 106K followers, an engagement rate of 0.02%. Measured over 48 original posts, its engagement rate beats 26% of 21,185 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 3.6K times each, and 0.579% of those impressions turn into an interaction. That is about 3.43% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.9 posts a day over the last 30 days, though only 20% of days saw any activity at all. Most posts go out around 10:00 UTC, and Thursday is the busiest day of the week. Of the 48 posts sampled, 88% carry an image or video, 8% are part of a thread and 29% link out. The account's strongest tracked post pulled 128 interactions, about 6.1x its own typical post. Recurring topics include #therealinvestmentshow, #dailymarketcommentary.
Measured over 48 original posts from a 30-day window, last computed on October 13, 2026. Recurring tags: #therealinvestmentshow, #dailymarketcommentary.
Compared with accounts its own size
Lance Roberts's engagement rate beats 26% of the tracked X accounts closest to it in follower count (21,185 accounts, accounts of similar size (decile 7 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 27% 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 0.02%, Lance Roberts sits above the 10th percentile of the 212,805 accounts in this comparison. That places it in the bottom 25% band, which runs below 0.025%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.004% |
| 25th percentile | 0.025% |
| 50th percentile | 0.146% |
| 75th percentile | 0.697% |
| 90th percentile | 2.61% |
| 99th percentile | 83.1% |
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 10:00 UTC, and Thursday 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.
Show engagement by hour posted, utc as a table
| Hour (UTC) | Vs author median | Posts |
|---|---|---|
| 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 UTC | 0% | 116K |
| 22:00 UTC | -2% | 100K |
| 23:00 UTC | -1% | 90K |
Show engagement by day of week as a table
| Day | Vs author median | Posts |
|---|---|---|
| Sunday | +5% | 393K |
| Monday | +1% | 483K |
| Tuesday | -2% | 520K |
| Wednesday | -3% | 472K |
| Thursday | -2% | 430K |
| Friday | -3% | 447K |
| Saturday | +2% | 393K |
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.
| Format | This account | Catalog effect | 95% interval | Accounts behind it |
|---|---|---|---|---|
| Image or video | 88% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 29% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | +15% | +14% to +16% | 32K |
- 88% 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.
- 29% of its posts carry a link off X. Across the catalog, posts with an outbound link run 41% below the same accounts' other posts.
- Its average post runs 401 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
- Oct 12, 20266.1x their median
Another nail in the coffin of the "Financial Nihilism" crowd. "Across wealthy countries, millennials have higher inflation-adjusted incomes than previous generations did at comparable ages." -@TheEconomist @adamtaggart https://t.co/fhcU9lojmL
- Oct 12, 20264.7x their median
For all you valuation bugs. "The S&P 500 is statistically expensive on 17 of 20 metrics. September marks the 5th consecutive month the index is expensive on 17/20." - h/t @BlakeMillardCFA https://t.co/vPMnENi0qZ
- Oct 9, 20263.9x their median
Despite the S&P 500 hitting an all-time high this past week, investors remain negative on the market going into earnings season, which could well be a contrarian setup. h/t @ISABELNET_SA https://t.co/IqJHGCDFTD
- Oct 9, 20263.8x their median
The current bull market that started in October 2022, is now 4 years old. Of the six previous bull markets that lasted at least four years, five gained further ground in their fifth year, with an average fifth-year return of 12%. h/t @SoberLook @Truist https://t.co/tnC5CKZRtA
- Oct 12, 20263.7x their median
41 AI related companies in the S&P 500 index now make up roughly 49% of total market cap, exceeding every previous concentration cycle except for railroads. h/t @charliebilello https://t.co/6ZyQ8vc8nj
- Oct 12, 20263.0x their median
Lot's of comments over the weekend about the "AI bubble" and that it will burst in the next few months. Is AI a "bubble?" Maybe. But predicting when bubbles eventually burst has historically been very difficult to do as bull markets can last a lot longer than you think. Manage your risk, pay attention to trend of the market, and don't over leverage yourself. h/t @ISABELNET_SA @CarsonResearch
- Oct 13, 20262.8x their median
One of the big questions has been why the "normalization" of interest rates has not caused a big market selloff. The reason is that most sectors have seen sales growth exceed the cost of capital, suggesting muted sensitivity to higher interest rates. Furthermore, businesses also report that financing availability and costs have not materially constrained their investment plans.
- Oct 12, 20262.2x their median
10-12-26 The Housing Shortage Is A Bubble — And It Could Burst Soon In this Short video from the interview with @BillKingHouston, we discuss why America's housing shortage may actually be a temporary bubble that's about to burst — and how demographic shifts could trigger a major housing correction while creating powerful long-term deflationary pressures across the economy. Housing affordability has become a major challenge, particularly for younger Americans trying to purchase their first homes. But Bill argues that the current shortage may disappear much faster than most people expect. One major reason is the Baby Boomer generation. Americans are living longer and staying in their homes well into their 80s and 90s, delaying the transfer of existing housing supply to younger generations. As this demographic eventually releases more properties into the market, the supply-demand imbalance could shift dramatically. Meanwhile, residential construction has accelerated following years of underbuilding after the previous housing crash. Combined with slowing population growth, this could eventually transform today's housing shortage into an oversupply problem. Bill believes housing prices may have already peaked and could begin declining relatively quickly. There are also early warning signs in the rental market. In Houston, Bill estimates that approximately 80,000–100,000 apartments are sitting vacant, while occupancy rates have fallen significantly. Rents in lower-end apartment properties have already declined substantially over the past couple of years. Interestingly, private rental indicators from Zillow and Redfin are showing weakness that has yet to fully appear in official inflation statistics. Owners' Equivalent Rent, a major component of CPI, remains elevated despite weakening market rents. This suggests that significant housing disinflation may already be underway but hasn't fully filtered into the government's inflation calculations. The implications extend far beyond real estate. Bill argues that demographic decline is inherently deflationary over the long term. Fewer people ultimately mean less demand for housing, automobiles, groceries, and other consumer goods. That could create sustained downward pressure on prices and potentially help the Federal Reserve bring inflation closer to its 2% target. The bigger question is what happens when the housing market shifts from too few homes to too few buyers? Please ❤️like, bookmark🔖, and 🔁share with fellow investors.
- Oct 13, 20262.1x their median
Since 1974, every S&P 500 bull market that reached its fourth anniversary has gone on to complete a fifth year, with the four most recent cases delivering double-digit gains without a correction exceeding 10%. @SoberLook @Bluekurtic https://t.co/01v39f9TdL
- Oct 8, 20261.9x their median
10-8-26 The Term Premium Dilemma: A Growing Risk Of Fed Policy Error @michaellebowitz and I discuss why Treasury yields cannot simply keep rising indefinitely without fundamental support—and why the Federal Reserve's reliance on the elusive "term premium" could set the stage for another major policy mistake. Unlike stocks, where sentiment and speculation often dominate short-term price movements, the bond market is primarily driven by fundamentals. Treasury yields reflect inflation expectations, real interest rates, economic growth, monetary policy expectations, and compensation for future uncertainty. When I constructed MIchael's analysis, the 10-year Treasury yield stood at 5.26%. I broke it down into three major components: 2.3% breakeven inflation, reflecting inflation expectations, Fed credibility, energy prices, and wages. 1.9% real interest rate, tied to economic growth, productivity, and monetary policy expectations. Approximately 1% term premium, representing additional compensation investors demand for holding longer-term bonds. The key point? Term premium is only one component of Treasury yields, and its influence is constrained by underlying fundamentals and market supply and demand. But here's the problem: nobody actually knows precisely how large the term premium is. Different Wall Street and Federal Reserve models produce estimates ranging from 61 to 140 basis points. I estimate roughly 100 basis points, while Michael's model suggests just 77. That's a substantial difference for a variable increasingly used to interpret financial conditions and guide monetary policy. Michael specifically questions Dallas Fed President Lorie Logan's reliance on the term premium as part of the rationale for interest-rate decisions. His concern is that policymakers are treating an inherently uncertain model estimate as a reliable signal. If the Fed underestimates how restrictive higher long-term yields have already become, it could tighten too aggressively, unnecessarily weakening economic growth and increasing recession risks. Conversely, if policymakers mistakenly conclude that rising yields have already tightened financial conditions sufficiently, they could hold back on necessary rate hikes and allow inflation to persist. Either way, the Fed risks making decisions based on a number that cannot be directly observed and that even sophisticated models cannot agree upon. The real danger isn't simply that Treasury yields could rise further. It's that the Fed may misunderstand WHY they're rising—and make a costly policy mistake as a result. Please ❤️like, bookmark🔖, and 🔁share with fellow investors.
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.
Recurring topics
The most frequent hashtags in the sampled posts. They describe what this account writes about; they are not a performance signal, and the catalog-wide breakdown on the hub shows how little hashtag count moves.
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Reading these numbers
A typical post picks up 21 interactions against 106K followers, an engagement rate of 0.02%. Measured over 48 original posts, its engagement rate beats 26% of 21,185 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 3.6K times each, and 0.579% of those impressions turn into an interaction. That is about 3.43% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.9 posts a day over the last 30 days, though only 20% of days saw any activity at all. Most posts go out around 10:00 UTC, and Thursday is the busiest day of the week. Of the 48 posts sampled, 88% carry an image or video, 8% are part of a thread and 29% link out. The account's strongest tracked post pulled 128 interactions, about 6.1x its own typical post. Recurring topics include #therealinvestmentshow, #dailymarketcommentary.
- What is Lance Roberts's engagement rate on X?
- Lance Roberts (@LanceRoberts) has an engagement rate of 0.02%, based on the median interactions across 48 original posts from the last 30 days against 105,805 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.02%, Lance Roberts sits above the 10th percentile of the 212,805 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 @LanceRoberts have real engagement?
- Its engagement rate beats 26% of the tracked X accounts closest to it in follower count (21,185 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 @LanceRoberts post?
- Most posts go out around 10:00 UTC, and Thursday is its busiest day, at roughly 1.9 posts per day across the measured window.