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As BTC-TCs, both @Strategy | @Strive rely on robust capital markets access to scale the Treasury Model.
Through Digital Credit, they’ve opened additional capital-raising channels and, in my view, created a new asset class. The resulting preferred securities now trade as their own cohort | block in a secondary market, adjacent to $BTC and their “parent equities”, not separate from them.
My research at True North examines $STRC through that lens: buybacks, market structure, and the transmission channels connecting the offering to the wider complex.
This connection shows up in the data - the following results are from a broader analysis of all five preferred offerings: $STRK | $STRF | $STRD | $STRC | $SATA - using their price histories since inception and rolling attribution models built on matched trading sessions.
The results below are from a 9-4-26 snapshot of that larger analysis: a 60-session window spanning 6-11-26 through 9-4-26, covering the selloff, the pre-buyback rebound, and the buyback execution period.
Within that window, a model built on orthogonal (uncorrelated) factors explained 74.65% of daily price return variance in $STRC. The three largest allocations, expressed as shares of that explained variance, were:
a] Other (Non-STRC) Preferreds: ~44.7%
b] MSTR (ex-BTC): ~39.2%
c] BTC: ~15.7%
Read the full analysis here: tnorth.com/research/strc-…
Through Digital Credit, they’ve opened additional capital-raising channels and, in my view, created a new asset class. The resulting preferred securities now trade as their own cohort | block in a secondary market, adjacent to $BTC and their “parent equities”, not separate from them.
My research at True North examines $STRC through that lens: buybacks, market structure, and the transmission channels connecting the offering to the wider complex.
This connection shows up in the data - the following results are from a broader analysis of all five preferred offerings: $STRK | $STRF | $STRD | $STRC | $SATA - using their price histories since inception and rolling attribution models built on matched trading sessions.
The results below are from a 9-4-26 snapshot of that larger analysis: a 60-session window spanning 6-11-26 through 9-4-26, covering the selloff, the pre-buyback rebound, and the buyback execution period.
Within that window, a model built on orthogonal (uncorrelated) factors explained 74.65% of daily price return variance in $STRC. The three largest allocations, expressed as shares of that explained variance, were:
a] Other (Non-STRC) Preferreds: ~44.7%
b] MSTR (ex-BTC): ~39.2%
c] BTC: ~15.7%
Read the full analysis here: tnorth.com/research/strc-…
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My comments around ATM issuance on last night's (awesome) @TNorth episode seem to have a few people in a tizzy.
The simple data and evidence backed point is this:
When it comes to $MSTR | $ASST, based on how shares have been issued, the ATM is noise within the tape and isn't a long or short term driver of price.
The simple data and evidence backed point is this:
When it comes to $MSTR | $ASST, based on how shares have been issued, the ATM is noise within the tape and isn't a long or short term driver of price.
@BritishHodlh@TheRealDHRhat my latest v20 models explain 72.8% to 85.2% of variance. Secondly, I find it interesting that (the A.I.) concedes the short term variance results (using outdated 63% R2 stats) and then pivots to an unproven "longer term structural effect” that depends on BPS or CEBE being the factors that set value or the multiple.
However, there are a lot of flaws there, specifically around the claim that dilution effects reducing BTC per share (or CEBE) lowers the mNAV or the price for any given total NAV, even if it doesn’t show up in the regression. Also, declines in BPS and mNAV “compression” are used as evidence of a structural effect that my variance work can't account for.
Ironically, BPS has been one of the most consistently modeled factors in my work and I think the A.I. is assuming that BPS | CEBE are valid metrics for what the market is pricing; or for the “residual claim” the market is valuing, but they aren't.
After today's latest run (with a fresh as of 10-30 date), when assessing BPS growth as a factor across all models from 2021 to 2026, its price variance contribution is just 0.04% to 0.33%.
Getting more specific, in my full Capital Structure model (which explains 85.2% of price variance), the variance contribution from BTC Per Share is 0.04% (+R2=0.000) and it is statistically insignificant (t=-0.948,p=0.3438 ), just as the ATM itself is statistically insignificant (t=0.961,p=0.3375 ) with a 0.67% attribution.
Even in the broader 2021–2026 models where BPS shows significance, the t-stat is negative (t=-5.73 to -7.01) which in plain terms means that generally, as BTC Per Share went up, share price went down. I think that is a rather concrete answer about whether or not the KPI shows up as some missing long-horizon driver of price.
@Strategy itself has defined BTC Yield as a narrow KPI for per share accretion on $BTC holdings and has repeatedly stated that it isn't a measure of valuation, financial performance, or returns.
Specifically, Strategy’s own Q3 2026 financial release (filed October 29, 2026) explicitly states in its KPI disclosures that BPS (in Sats) "does not represent (i) the Company's ability to satisfy its financial obligations, or (ii) the Company's book value per share" and that BTC Yield "is not a measure of the return on investment the Company's shareholders may have achieved historically or can achieve in the future by purchasing stock of the Company".
BTC Per Share is essentially an accounting reality that doesn’t represent a redeemable claim nor a redeemable residual after senior claims.
If we move onto CEBE; this is an attempt to net out senior claims, but it serves as just another formulation of the same accounting residual and is not what the market is forward pricing. Based on years of analysis what I see tells me that the market is pricing the BTC capital base, the optionality within the equity, the adversarial positioning around the equity and the sentiment | positioning around the resulting structure (mNAV). With mNAV acting as a multiple that is assigned independently of the current BPS | CEBE reality. I think this is somewhat evidenced by persistent rises in BTC Per Share (for many BTC-TC’s) while share price fell.
Now the question that I have is this: If the company that created the metric, defined the metric, and was the first to consistently report the metric, is saying that it's not a measure of valuation or related to stock price performance; perhaps there is a reason for that. No? At the same time @saylor himself has described mNAV expansion as driven by market sentiment | confidence, with BTC Yield and BPS rising as a result of that sentiment rather than being its cause. The data, the results of my modeling, and the official corporate framing are well aligned.
Coming back to the analysis that I have done in more detail, the modeling isn't a simple “correlation” analysis and it isn't missing a slow structural effect that is captured in BPS | CEBE or dilution effects .
Rather, using orthogonalized factors, Newey-West HAC standard errors, rolling 90D | 180D Shapley windows, and BVAR sign restrictions, its showing that the factors that actually move price variance are overwhelmingly $BTC direction (accounting for 41.2% – 51.2%), followed by options positioning (GEX, DEX, Max Pain Distance, PCR), shorting pressure and related positioning, volatility (VIX and MSTR IV), volume (Turnover vs. ADV), capital rotation ($BTC Miners, Spot ETFs, and Mag 7), and the preferred capital structure ($STRK, $STRF, $STRD, and $STRC).
The ATM is simply noise inside that process (0.24% to 0.67% of variance, even when tested across 5d, 10d, and 20d rolling sums) and that is consistent over days, weeks, months, and now years.
In the face of all of that, to treat a change in an internal KPI as the missing long horizon driver we would also have to use the same investment framing and metric that the company itself already excludes as valuation, and the market pricing process doesn’t reinforce.
By the way, I should note that the money printing comparison is a common one that doesn't really fit or apply here. Money printing expands the supply of the unit of account against a relatively fixed base. The ATM is issued against available liquidity that is then used to acquire more of an underlying asset; which isn’t really an expansion of the monetary base. Yes, the ownership percentage of an existing share falls, but the economics of that share depend on what the company receives and does with the proceeds. But I think this is making the same assumption that the share count is the scarce unit and that the market capitalizes a per share claim, but there is no evidence of that in the observed data or price trends.
Finally, yes, an artificial buyer or seller can move the price, that is obviously true for individual trades, and my work never denied that. What I tested was how much issuance (and also buybacks) explain price variance over various time frames once I account for $BTC and include other factors. What I found was that “other factors” overwhelmingly dominate. So claiming otherwise is arguing against a claim I didn't make.
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@TNorthtcheB@VatcheBalayananother point on the “larger float dampening convexity” claim:
I went back to my ouputs, in my model that covers the 8-2025 to 10-2026 window, (when the share float was at its largest) the $BTC onl$BTClope” in the results was actually higher (~1.51 vs. ~1.27 in the full 2021–2026 sample), meaning $MSTR moved more per unit of $BTC return, not less.
At the same time and in that same window, $MSTR IV changes [8.11%], market cap scaled GEX {Gamma Exposure} [4.96%], and distance to Max Pain [4.84%] accounted for nearly 18 points of fitted R2 inside a model that explains ~85.2% of total variance.
If the claim is that a larger float structurally took away upside convexity, the data actually shows the exact opposite: both directional $BTC sensitivity and the market cap scaled options | volatility mechanics that drive convexity were stronger during a period with the highest share float.
Anyone claiming the float muted the upside needs to show how they separated that from changes in the $BTC regime and options positioning.
I went back to my ouputs, in my model that covers the 8-2025 to 10-2026 window, (when the share float was at its largest) the $BTC onl$BTClope” in the results was actually higher (~1.51 vs. ~1.27 in the full 2021–2026 sample), meaning $MSTR moved more per unit of $BTC return, not less.
At the same time and in that same window, $MSTR IV changes [8.11%], market cap scaled GEX {Gamma Exposure} [4.96%], and distance to Max Pain [4.84%] accounted for nearly 18 points of fitted R2 inside a model that explains ~85.2% of total variance.
If the claim is that a larger float structurally took away upside convexity, the data actually shows the exact opposite: both directional $BTC sensitivity and the market cap scaled options | volatility mechanics that drive convexity were stronger during a period with the highest share float.
Anyone claiming the float muted the upside needs to show how they separated that from changes in the $BTC regime and options positioning.
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@saylor @phonglee@TNorthanswer, the coupon on a preferred is how the market is compensated for the risks associated with the offering.
The rate is set (or adjusted) so that the pref can clear at or near par given the residual risk investors are asked to take on. For Digital Credit that can be the issuer credit, potential dividend deferral, residual claim priority, but most directly {a} $BTC risk, {b} Parent Equity Risk ($ASST | $MSTR) and the risks associated with {c} Digital Credit as an asset class.
The cash | coverage numbers don't set the price, they are balance sheet details that (based on the data) marginally affect the assessment of those residual risks. The price and price level is the market’s view of whether or not the coupon adequately compensates for the risk, thus what the market is pricing are a, b and c from above.
The simplified answer is that if the market thinks the risk is higher than the coupon, the pref trades below par; if the market thinks that the coupon is too low for the risk, the pref trades higher.
Coverage and cash are inputs into that risk assessment but they don’t mechanically set the price or the level. I was recently on a pod with @chasepalmieri where we went into the details on how this plays out in $STRC.
x.com/basedlayer/sta…
The rate is set (or adjusted) so that the pref can clear at or near par given the residual risk investors are asked to take on. For Digital Credit that can be the issuer credit, potential dividend deferral, residual claim priority, but most directly {a} $BTC risk, {b} Parent Equity Risk ($ASST | $MSTR) and the risks associated with {c} Digital Credit as an asset class.
The cash | coverage numbers don't set the price, they are balance sheet details that (based on the data) marginally affect the assessment of those residual risks. The price and price level is the market’s view of whether or not the coupon adequately compensates for the risk, thus what the market is pricing are a, b and c from above.
The simplified answer is that if the market thinks the risk is higher than the coupon, the pref trades below par; if the market thinks that the coupon is too low for the risk, the pref trades higher.
Coverage and cash are inputs into that risk assessment but they don’t mechanically set the price or the level. I was recently on a pod with @chasepalmieri where we went into the details on how this plays out in $STRC.
x.com/basedlayer/sta…
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Back on @TNorth Episode 85:
True North Ep. 85: Let Us In, Wall Street
Featuring @PunterJeff, @AdamBLiv, @_Adrian and @nithusezni.
Timestamps:
00:00 - True North Loading...
01:30 - Midterms And The Money Printer
10:02 - Balance Sheet Overview
15:32 - The ATM Narrative
28:17 - $BTC And The S&P 500
48:34 - What5:30 - Rating Digital Credit $STRC $SATA
01:06:30 - Hard Fork Coins On Balance Sheet
01:16:53 - Final Thoughts
$MSTR $ASST $STRC $SATA $SATS
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Remember the $STRC "Death Spiral" in June?
I now expect that people will get just as loud screaming "we're so back" ¯\_(ツ)_/¯
I now expect that people will get just as loud screaming "we're so back" ¯\_(ツ)_/¯
JUST IN: @TNorth's @_Adrian Morris just called out the $STRC whiplash. "3 weeks ago everyone couldn't stop talking about Stretch. People need to relax."
@PunterJeff Walton quips "it's a death spiral w/ a 10% leverage ratio & $54 billion of capital."
The math hasn't changed.🔥
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$BTC: Whether Red | Blue everyone can appreciate the Orange
Florida elected a Republican governor who backed a U.S. Bitcoin reserve. Texas elected a Democratic senator who voted to create one for his state. The case for holding Bitcoin crosses party lines.
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Time, and a shift in the markets risk perception of $BTC will be the most important factors in the long term success of $STRC, $SATA and Digital Credit:
For Digital Credit, the biggest stabilizer may be time.
Adrian Morris (@_Adrian) explains how Bitcoin $BTC capital could expand the market.
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Could a $MSTR common stock buyback be "accretive" on a BTC Per Share or Yield basis? Sure.
1] Does that really matter?
2] That has almost nothing to do with how the market is pricing the equity.
3] The shares will be issued again at some point, why would the market reward that with a higher price?
1] Does that really matter?
2] That has almost nothing to do with how the market is pricing the equity.
3] The shares will be issued again at some point, why would the market reward that with a higher price?
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The BTC-TC model depends on 1] Capital markets access and 2] Share issuance.
When a company does (or considers) share buybacks whether on the common stock ($MSTR | $MTPLF) and | or the preferred equities ($STRC | $SATA): They are signaling weakenss to the market.
When a company does (or considers) share buybacks whether on the common stock ($MSTR | $MTPLF) and | or the preferred equities ($STRC | $SATA): They are signaling weakenss to the market.
"The entire model is share issuance. When you're buying back shares, whether on the common or preferred, you're running the model in reverse. And that is an undeniable signal to the market of weakness."
-@_Adrian of @TNorth on this week's RE:Bitcoin
🎥 Watch on Youtube: youtu.be/jI7M2iUQViw
@Strategy $MSTR $STRC
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$MSTR: ATM Share Issuance | BTC Per Share - Which is driving price...?
What MSTR Bulls Get Wrong 🥶
What if @Strategy's biggest levers don't move the needle?
@_Adrian of @TNorth joins me on RE:Bitcoin to challenge four popular $MSTR narratives:
🔸 BTC Per Share doesn't drive stock price
🔸 MSTR ATM issuance doesn't suppress MSTR price
🔸 STRC TRC price
🔸 Dividend rates and daily dividends are noise
Forget the narratives. What does the data actually say?
A must-watch for every MSTR shareholder.
🎥 Watch here: youtu.be/jI7M2iUQViw
$STRC $STRD $STRF $STRK
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Summary of Activities:
$MSTR: 1,178,55 shares sold for $164M
$STRC: 2,092,035 shares purchased for $208.2M
$BTC: 811₿ purchased for $65.5M
Cash Reserve: $98.5M added
$MSTR: 1,178,55 shares sold for $164M
$STRC: 2,092,035 shares purchased for $208.2M
$BTC: 811₿ purchased for $65.5M
Cash Reserve: $98.5M added
Strategy has acquired 811 $BTC and repurchased $208M of $STRC. As of 11/1/26, we hold 849,327 BTC and $4.9B of USD Assets. $MSTR strategy.com/press/strategy…
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The market is both using @Strategy as exit liquidity and testing their resolve through counter-trading $STRC buybacks:
Buying at $99 can give someone else a way out.
Adrian Morris (@_Adrian) argues that Strategy’s $MSTR buybacks invite traders to test the prices it defends, whether $99 or $99.50.
“Every intervention in the market will be countertraded by the market.”
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>claims STRC is in a death spiral
>claims Strategy will be liquidated
>wrong
>tells his base to sell BTC
>BTC rips
>whoops
>claims a CFO resignation is a "red flag"
>100+ public CFOs resign every year
For just $799 a year, you can buy his course and be just as dumb as he is.
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What's ahead during a $BTC Bull Run:
5 Engines for @Strategy -
$MSTR | $STRK | $STRF | $STRD | $STRC
3 Engines for @Strive -
$ASST | $SATA | $SATS
All buying $BTC
5 Engines for @Strategy -
$MSTR | $STRK | $STRF | $STRD | $STRC
3 Engines for @Strive -
$ASST | $SATA | $SATS
All buying $BTC
Five engines for Strategy. Three for Strive.
Adrian Morris (@_Adrian) thinks a $BTC bull market could bring buyers into all three: Bitcoin, equity exposure and digital credit.
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$STRC: The forward-looking valuation and risk assessment of $BTC | $MSTR flows through to Digital Credit.
Here's how I think about it with @IIICapital:
Here's how I think about it with @IIICapital:
If $BTC were at $200K, would Strategy $MSTR need buybacks?
Adrian Morris (@_Adrian) explains why a higher Bitcoin price would change the case for Strategy’s buybacks.
“Stress and risk assessment from Bitcoin and from the capital structure will flow through to Digital Credit.”
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If $BTC is a potential "Lingua Franca" for money, Digital Credit ($STRC | $SATA) essentially acts as a translation layer; turning $BTC into yield.
People still speak French and Spanish even when English is the common language.
Adrian Morris (@_Adrian) thinks Bitcoin could play a similar role for money, with digital credit providing a form of translation.
“I very much view digital credit as a yield curve on top of $BTC.”
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