Crypto 牧星
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Crypto 牧星
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Why did the crypto market rise when the Democrats won the midterm elections?
The first principle of election-driven market moves is that markets never trade the outcome itself, but the difference between the outcome and expectations.
If, before the election, the market had already priced in the worst-case scenario—that a Democratic landslide would mean a sweeping crackdown—then prices would already have come under heavy pressure. Short positions would be crowded, risk exposure reduced, and capital outflows completed.
So when the results come in, if reality is even slightly better than the worst-case scenario—for example, the margin of victory is narrower than expected, the winners strike a moderate tone, or policy priorities lie elsewhere—there is a reason for depressed prices to rebound.
This is the pattern of “the bad news is fully priced in”: the bad news has already driven prices down before it becomes reality, so its arrival actually releases some of the pressure.
Seen through this framework, a【counterintuitive rally】doesn’t even require the industry to gain any tangible benefit. Reality merely needs to be no worse than what has already been priced in.
It’s straightforward to test this explanation: look at price action before the election. If prices were already under significant pressure and short positions were piling up, the post-election rally is likely a rebound driven by the gap between expectations and reality. Its staying power may be limited: once that gap has closed, the rally is over, and the market’s direction is once again left to fundamentals and liquidity.
Why did the crypto market rise when the Democrats won the midterm elections?
The first principle of election-driven market moves is that markets never trade the outcome itself, but the difference between the outcome and expectations.
If, before the election, the market had already priced in the worst-case scenario—that a Democratic landslide would mean a sweeping crackdown—then prices would already have come under heavy pressure. Short positions would be crowded, risk exposure reduced, and capital outflows completed.
So when the results come in, if reality is even slightly better than the worst-case scenario—for example, the margin of victory is narrower than expected, the winners strike a moderate tone, or policy priorities lie elsewhere—there is a reason for depressed prices to rebound.
This is the pattern of “the bad news is fully priced in”: the bad news has already driven prices down before it becomes reality, so its arrival actually releases some of the pressure.
Seen through this framework, a【counterintuitive rally】doesn’t even require the industry to gain any tangible benefit. Reality merely needs to be no worse than what has already been priced in.
It’s straightforward to test this explanation: look at price action before the election. If prices were already under significant pressure and short positions were piling up, the post-election rally is likely a rebound driven by the gap between expectations and reality. Its staying power may be limited: once that gap has closed, the rally is over, and the market’s direction is once again left to fundamentals and liquidity.
The first principle of election-driven market moves is that markets never trade the outcome itself, but the difference between the outcome and expectations.
If, before the election, the market had already priced in the worst-case scenario—that a Democratic landslide would mean a sweeping crackdown—then prices would already have come under heavy pressure. Short positions would be crowded, risk exposure reduced, and capital outflows completed.
So when the results come in, if reality is even slightly better than the worst-case scenario—for example, the margin of victory is narrower than expected, the winners strike a moderate tone, or policy priorities lie elsewhere—there is a reason for depressed prices to rebound.
This is the pattern of “the bad news is fully priced in”: the bad news has already driven prices down before it becomes reality, so its arrival actually releases some of the pressure.
Seen through this framework, a【counterintuitive rally】doesn’t even require the industry to gain any tangible benefit. Reality merely needs to be no worse than what has already been priced in.
It’s straightforward to test this explanation: look at price action before the election. If prices were already under significant pressure and short positions were piling up, the post-election rally is likely a rebound driven by the gap between expectations and reality. Its staying power may be limited: once that gap has closed, the rally is over, and the market’s direction is once again left to fundamentals and liquidity.
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Nick Murray: Mentor to financial advisors, redefining investing as a behavioral issue.
A speaker who has served the financial advisory industry for decades, known for the quote, “The market doesn’t know you own it.”
Nick Murray is a spiritual mentor of sorts to the U.S. financial advisory industry. For decades, he has spoken and written for wealth management professionals, and his books are regarded by advisors as a source of professional philosophy.
His central argument is simple: investment failure is never caused by a lack of market knowledge, but by a loss of behavioral control. So the essence of financial planning isn’t managing assets—it’s managing people’s behavior.
The main factor determining long-term, real-world investment results is not economic or market performance, but investor behavior. Investors are naturally their own worst enemies.
He has a widely repeated quote: “The market doesn’t know you own it. It owes you no emotional returns.”
This perspective takes the case for index investing through regular contributions to a philosophical level: what you need isn’t a smarter strategy, but a structure that doesn’t depend on emotional ups and downs. Index funds combined with automated, mechanical contributions are precisely the market-based form of that structure.
Nick Murray: Mentor to financial advisors, redefining investing as a behavioral issue.
A speaker who has served the financial advisory industry for decades, known for the quote, “The market doesn’t know you own it.”
Nick Murray is a spiritual mentor of sorts to the U.S. financial advisory industry. For decades, he has spoken and written for wealth management professionals, and his books are regarded by advisors as a source of professional philosophy.
His central argument is simple: investment failure is never caused by a lack of market knowledge, but by a loss of behavioral control. So the essence of financial planning isn’t managing assets—it’s managing people’s behavior.
The main factor determining long-term, real-world investment results is not economic or market performance, but investor behavior. Investors are naturally their own worst enemies.
He has a widely repeated quote: “The market doesn’t know you own it. It owes you no emotional returns.”
This perspective takes the case for index investing through regular contributions to a philosophical level: what you need isn’t a smarter strategy, but a structure that doesn’t depend on emotional ups and downs. Index funds combined with automated, mechanical contributions are precisely the market-based form of that structure.
A speaker who has served the financial advisory industry for decades, known for the quote, “The market doesn’t know you own it.”
Nick Murray is a spiritual mentor of sorts to the U.S. financial advisory industry. For decades, he has spoken and written for wealth management professionals, and his books are regarded by advisors as a source of professional philosophy.
His central argument is simple: investment failure is never caused by a lack of market knowledge, but by a loss of behavioral control. So the essence of financial planning isn’t managing assets—it’s managing people’s behavior.
The main factor determining long-term, real-world investment results is not economic or market performance, but investor behavior. Investors are naturally their own worst enemies.
He has a widely repeated quote: “The market doesn’t know you own it. It owes you no emotional returns.”
This perspective takes the case for index investing through regular contributions to a philosophical level: what you need isn’t a smarter strategy, but a structure that doesn’t depend on emotional ups and downs. Index funds combined with automated, mechanical contributions are precisely the market-based form of that structure.
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Bezos’s question: Why doesn’t anyone copy Buffett?
The Amazon founder asked the famous question—and got the whole answer.
Jeff Bezos, founder of Amazon, once asked Buffett a question that became widely known: Your investment approach is so simple—why doesn’t anyone follow it? Buffett’s reply became one of the most famous lines in investment history: Because nobody wants to get rich slowly.
Both men are business geniuses studied by billions, and they agreed that the obstacle wasn’t knowledge but human nature—the simpler the method, the fewer people believe it works.
This anecdote is the most eloquent footnote to long-term investing: the barrier isn’t intelligence, but whether you can accept spending decades doing things in the least glamorous way possible.
The man who asked the question went on to build Amazon; the man who answered had already become a legend. That word they both agreed on—“slow”—is the most valuable consensus on this list.
Bezos’s question: Why doesn’t anyone copy Buffett?
The Amazon founder asked the famous question—and got the whole answer.
Jeff Bezos, founder of Amazon, once asked Buffett a question that became widely known: Your investment approach is so simple—why doesn’t anyone follow it? Buffett’s reply became one of the most famous lines in investment history: Because nobody wants to get rich slowly.
Both men are business geniuses studied by billions, and they agreed that the obstacle wasn’t knowledge but human nature—the simpler the method, the fewer people believe it works.
This anecdote is the most eloquent footnote to long-term investing: the barrier isn’t intelligence, but whether you can accept spending decades doing things in the least glamorous way possible.
The man who asked the question went on to build Amazon; the man who answered had already become a legend. That word they both agreed on—“slow”—is the most valuable consensus on this list.
The Amazon founder asked the famous question—and got the whole answer.
Jeff Bezos, founder of Amazon, once asked Buffett a question that became widely known: Your investment approach is so simple—why doesn’t anyone follow it? Buffett’s reply became one of the most famous lines in investment history: Because nobody wants to get rich slowly.
Both men are business geniuses studied by billions, and they agreed that the obstacle wasn’t knowledge but human nature—the simpler the method, the fewer people believe it works.
This anecdote is the most eloquent footnote to long-term investing: the barrier isn’t intelligence, but whether you can accept spending decades doing things in the least glamorous way possible.
The man who asked the question went on to build Amazon; the man who answered had already become a legend. That word they both agreed on—“slow”—is the most valuable consensus on this list.
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Look closely at the internal structure of several decades of history, and you’ll find that the leading sectors were completely different in each decade: energy drove one, technology another, and consumer spending yet another.
The sectors change, the engines change, but the broad trend of the index rising over the long term has remained constant.
This shows that the historical returns of U.S. stock indexes don’t depend on any one industry being in favor. They rely on a more fundamental mechanism that has repeatedly played out throughout history: “there’s always a new growth engine ready to take over.”
For someone investing regularly, this means the quality of historical returns isn’t tied to a single engine. You’re not betting on which sector will lead in a given decade—you’re betting that the engine-switching process itself will continue.
Looking back, this relay race has never stalled. That’s the strongest sense of security historical data can offer.
Video source: @湾林
$QQQB #纳指 #美股指数
Look closely at the internal structure of several decades of history, and you’ll find that the leading sectors were completely different in each decade: energy drove one, technology another, and consumer spending yet another.
The sectors change, the engines change, but the broad trend of the index rising over the long term has remained constant.
This shows that the historical returns of U.S. stock indexes don’t depend on any one industry being in favor. They rely on a more fundamental mechanism that has repeatedly played out throughout history: “there’s always a new growth engine ready to take over.”
For someone investing regularly, this means the quality of historical returns isn’t tied to a single engine. You’re not betting on which sector will lead in a given decade—you’re betting that the engine-switching process itself will continue.
Looking back, this relay race has never stalled. That’s the strongest sense of security historical data can offer.
Video source: @湾林
$QQQB #纳指 #美股指数
The sectors change, the engines change, but the broad trend of the index rising over the long term has remained constant.
This shows that the historical returns of U.S. stock indexes don’t depend on any one industry being in favor. They rely on a more fundamental mechanism that has repeatedly played out throughout history: “there’s always a new growth engine ready to take over.”
For someone investing regularly, this means the quality of historical returns isn’t tied to a single engine. You’re not betting on which sector will lead in a given decade—you’re betting that the engine-switching process itself will continue.
Looking back, this relay race has never stalled. That’s the strongest sense of security historical data can offer.
Video source: @湾林
$QQQB #纳指 #美股指数
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Eugene Fama, a professor at the University of Chicago, founder of the efficient market hypothesis, and 2013 Nobel Prize winner in Economic Sciences, is widely recognized in academia as the foremost authority on how market prices are formed.
He and his collaborator Kenneth French conducted a famous study comparing the long-term performance of thousands of fund managers against statistical benchmarks, seeking to distinguish whose results came from genuine skill and whose were merely luck.
The harsh conclusion lies in the threshold: even by the most lenient standards, only a tiny proportion of managers could be statistically confirmed to possess genuine skill—and they were extremely difficult to identify in advance.
You cannot know ahead of time whether the “master” in front of you is one of those rare few or simply someone who has had a lucky streak.
Fama’s research did not claim that “nobody can win.” What it dismantled was something more fundamental: the feasibility of “picking.” A few truly skilled managers may indeed exist, but you cannot tell who will win in advance. By the time you have enough historical data to verify their skill, your money has already been bet on the outcome.
So for ordinary investors, the right takeaway is not “there are no skilled managers in the world,” but “even if they exist, you won’t be able to pick them in advance.”
Since picking is inevitably a blind bet, the most rational response is to stop trying to pick and simply take the market average, which depends on no one in particular.
Eugene Fama, a professor at the University of Chicago, founder of the efficient market hypothesis, and 2013 Nobel Prize winner in Economic Sciences, is widely recognized in academia as the foremost authority on how market prices are formed.
He and his collaborator Kenneth French conducted a famous study comparing the long-term performance of thousands of fund managers against statistical benchmarks, seeking to distinguish whose results came from genuine skill and whose were merely luck.
The harsh conclusion lies in the threshold: even by the most lenient standards, only a tiny proportion of managers could be statistically confirmed to possess genuine skill—and they were extremely difficult to identify in advance.
You cannot know ahead of time whether the “master” in front of you is one of those rare few or simply someone who has had a lucky streak.
Fama’s research did not claim that “nobody can win.” What it dismantled was something more fundamental: the feasibility of “picking.” A few truly skilled managers may indeed exist, but you cannot tell who will win in advance. By the time you have enough historical data to verify their skill, your money has already been bet on the outcome.
So for ordinary investors, the right takeaway is not “there are no skilled managers in the world,” but “even if they exist, you won’t be able to pick them in advance.”
Since picking is inevitably a blind bet, the most rational response is to stop trying to pick and simply take the market average, which depends on no one in particular.
He and his collaborator Kenneth French conducted a famous study comparing the long-term performance of thousands of fund managers against statistical benchmarks, seeking to distinguish whose results came from genuine skill and whose were merely luck.
The harsh conclusion lies in the threshold: even by the most lenient standards, only a tiny proportion of managers could be statistically confirmed to possess genuine skill—and they were extremely difficult to identify in advance.
You cannot know ahead of time whether the “master” in front of you is one of those rare few or simply someone who has had a lucky streak.
Fama’s research did not claim that “nobody can win.” What it dismantled was something more fundamental: the feasibility of “picking.” A few truly skilled managers may indeed exist, but you cannot tell who will win in advance. By the time you have enough historical data to verify their skill, your money has already been bet on the outcome.
So for ordinary investors, the right takeaway is not “there are no skilled managers in the world,” but “even if they exist, you won’t be able to pick them in advance.”
Since picking is inevitably a blind bet, the most rational response is to stop trying to pick and simply take the market average, which depends on no one in particular.
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William F. Sharpe, Stanford professor, originator of the Capital Asset Pricing Model, and Nobel laureate in Economic Sciences famed for the “Sharpe ratio”—the standard yardstick the financial world uses today to measure risk and return is named after him.
He wrote an article renowned for its brevity, titled “The Arithmetic of Active Management.”
The entire argument requires no supporting data, just two steps of arithmetic:
01. All investors collectively hold the entire market, so the weighted average performance of everyone is simply the market itself;
02. Passive investors get the market itself at zero cost, while active investors pay hefty fees to get that same market. Therefore, the average performance of the active group must be lower than that of the passive group, by exactly the amount of all costs.
The force of this paper lies in the fact that it depends on no historical data; it is a mathematical certainty. Regardless of whether markets rise or fall, and regardless of how the times change, everyone’s results averaged together equal the market’s average return. Passive investors receive that average itself, while active investors, because of the various costs incurred along the way, are destined to receive a discounted version of it. The active group’s overall performance is therefore destined to lag behind the passive group’s.
Overturning an entire industry on a single page—that is a rare feat of efficiency in the history of academia.
William F. Sharpe, Stanford professor, originator of the Capital Asset Pricing Model, and Nobel laureate in Economic Sciences famed for the “Sharpe ratio”—the standard yardstick the financial world uses today to measure risk and return is named after him.
He wrote an article renowned for its brevity, titled “The Arithmetic of Active Management.”
The entire argument requires no supporting data, just two steps of arithmetic:
01. All investors collectively hold the entire market, so the weighted average performance of everyone is simply the market itself;
02. Passive investors get the market itself at zero cost, while active investors pay hefty fees to get that same market. Therefore, the average performance of the active group must be lower than that of the passive group, by exactly the amount of all costs.
The force of this paper lies in the fact that it depends on no historical data; it is a mathematical certainty. Regardless of whether markets rise or fall, and regardless of how the times change, everyone’s results averaged together equal the market’s average return. Passive investors receive that average itself, while active investors, because of the various costs incurred along the way, are destined to receive a discounted version of it. The active group’s overall performance is therefore destined to lag behind the passive group’s.
Overturning an entire industry on a single page—that is a rare feat of efficiency in the history of academia.
He wrote an article renowned for its brevity, titled “The Arithmetic of Active Management.”
The entire argument requires no supporting data, just two steps of arithmetic:
01. All investors collectively hold the entire market, so the weighted average performance of everyone is simply the market itself;
02. Passive investors get the market itself at zero cost, while active investors pay hefty fees to get that same market. Therefore, the average performance of the active group must be lower than that of the passive group, by exactly the amount of all costs.
The force of this paper lies in the fact that it depends on no historical data; it is a mathematical certainty. Regardless of whether markets rise or fall, and regardless of how the times change, everyone’s results averaged together equal the market’s average return. Passive investors receive that average itself, while active investors, because of the various costs incurred along the way, are destined to receive a discounted version of it. The active group’s overall performance is therefore destined to lag behind the passive group’s.
Overturning an entire industry on a single page—that is a rare feat of efficiency in the history of academia.
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Verified
The Binance hack is a test—and if they ace it, their moat will only grow stronger.
When an exchange gets hacked, the first reaction is: It’s over. They’re done for. They’re going under.
But look back at the platforms in the industry that have had incidents, and you’ll see that what determines whether a market leader loses its standing isn’t whether something happened, but how it responds afterward.
When an event of this magnitude hits an established leader, handling it well could actually bring back more customers.
Why?
Because vulnerabilities are an industry-wide problem. Anyone can get hit.
What sets companies apart is how they respond afterward: reimbursing users, sharing information openly and transparently, tracking and freezing stolen funds, reviewing what happened, and making improvements.
Smaller platforms simply can’t afford to carry out this whole process—and even if they try, they can’t do it all.
So users are weighing their options. If anyone can get hit, I’ll choose the one most capable of protecting me.
For the biggest players, every crisis is an exam they have to pass. Pass, and they add a “battle-tested” badge to their name. Fail, and they may never recover—or even disappear altogether.
Seen this way, Binance’s hack isn’t entirely a bad thing.
If they deliver an industry-leading response, it’s like paying for one incident and buying credibility that competitors can’t copy, no matter how hard they try.
The Binance hack is a test—and if they ace it, their moat will only grow stronger.
When an exchange gets hacked, the first reaction is: It’s over. They’re done for. They’re going under.
But look back at the platforms in the industry that have had incidents, and you’ll see that what determines whether a market leader loses its standing isn’t whether something happened, but how it responds afterward.
When an event of this magnitude hits an established leader, handling it well could actually bring back more customers.
Why?
Because vulnerabilities are an industry-wide problem. Anyone can get hit.
What sets companies apart is how they respond afterward: reimbursing users, sharing information openly and transparently, tracking and freezing stolen funds, reviewing what happened, and making improvements.
Smaller platforms simply can’t afford to carry out this whole process—and even if they try, they can’t do it all.
So users are weighing their options. If anyone can get hit, I’ll choose the one most capable of protecting me.
For the biggest players, every crisis is an exam they have to pass. Pass, and they add a “battle-tested” badge to their name. Fail, and they may never recover—or even disappear altogether.
Seen this way, Binance’s hack isn’t entirely a bad thing.
If they deliver an industry-leading response, it’s like paying for one incident and buying credibility that competitors can’t copy, no matter how hard they try.
When an exchange gets hacked, the first reaction is: It’s over. They’re done for. They’re going under.
But look back at the platforms in the industry that have had incidents, and you’ll see that what determines whether a market leader loses its standing isn’t whether something happened, but how it responds afterward.
When an event of this magnitude hits an established leader, handling it well could actually bring back more customers.
Why?
Because vulnerabilities are an industry-wide problem. Anyone can get hit.
What sets companies apart is how they respond afterward: reimbursing users, sharing information openly and transparently, tracking and freezing stolen funds, reviewing what happened, and making improvements.
Smaller platforms simply can’t afford to carry out this whole process—and even if they try, they can’t do it all.
So users are weighing their options. If anyone can get hit, I’ll choose the one most capable of protecting me.
For the biggest players, every crisis is an exam they have to pass. Pass, and they add a “battle-tested” badge to their name. Fail, and they may never recover—or even disappear altogether.
Seen this way, Binance’s hack isn’t entirely a bad thing.
If they deliver an industry-leading response, it’s like paying for one incident and buying credibility that competitors can’t copy, no matter how hard they try.
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In 2025, approximately $1.5 billion was stolen from Bybit, making it the largest security incident in crypto history at the time. The industry responded with extensive reviews of multisig procedures and hot-cold wallet separation.
Less than a year later, a similar incident happened again—four times larger than the previous one—and the blame may once again point to the same group.
The attack paths in the two incidents were strikingly similar. This suggests that even after an attack pattern had been proven effective, the industry failed to systematically block it. Security improvements at individual exchanges have been piecemeal and incremental, with no industry-wide mandatory standards in place.
Two consecutive breaches on this scale will likely change that. Regulators and major clients have good reason to demand that exchanges disclose details of their security architecture and undergo third-party red-team testing. Security capabilities may shift from being a marketing selling point to a licensing requirement.
For ordinary users, the criteria for judging exchanges are likely to change as well.
In 2025, approximately $1.5 billion was stolen from Bybit, making it the largest security incident in crypto history at the time. The industry responded with extensive reviews of multisig procedures and hot-cold wallet separation.
Less than a year later, a similar incident happened again—four times larger than the previous one—and the blame may once again point to the same group.
The attack paths in the two incidents were strikingly similar. This suggests that even after an attack pattern had been proven effective, the industry failed to systematically block it. Security improvements at individual exchanges have been piecemeal and incremental, with no industry-wide mandatory standards in place.
Two consecutive breaches on this scale will likely change that. Regulators and major clients have good reason to demand that exchanges disclose details of their security architecture and undergo third-party red-team testing. Security capabilities may shift from being a marketing selling point to a licensing requirement.
For ordinary users, the criteria for judging exchanges are likely to change as well.
Less than a year later, a similar incident happened again—four times larger than the previous one—and the blame may once again point to the same group.
The attack paths in the two incidents were strikingly similar. This suggests that even after an attack pattern had been proven effective, the industry failed to systematically block it. Security improvements at individual exchanges have been piecemeal and incremental, with no industry-wide mandatory standards in place.
Two consecutive breaches on this scale will likely change that. Regulators and major clients have good reason to demand that exchanges disclose details of their security architecture and undergo third-party red-team testing. Security capabilities may shift from being a marketing selling point to a licensing requirement.
For ordinary users, the criteria for judging exchanges are likely to change as well.
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Article
OKX and ICE’s OKXICE | Opposed by 26 Publicly Traded CompaniesIssue focus
The opposition is not to tokenization, but to this particular platform and this particular route
26 publicly traded companies have openly opposed OKXICE tokenizing the shares they issued under the SEC’s innovation exemption framework, even though some of those companies’ shares have already been tokenized on other platforms.
So the question is not the broad one of “whether companies oppose stock tokenization,” but a very specific comparison: Why has doing the same thing on this particular platform, via this particular exemption route, triggered collective opposition, while companies have not publicly objected to other platforms or mounted a collective response of comparable strength?
OKX and ICE’s OKXICE | Opposed by 26 Publicly Traded Companies
Issue focus
The opposition is not to tokenization, but to this particular platform and this particular route
26 publicly traded companies have openly opposed OKXICE tokenizing the shares they issued under the SEC’s innovation exemption framework, even though some of those companies’ shares have already been tokenized on other platforms.
So the question is not the broad one of “whether companies oppose stock tokenization,” but a very specific comparison: Why has doing the same thing on this particular platform, via this particular exemption route, triggered collective opposition, while companies have not publicly objected to other platforms or mounted a collective response of comparable strength?
The opposition is not to tokenization, but to this particular platform and this particular route
26 publicly traded companies have openly opposed OKXICE tokenizing the shares they issued under the SEC’s innovation exemption framework, even though some of those companies’ shares have already been tokenized on other platforms.
So the question is not the broad one of “whether companies oppose stock tokenization,” but a very specific comparison: Why has doing the same thing on this particular platform, via this particular exemption route, triggered collective opposition, while companies have not publicly objected to other platforms or mounted a collective response of comparable strength?
ICEUS+1.73%
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Breaking the Signature Doesn’t Mean Destroying the Bitcoin Network
Picking a lock and tearing down an entire building are two completely different things.
Quantum computing might break Bitcoin’s current elliptic-curve signatures. That’s one thing.
Whether the Bitcoin network itself would collapse as a result is another. The signature algorithm is just one component of the system.
The Bitcoin network as a whole is maintained by nodes, miners, developers, and holders around the world. Components can be replaced—and they have been many times before, without taking the network offline.
Even if a quantum attack were to happen one day, it would threaten the security of assets associated with specific addresses. The ledger would keep recording transactions, blocks would keep being produced, and nodes would keep validating as usual.
Doomsday narratives conflate vulnerabilities at the algorithm level with the survival of the system as a whole.
That conceptual error is exactly what some cryptographers have repeatedly sought to correct.
The real risk is that upgrades may take too long. During the transition, some assets will remain in the old system, exposed to attack.
Breaking the Signature Doesn’t Mean Destroying the Bitcoin Network
Picking a lock and tearing down an entire building are two completely different things.
Quantum computing might break Bitcoin’s current elliptic-curve signatures. That’s one thing.
Whether the Bitcoin network itself would collapse as a result is another. The signature algorithm is just one component of the system.
The Bitcoin network as a whole is maintained by nodes, miners, developers, and holders around the world. Components can be replaced—and they have been many times before, without taking the network offline.
Even if a quantum attack were to happen one day, it would threaten the security of assets associated with specific addresses. The ledger would keep recording transactions, blocks would keep being produced, and nodes would keep validating as usual.
Doomsday narratives conflate vulnerabilities at the algorithm level with the survival of the system as a whole.
That conceptual error is exactly what some cryptographers have repeatedly sought to correct.
The real risk is that upgrades may take too long. During the transition, some assets will remain in the old system, exposed to attack.
Picking a lock and tearing down an entire building are two completely different things.
Quantum computing might break Bitcoin’s current elliptic-curve signatures. That’s one thing.
Whether the Bitcoin network itself would collapse as a result is another. The signature algorithm is just one component of the system.
The Bitcoin network as a whole is maintained by nodes, miners, developers, and holders around the world. Components can be replaced—and they have been many times before, without taking the network offline.
Even if a quantum attack were to happen one day, it would threaten the security of assets associated with specific addresses. The ledger would keep recording transactions, blocks would keep being produced, and nodes would keep validating as usual.
Doomsday narratives conflate vulnerabilities at the algorithm level with the survival of the system as a whole.
That conceptual error is exactly what some cryptographers have repeatedly sought to correct.
The real risk is that upgrades may take too long. During the transition, some assets will remain in the old system, exposed to attack.
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Article
Yen Carry Trade | Exacerbating Turmoil in the Global Bond MarketThe surge in Japanese government bond yields is likely driving 'Mrs. Watanabe' to close her positions, which could be an invisible hand exacerbating turmoil in the global bond market.
In this round of the global bond market storm, one player has been severely underestimated — Japan.
Japan is one of the largest creditor nations in the world.
For decades, Japan's domestic interest rates have been super low, so Japanese investors chasing returns have had to allocate funds to overseas high-yield assets. This means borrowing low-interest yen to buy high-yield dollar assets and pocketing the spread.
Japan's pensions, sovereign funds, and financial institutions hold trillions of dollars in foreign bonds, with U.S. Treasuries being the largest component. Even the trillion-dollar 'Mrs. Watanabe' would do this.
Yen Carry Trade | Exacerbating Turmoil in the Global Bond Market
The surge in Japanese government bond yields is likely driving 'Mrs. Watanabe' to close her positions, which could be an invisible hand exacerbating turmoil in the global bond market.
In this round of the global bond market storm, one player has been severely underestimated — Japan.
Japan is one of the largest creditor nations in the world.
For decades, Japan's domestic interest rates have been super low, so Japanese investors chasing returns have had to allocate funds to overseas high-yield assets. This means borrowing low-interest yen to buy high-yield dollar assets and pocketing the spread.
Japan's pensions, sovereign funds, and financial institutions hold trillions of dollars in foreign bonds, with U.S. Treasuries being the largest component. Even the trillion-dollar 'Mrs. Watanabe' would do this.
In this round of the global bond market storm, one player has been severely underestimated — Japan.
Japan is one of the largest creditor nations in the world.
For decades, Japan's domestic interest rates have been super low, so Japanese investors chasing returns have had to allocate funds to overseas high-yield assets. This means borrowing low-interest yen to buy high-yield dollar assets and pocketing the spread.
Japan's pensions, sovereign funds, and financial institutions hold trillions of dollars in foreign bonds, with U.S. Treasuries being the largest component. Even the trillion-dollar 'Mrs. Watanabe' would do this.
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Article
CLARITY Act | Who Wins? Who Loses? Who's Betting?New phase: the regulatory bill has crossed a critical threshold.
The legislative process has entered a decisive phase.
On May 14, 2026, the Senate Banking Committee passed the CLARITY Act with a vote of 15 to 9.
This event itself isn't surprising; what's unexpected is that it came earlier than most people's predictions.
Insiders know that the committee stage is actually the easiest part; the real challenges lie ahead.
The full Senate needs to gather 60 votes for it to pass.
The Agriculture Committee's version needs some coordination.
The House needs to merge the bill texts.
The White House needs to sign off.
......
If any link gets stuck, the entire process could be reset.
CLARITY Act | Who Wins? Who Loses? Who's Betting?
New phase: the regulatory bill has crossed a critical threshold.
The legislative process has entered a decisive phase.
On May 14, 2026, the Senate Banking Committee passed the CLARITY Act with a vote of 15 to 9.
This event itself isn't surprising; what's unexpected is that it came earlier than most people's predictions.
Insiders know that the committee stage is actually the easiest part; the real challenges lie ahead.
The full Senate needs to gather 60 votes for it to pass.
The Agriculture Committee's version needs some coordination.
The House needs to merge the bill texts.
The White House needs to sign off.
......
If any link gets stuck, the entire process could be reset.
The legislative process has entered a decisive phase.
On May 14, 2026, the Senate Banking Committee passed the CLARITY Act with a vote of 15 to 9.
This event itself isn't surprising; what's unexpected is that it came earlier than most people's predictions.
Insiders know that the committee stage is actually the easiest part; the real challenges lie ahead.
The full Senate needs to gather 60 votes for it to pass.
The Agriculture Committee's version needs some coordination.
The House needs to merge the bill texts.
The White House needs to sign off.
......
If any link gets stuck, the entire process could be reset.
212
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After institutions allocated to crypto ETFs, there wasn't an explosive increase in positions, not because they don't like it, but because they don't know how to classify crypto assets within their existing frameworks.
After the approval of spot ETFs for BTC and ETH, institutions have indeed been net buyers, with significant inflows into BlackRock's IBIT and Fidelity's FBTC.
However, a closer look at the numbers reveals that the proportion of crypto ETFs in the overall AUM of institutions is still very low, and the inflow speed is far below market expectations.
Institutions are buying, but the volume doesn't match the initial expectations. Why is that?
This leads to the core issue: crypto assets are seen by institutions as assets with 【no standard classification】. They are neither bonds, stocks, commodities, nor currencies.
There are no standard asset category codes, no accompanying risk models, and no industry-standard allocation ratio references.
This means that each institution wishing to allocate to crypto ETFs has to run a complete internal approval process specifically for it. This isn't just a regular approval process; it's a full framework adaptation that takes much longer.
For example: If an institution wants to allocate to crypto ETFs, which risk model should they use? What standard should the allocation ratio refer to? What format should the position report follow? Which account category does it fall under? There are no industry-standard answers for these questions.
Each institution has to design from scratch, and every step has to be justified individually. Just convincing the investment committee that "this allocation ratio is reasonable" could take several rounds of meetings.
The value of the CLARITY Act is that it solves this problem all at once.
After this, institutions won't say, "We have no precedent for this asset; we need special approval," but will directly say, "This asset belongs to digital goods, similar to gold and commodities, and can be allocated under that framework."
Looking at the history of gold ETFs, once the asset category framework is adapted, the demand for allocation will steadily grow along the model-driven path.
After institutions allocated to crypto ETFs, there wasn't an explosive increase in positions, not because they don't like it, but because they don't know how to classify crypto assets within their existing frameworks.
After the approval of spot ETFs for BTC and ETH, institutions have indeed been net buyers, with significant inflows into BlackRock's IBIT and Fidelity's FBTC.
However, a closer look at the numbers reveals that the proportion of crypto ETFs in the overall AUM of institutions is still very low, and the inflow speed is far below market expectations.
Institutions are buying, but the volume doesn't match the initial expectations. Why is that?
This leads to the core issue: crypto assets are seen by institutions as assets with 【no standard classification】. They are neither bonds, stocks, commodities, nor currencies.
There are no standard asset category codes, no accompanying risk models, and no industry-standard allocation ratio references.
This means that each institution wishing to allocate to crypto ETFs has to run a complete internal approval process specifically for it. This isn't just a regular approval process; it's a full framework adaptation that takes much longer.
For example: If an institution wants to allocate to crypto ETFs, which risk model should they use? What standard should the allocation ratio refer to? What format should the position report follow? Which account category does it fall under? There are no industry-standard answers for these questions.
Each institution has to design from scratch, and every step has to be justified individually. Just convincing the investment committee that "this allocation ratio is reasonable" could take several rounds of meetings.
The value of the CLARITY Act is that it solves this problem all at once.
After this, institutions won't say, "We have no precedent for this asset; we need special approval," but will directly say, "This asset belongs to digital goods, similar to gold and commodities, and can be allocated under that framework."
Looking at the history of gold ETFs, once the asset category framework is adapted, the demand for allocation will steadily grow along the model-driven path.
After the approval of spot ETFs for BTC and ETH, institutions have indeed been net buyers, with significant inflows into BlackRock's IBIT and Fidelity's FBTC.
However, a closer look at the numbers reveals that the proportion of crypto ETFs in the overall AUM of institutions is still very low, and the inflow speed is far below market expectations.
Institutions are buying, but the volume doesn't match the initial expectations. Why is that?
This leads to the core issue: crypto assets are seen by institutions as assets with 【no standard classification】. They are neither bonds, stocks, commodities, nor currencies.
There are no standard asset category codes, no accompanying risk models, and no industry-standard allocation ratio references.
This means that each institution wishing to allocate to crypto ETFs has to run a complete internal approval process specifically for it. This isn't just a regular approval process; it's a full framework adaptation that takes much longer.
For example: If an institution wants to allocate to crypto ETFs, which risk model should they use? What standard should the allocation ratio refer to? What format should the position report follow? Which account category does it fall under? There are no industry-standard answers for these questions.
Each institution has to design from scratch, and every step has to be justified individually. Just convincing the investment committee that "this allocation ratio is reasonable" could take several rounds of meetings.
The value of the CLARITY Act is that it solves this problem all at once.
After this, institutions won't say, "We have no precedent for this asset; we need special approval," but will directly say, "This asset belongs to digital goods, similar to gold and commodities, and can be allocated under that framework."
Looking at the history of gold ETFs, once the asset category framework is adapted, the demand for allocation will steadily grow along the model-driven path.
1
235
·
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Article
$uPEG, $SATO, $SLOP丨【Creating Actions】Expand DeFi Boundaries#uPEG #SATO #slop
Unlocking infinite innovation space.
Hooks build liquidity Legos.
From rigid trading tools to a programmable financial infrastructure.
A lot of folks hearing that Uniswap V4 introduced Hooks might think, 'Here we go again with the hype.'
But this time, there might actually be something substantial.
The essence of Hooks is to modularize custom logic embedded throughout the entire lifecycle of a liquidity pool. Previously, Uniswap's pool functionality was fixed—just swap and collect fees.
After Hooks dropped, the pools became programmable—developers can plug in dynamic fees, limit orders, auto-compounding features, and even tightly integrate trading actions with completely unrelated on-chain activities like art generation and NFT burning.
$uPEG, $SATO, $SLOP丨【Creating Actions】Expand DeFi Boundaries
#uPEG #SATO #slop
Unlocking infinite innovation space.
Hooks build liquidity Legos.
From rigid trading tools to a programmable financial infrastructure.
A lot of folks hearing that Uniswap V4 introduced Hooks might think, 'Here we go again with the hype.'
But this time, there might actually be something substantial.
The essence of Hooks is to modularize custom logic embedded throughout the entire lifecycle of a liquidity pool. Previously, Uniswap's pool functionality was fixed—just swap and collect fees.
After Hooks dropped, the pools became programmable—developers can plug in dynamic fees, limit orders, auto-compounding features, and even tightly integrate trading actions with completely unrelated on-chain activities like art generation and NFT burning.
Unlocking infinite innovation space.
Hooks build liquidity Legos.
From rigid trading tools to a programmable financial infrastructure.
A lot of folks hearing that Uniswap V4 introduced Hooks might think, 'Here we go again with the hype.'
But this time, there might actually be something substantial.
The essence of Hooks is to modularize custom logic embedded throughout the entire lifecycle of a liquidity pool. Previously, Uniswap's pool functionality was fixed—just swap and collect fees.
After Hooks dropped, the pools became programmable—developers can plug in dynamic fees, limit orders, auto-compounding features, and even tightly integrate trading actions with completely unrelated on-chain activities like art generation and NFT burning.
220
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Article
What are the Hooks in Uniswap V4?What are the Hooks in Uniswap V4? Why do they call them hooks?
In the programming world, a 'Hook' is a classic term that refers to specific points in the main workflow of a system where external code can attach and execute custom logic without altering the core code itself.
We can think of Hooks as little programs or smart triggers attached to each liquidity pool. Developers can set rules in advance, allowing the liquidity pool to automatically execute operations at specific times.
For example, checking participant eligibility before a trade, dynamically adjusting fees based on market fluctuations during a trade, or automatically reinvesting profits after a trade.
What are the Hooks in Uniswap V4?
What are the Hooks in Uniswap V4? Why do they call them hooks?
In the programming world, a 'Hook' is a classic term that refers to specific points in the main workflow of a system where external code can attach and execute custom logic without altering the core code itself.
We can think of Hooks as little programs or smart triggers attached to each liquidity pool. Developers can set rules in advance, allowing the liquidity pool to automatically execute operations at specific times.
For example, checking participant eligibility before a trade, dynamically adjusting fees based on market fluctuations during a trade, or automatically reinvesting profits after a trade.
In the programming world, a 'Hook' is a classic term that refers to specific points in the main workflow of a system where external code can attach and execute custom logic without altering the core code itself.
We can think of Hooks as little programs or smart triggers attached to each liquidity pool. Developers can set rules in advance, allowing the liquidity pool to automatically execute operations at specific times.
For example, checking participant eligibility before a trade, dynamically adjusting fees based on market fluctuations during a trade, or automatically reinvesting profits after a trade.
545
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I heard that the liquidity in crypto has all flowed into the US stock market, treating those stocks like meme coins and shitcoins, is that right?
I heard that the liquidity in crypto has all flowed into the US stock market, treating those stocks like meme coins and shitcoins, is that right?
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Bearish
The explosive growth and certain prospects in the AI sector are attracting a ton of crypto talent and capital to shift its way.
By 2025, AI venture capital is expected to exceed $200 billion, while crypto only sits at $19.7 billion, creating a massive capital gap that results in a powerful resource siphoning effect.
The weekly code commits in the crypto industry have plummeted by 75% since the start of 2025, with active developers down by 56%. By early 2026, hiring in the crypto space has nosedived by 80% year-on-year, with only about 6.5 new positions created daily.
This migration is seen as a natural selection of tech talent in search of higher returns, more stable development paths, and a stronger sense of being at the tech frontier.
AI companies like OpenAI, Anthropic, and DeepSeek offer compensation and growth opportunities that far exceed the crypto industry's average, while the token incentives and remote culture that crypto once relied on are being diluted by the globalization of remote hiring and competitive salaries also provided by AI firms.
This is essentially a rational choice for tech talent during the cyclical bear market of the crypto space.
Moreover, behind star AI projects like Hermes Agent and OpenRouter are seasoned figures from the crypto industry.
They are successfully transferring the product thinking, community operations, and rapid iteration capabilities accumulated in the Web3 space to the AI track.
🚀 The hotshot Hermes Agent is backed by the open-source AI research institution Nous Research, whose CEO Jeffrey Quesnelle was the chief engineer for the Ethereum MEV infrastructure project Eden Network.
🚀 The founder of the world’s largest AI large model aggregation platform, OpenRouter, Alex Atallah, was a co-founder of OpenSea.
#Aİ #AI代理 #x402
The explosive growth and certain prospects in the AI sector are attracting a ton of crypto talent and capital to shift its way.
By 2025, AI venture capital is expected to exceed $200 billion, while crypto only sits at $19.7 billion, creating a massive capital gap that results in a powerful resource siphoning effect.
The weekly code commits in the crypto industry have plummeted by 75% since the start of 2025, with active developers down by 56%. By early 2026, hiring in the crypto space has nosedived by 80% year-on-year, with only about 6.5 new positions created daily.
This migration is seen as a natural selection of tech talent in search of higher returns, more stable development paths, and a stronger sense of being at the tech frontier.
AI companies like OpenAI, Anthropic, and DeepSeek offer compensation and growth opportunities that far exceed the crypto industry's average, while the token incentives and remote culture that crypto once relied on are being diluted by the globalization of remote hiring and competitive salaries also provided by AI firms.
This is essentially a rational choice for tech talent during the cyclical bear market of the crypto space.
Moreover, behind star AI projects like Hermes Agent and OpenRouter are seasoned figures from the crypto industry.
They are successfully transferring the product thinking, community operations, and rapid iteration capabilities accumulated in the Web3 space to the AI track.
🚀 The hotshot Hermes Agent is backed by the open-source AI research institution Nous Research, whose CEO Jeffrey Quesnelle was the chief engineer for the Ethereum MEV infrastructure project Eden Network.
🚀 The founder of the world’s largest AI large model aggregation platform, OpenRouter, Alex Atallah, was a co-founder of OpenSea.
#Aİ #AI代理 #x402
By 2025, AI venture capital is expected to exceed $200 billion, while crypto only sits at $19.7 billion, creating a massive capital gap that results in a powerful resource siphoning effect.
The weekly code commits in the crypto industry have plummeted by 75% since the start of 2025, with active developers down by 56%. By early 2026, hiring in the crypto space has nosedived by 80% year-on-year, with only about 6.5 new positions created daily.
This migration is seen as a natural selection of tech talent in search of higher returns, more stable development paths, and a stronger sense of being at the tech frontier.
AI companies like OpenAI, Anthropic, and DeepSeek offer compensation and growth opportunities that far exceed the crypto industry's average, while the token incentives and remote culture that crypto once relied on are being diluted by the globalization of remote hiring and competitive salaries also provided by AI firms.
This is essentially a rational choice for tech talent during the cyclical bear market of the crypto space.
Moreover, behind star AI projects like Hermes Agent and OpenRouter are seasoned figures from the crypto industry.
They are successfully transferring the product thinking, community operations, and rapid iteration capabilities accumulated in the Web3 space to the AI track.
🚀 The hotshot Hermes Agent is backed by the open-source AI research institution Nous Research, whose CEO Jeffrey Quesnelle was the chief engineer for the Ethereum MEV infrastructure project Eden Network.
🚀 The founder of the world’s largest AI large model aggregation platform, OpenRouter, Alex Atallah, was a co-founder of OpenSea.
#Aİ #AI代理 #x402
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☀️First off, you just need to study the crypto market,
⛈️Now, you also need to keep an eye on US stocks, AI, macro liquidity, geopolitical factors ......
The era where Bitcoin's price was driven by a single narrative (like halving cycles or digital gold) is over.
Traders are gradually realizing that Bitcoin's price is actually the result of multiple structural forces at play: ETF capital flows, miner sell pressure, corporate treasury accumulation, derivatives liquidation, regulatory policy changes, and the tightening or loosening of macro liquidity ......
Therefore, the analytical framework must shift from 【listening to stories】 to 【seeing structures】. This includes analyzing on-chain data (like illiquid supply, net exchange flows), monitoring daily ETF inflows and outflows, observing options market position distributions/expirations, and evaluating miners' break-even points and expectations around the Fed's actions ......
In this new paradigm where structure reigns, having a profound understanding of the market's microstructure often allows you to better capture market trends, rather than blindly chasing grand narratives.
☀️First off, you just need to study the crypto market,
⛈️Now, you also need to keep an eye on US stocks, AI, macro liquidity, geopolitical factors ......
The era where Bitcoin's price was driven by a single narrative (like halving cycles or digital gold) is over.
Traders are gradually realizing that Bitcoin's price is actually the result of multiple structural forces at play: ETF capital flows, miner sell pressure, corporate treasury accumulation, derivatives liquidation, regulatory policy changes, and the tightening or loosening of macro liquidity ......
Therefore, the analytical framework must shift from 【listening to stories】 to 【seeing structures】. This includes analyzing on-chain data (like illiquid supply, net exchange flows), monitoring daily ETF inflows and outflows, observing options market position distributions/expirations, and evaluating miners' break-even points and expectations around the Fed's actions ......
In this new paradigm where structure reigns, having a profound understanding of the market's microstructure often allows you to better capture market trends, rather than blindly chasing grand narratives.
⛈️Now, you also need to keep an eye on US stocks, AI, macro liquidity, geopolitical factors ......
The era where Bitcoin's price was driven by a single narrative (like halving cycles or digital gold) is over.
Traders are gradually realizing that Bitcoin's price is actually the result of multiple structural forces at play: ETF capital flows, miner sell pressure, corporate treasury accumulation, derivatives liquidation, regulatory policy changes, and the tightening or loosening of macro liquidity ......
Therefore, the analytical framework must shift from 【listening to stories】 to 【seeing structures】. This includes analyzing on-chain data (like illiquid supply, net exchange flows), monitoring daily ETF inflows and outflows, observing options market position distributions/expirations, and evaluating miners' break-even points and expectations around the Fed's actions ......
In this new paradigm where structure reigns, having a profound understanding of the market's microstructure often allows you to better capture market trends, rather than blindly chasing grand narratives.
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From escaping Wall Street to returning to Wall Street
Personally, I find it ironic that Bitcoin is currently being co-opted by the establishment to achieve its mainstream status, despite its anti-establishment origins.
The genesis block of Bitcoin even has a critique of the traditional financial system etched into it.
However, the largest wave of adoption right now is being driven by the very entities it aimed to disrupt, like banks, investment banks, and asset management firms.
Major whales might also leverage the ETF's physical exchange mechanism to move Bitcoin from decentralized wallets to institutional custody accounts like those at BlackRock, in exchange for more liquid and protected fund shares within the traditional financial system.
This creates a profound paradox: Bitcoin gains the widespread recognition and legitimacy it initially dreamed of through being absorbed and regulated by the traditional financial system.
#华尔街 #比特币 #传统金融
From escaping Wall Street to returning to Wall Street
Personally, I find it ironic that Bitcoin is currently being co-opted by the establishment to achieve its mainstream status, despite its anti-establishment origins.
The genesis block of Bitcoin even has a critique of the traditional financial system etched into it.
However, the largest wave of adoption right now is being driven by the very entities it aimed to disrupt, like banks, investment banks, and asset management firms.
Major whales might also leverage the ETF's physical exchange mechanism to move Bitcoin from decentralized wallets to institutional custody accounts like those at BlackRock, in exchange for more liquid and protected fund shares within the traditional financial system.
This creates a profound paradox: Bitcoin gains the widespread recognition and legitimacy it initially dreamed of through being absorbed and regulated by the traditional financial system.
#华尔街 #比特币 #传统金融
Personally, I find it ironic that Bitcoin is currently being co-opted by the establishment to achieve its mainstream status, despite its anti-establishment origins.
The genesis block of Bitcoin even has a critique of the traditional financial system etched into it.
However, the largest wave of adoption right now is being driven by the very entities it aimed to disrupt, like banks, investment banks, and asset management firms.
Major whales might also leverage the ETF's physical exchange mechanism to move Bitcoin from decentralized wallets to institutional custody accounts like those at BlackRock, in exchange for more liquid and protected fund shares within the traditional financial system.
This creates a profound paradox: Bitcoin gains the widespread recognition and legitimacy it initially dreamed of through being absorbed and regulated by the traditional financial system.
#华尔街 #比特币 #传统金融
191
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Head of ETH treasury firm — BITMINE, announces it will slow down its ETH purchases. Their stack is incredibly robust, holding 5.18 million ETH, of which 4.36 million are staked.
Here lies a structural cognitive gap: over 80% of investors in the crypto space only understand cryptocurrencies as price speculation.
This cognitive model is singular and linear, meaning that 【buying is the only bullish action, selling/ceasing to buy is bearish behavior】.
In reality, for institutions holding millions of ETH, price appreciation is just one dimension of their massive profit matrix.
Even though BITMINE is slowing its buying pace, their methods of earning through staking, capturing ecosystem value via protocol development, and innovating financial products to set industry standards represent a more advanced and sustainable way of being bullish and realizing value.
This is a multidimensional game of capital, showcasing the profound cognitive and behavioral gap between institutions and retail investors.
#BITMINE #DAT #以太坊 #以太坊质押 #ETH
Head of ETH treasury firm — BITMINE, announces it will slow down its ETH purchases. Their stack is incredibly robust, holding 5.18 million ETH, of which 4.36 million are staked.
Here lies a structural cognitive gap: over 80% of investors in the crypto space only understand cryptocurrencies as price speculation.
This cognitive model is singular and linear, meaning that 【buying is the only bullish action, selling/ceasing to buy is bearish behavior】.
In reality, for institutions holding millions of ETH, price appreciation is just one dimension of their massive profit matrix.
Even though BITMINE is slowing its buying pace, their methods of earning through staking, capturing ecosystem value via protocol development, and innovating financial products to set industry standards represent a more advanced and sustainable way of being bullish and realizing value.
This is a multidimensional game of capital, showcasing the profound cognitive and behavioral gap between institutions and retail investors.
#BITMINE #DAT #以太坊 #以太坊质押 #ETH
Here lies a structural cognitive gap: over 80% of investors in the crypto space only understand cryptocurrencies as price speculation.
This cognitive model is singular and linear, meaning that 【buying is the only bullish action, selling/ceasing to buy is bearish behavior】.
In reality, for institutions holding millions of ETH, price appreciation is just one dimension of their massive profit matrix.
Even though BITMINE is slowing its buying pace, their methods of earning through staking, capturing ecosystem value via protocol development, and innovating financial products to set industry standards represent a more advanced and sustainable way of being bullish and realizing value.
This is a multidimensional game of capital, showcasing the profound cognitive and behavioral gap between institutions and retail investors.
#BITMINE #DAT #以太坊 #以太坊质押 #ETH
1
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$BTC LONG SETUP ... NEXT TARGET 81,923.14
Upper Range Breakout Observed Alongside Balanced Momentum Signals
Entry: 78,610.70 - 78,959.38 (Long)
TP1: 79,831.07
TP2: 80,877.11
Final TP: 81,923.14
SL: 77,739.01
Price expanded upward over the past twenty-four hours to trade above the peak of the last twenty four-hour candles. As the relative strength index remains neutral on the four-hour chart, traders monitor whether this level transitions into support.
As long as 78,610.70 holds, structure stays constructive
Must use stop loss while trading
Trade $BTC
Not financial advice. Always DYOR.
Like & Follow for Daily Trade Analytics & Insider News. @SarwatAK
#HotTrends #TechnicalAnalysis #BTCRebounds80K
SarwatAK
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