CoinRank

As we enter early 2026, narratives come and go, but real crypto adoption is quietly moving from price action to institutional-grade infrastructure.

Host | Harry @CoinRank_io
Sponsor | David Strategy Advisor of @aiwayworld

Guest Speakers
JACK | CMO @xone_chain
Austin | Ambassador @Linkr_Web3
Mike | CMO @AllInX_Exchange
Cheeryjoe | Ambassador @CoinMy_Cex

Time: 2026/1/8 20:00 (UTC+8)

X Space: https://x.com/i/spaces/1OyKAjgOlkbGb?s=20
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Tune in and join us live as we discuss where crypto is truly moving from narrative to infrastructure — and how RWA is driving that shift. 🚀
#CoinRank #AMA #Web3 #RWA

Gold May Surpass US Treasury Bonds to Become the Largest Official Reserve Asset

Polymarket’s denial of a US invasion of Venezuela sparks strong user discontent.

opBNB mainnet completes Fourier hard fork, reducing block time to 250 milliseconds

Welcome to CoinRank Daily Data Report. In this column series, CoinRank will provide important daily cryptocurrency data news, allowing readers to quickly understand the latest developments in the cryptocurrency market.

Gold May Surpass US Treasury Bonds to Become the Largest Official Reserve Asset 

 

Driven by the surge in gold prices over the past year and active purchases by central banks worldwide, gold is poised to surpass US Treasury bonds to become the largest reserve asset held by US governments overseas.

 

According to data released this month by the World Gold Council, the total amount of official US gold reserves held overseas exceeds 900 million troy ounces (data for most countries is as of the end of November, while data for a few countries is as of the end of October).

 

Based on gold prices on November 30, this is equivalent to $3.82 trillion in gold.

 

In comparison, as of October, the value of long-term and short-term US Treasury bonds held by US governments overseas was close to $3.88 trillion.

 

Assuming that the size of central bank gold reserves remains unchanged by the end of the year, based on year-end prices, the value of US official gold reserves held overseas would be $3.93 trillion, already exceeding the size of US Treasury bonds held by overseas governments.

 

Why Gold Is Surging: Central Banks, Sanctions, and Trust-1

Gold Front-Runs QE as Bitcoin Waits for Liquidity-2

 

Polymarket’s denial of a US invasion of Venezuela sparks strong user discontent.

 

The decentralized prediction market Polymarket’s refusal to classify the recent US military raid on Venezuela and the arrest of President Maduro and his wife as an “invasion” has sparked strong user discontent.

 

Despite the US seizing power and taking the head of state to the US, contracts worth millions of dollars related to “invasion” were ruled “not triggered,” drawing criticism from gamblers who see it as “redefining facts.”

 

The platform, founded by crypto entrepreneurs, received approval from the US Commodity Futures Trading Commission (CFTC) to return to the US market after Donald Trump Jr., son of former President Trump, invested in and joined its board.

 

This incident not only raises questions about the transparency of the judgment criteria but also raises deeper concerns about insider trading and whether the platform is politically influenced.

 

This incident reflects the risks of ambiguity and regulatory vacuum in the definition of real-world political and military events faced by decentralized prediction markets.

 

opBNB mainnet completes Fourier hard fork, reducing block time to 250 milliseconds

 

According to the official BNB Chain announcement, opBNB completed its Fourier mainnet hard fork upgrade on January 7, 2026 at 11:00 (UTC+8). The core change is merging PR #305, reducing the block interval from 500 milliseconds to 250 milliseconds, significantly improving transaction throughput and confirmation speed.

 

CZ encourages developers to continue building and promoting the development of the BNB ecosystem.

 

〈CoinRank Daily Data Report (1/7)｜Gold May Surpass US Treasury Bonds to Become the Largest Official Reserve Asset〉這篇文章最早發佈於《CoinRank》。

Bitcoin’s recent rebound has improved sentiment, but price strength alone is insufficient to confirm a full recovery without supporting liquidity and macro data.

Stablecoin supply, ETF holdings, and derivatives positioning show limited improvement, suggesting that capital commitment to Bitcoin remains cautious rather than conviction-driven.

Until real rates fall, liquidity expands, and sustained ETF inflows appear, waiting for clearer confirmation may offer better risk control than chasing short-term rallies.

Bitcoin (BTC) has rebounded recently, but macro conditions, ETF flows, stablecoin data, and derivatives positioning suggest the recovery is not yet confirmed.

Over the past few days, Bitcoin (BTC) has shown clear signs of short-term recovery. Prices have moved higher, market discussions have heated up, and overall sentiment has improved rapidly. For many participants, this rebound feels like the long-awaited signal that the market is finally turning bullish again.

 

However, history repeatedly shows that price action alone is rarely sufficient to confirm a true trend reversal. While the recent move in Bitcoin (BTC) is undeniable, a closer look at macro indicators, liquidity conditions, on-chain data, and derivatives positioning suggests that the market may still be in a transitional phase rather than a confirmed recovery.

 

This article first outlines the recent rebound in Bitcoin (BTC) and the reasons commonly cited to support a bullish narrative. It then presents a data-driven counterpoint, explaining why caution remains justified at this stage.

 

 

BITCOIN (BTC) RECENT REBOUND AND MARKET REACTION

 

The most obvious signal of recovery is price behavior. After a prolonged period of weakness, Bitcoin (BTC) has climbed steadily over several sessions, breaking the monotony of downward or sideways movement. This rebound has been fast enough to reignite speculative interest and short-term optimism.

 

At the same time, market sentiment indicators have reacted sharply. The crypto Fear & Greed Index jumped from deeply pessimistic levels to near-neutral territory within a single day. Such rapid shifts tend to amplify confidence, as traders interpret them as evidence that downside risk has already been absorbed.

 

Spot market activity has also picked up modestly. Volumes are higher than during the recent lows, reinforcing the perception that capital is returning. On the surface, these developments paint a convincing picture of recovery. Yet surface-level strength often hides unresolved structural constraints.

 

WHY SOME BELIEVE BITCOIN (BTC) IS RECOVERING

 

One widely cited argument is the macro environment. Nominal interest rates in the United States are declining, which theoretically benefits risk assets like Bitcoin (BTC). Lower nominal yields reduce the opportunity cost of holding assets that do not generate cash flow.

 

Another frequently mentioned factor is ETF activity. Spot Bitcoin ETFs have become a key transmission channel between traditional finance and crypto markets. Even modest changes in ETF flows can influence short-term price action, leading many to attribute the recent rebound in Bitcoin (BTC) to institutional positioning.

 

Finally, sentiment-based indicators reinforce the bullish narrative. As fear levels rise from extreme pessimism toward neutrality, traders often interpret this as confirmation that the worst phase is over. In previous cycles, similar sentiment shifts sometimes preceded broader trend reversals.

 

Despite these arguments, none of them are sufficient on their own to confirm that Bitcoin (BTC) has entered a sustainable recovery phase.

 

MACRO DATA SHOWS BITCOIN (BTC) LIQUIDITY REMAINS CONSTRAINED

 

From a macro perspective, the issue is not whether nominal rates are falling. That development has been well understood for some time. The more critical question is whether liquidity is actually flowing into the financial system.

 

At present, the so-called intermediate layer of liquidity remains blocked. While the U.S. is lowering interest rates, it is simultaneously issuing large amounts of debt, effectively absorbing liquidity. This dynamic limits how much capital can reach risk assets, including Bitcoin (BTC).

 

Conditions in the real economy reinforce this constraint. Bank lending standards remain tight, and corporations are hesitant to borrow. Without credit expansion, monetary easing struggles to translate into broader market liquidity.

 

This situation is reflected in real interest rates. Over the past two weeks, real rates have increased slightly, from around 1.92 to approximately 1.94. Even small increases matter, as rising real rates are inconsistent with the liquidity expansion typically required for a sustained bull market.

 

The U.S. dollar index supports this interpretation. During the same period, DXY has remained largely unchanged, moving only marginally from about 98.4 to 98.2. A stable dollar suggests that global liquidity conditions remain restrictive, offering limited macro support for Bitcoin (BTC).

 

MID-TERM ON-CHAIN AND ETF DATA SIGNAL CAUTION FOR BITCOIN (BTC)

 

Mid-term crypto-native indicators also point to caution. On-chain stablecoin supply, a key proxy for native liquidity, has shown minimal change. Over the past two weeks, total stablecoin market capitalization declined slightly from around 270 to approximately 268.8, indicating that fresh capital inflows remain limited.

 

ETF data tells a similar story. Total spot Bitcoin ETF holdings are effectively unchanged at roughly $118 billion, consistent with levels seen two weeks ago. While short-term fluctuations exist, the overall picture suggests that institutional exposure to Bitcoin (BTC) has not meaningfully increased.

 

Recent price strength appears to be driven primarily by short-term ETF flow dynamics rather than sustained accumulation. Over the past five trading days, Bitcoin ETFs recorded four days of net outflows, including a large single-day outflow of approximately $1.15 billion.

 

Importantly, historical context matters. In early March 2024, the market experienced a structurally similar phase. Despite prolonged net inflows at the time, prices eventually declined and entered a deeper correction lasting more than two weeks. This episode highlights why ETF flows alone cannot confirm a durable recovery in Bitcoin (BTC).

 

 

SENTIMENT VS DERIVATIVES DATA IN BITCOIN (BTC) MARKETS

 

Sentiment indicators have rebounded sharply, but derivatives data remains subdued. The Fear & Greed Index jumped from the mid-20s to around 44 within a day, compared with a two-week average near 23.

 

Such rapid sentiment shifts often reflect emotional relief rather than structural improvement. When sentiment recovers faster than liquidity and positioning, the risk of false signals increases.

 

Derivatives positioning supports this cautious view. Open interest has remained relatively stable around 56, showing no meaningful expansion in leveraged exposure. A genuine trend reversal typically coincides with growing participation, which has yet to materialize in Bitcoin (BTC) markets.

 

In essence, traders feel more optimistic, but they are not yet committing capital aggressively.

 

CONCLUSION: WHY WAITING ON BITCOIN (BTC) STILL MAKES SENSE

 

The recent rebound in Bitcoin (BTC) is real, but the data suggests it is incomplete. Price and sentiment have moved first, while liquidity, macro confirmation, and positioning remain weak.

 

This does not imply an imminent collapse. It does imply that confidence is running ahead of confirmation. Without clear improvements in real rates, dollar weakness, stablecoin expansion, and sustained ETF inflows, the probability of a false recovery remains high.

 

In uncertain conditions, patience is not a missed opportunity but a form of risk management. Markets rarely move in a straight line, and clearer entry points often appear once trends are genuinely established.

 

When prices rise without strong structural support, caution is not pessimism—it is discipline.

 

Read More:

Gold Front-Runs QE as Bitcoin Waits for Liquidity-2

Why Gold Is Surging: Central Banks, Sanctions, and Trust-1

〈Bitcoin Is Rebounding, but the Data Suggests the Recovery Is Still Incomplete〉這篇文章最早發佈於《CoinRank》。

Polymarket partners with Parcl to integrate daily housing price indices into on-chain prediction markets, letting users trade real-estate price outcomes with USDC on Polygon.

The new market provides transparent settlement using publicly verifiable indices, reducing reliance on slow, subjective traditional real estate data.

Traders can express bullish or bearish views on housing prices, effectively creating a “shorting tool” and risk management option for real estate.

Polymarket and Parcl launch a real-estate prediction market using daily housing price indices, enabling on-chain “shorting” and new risk tools for housing prices.

The value proposition of “everything is predictable” continues to rise.

 

On the evening of January 5th, the on-chain real estate platform Parcl announced a partnership with the prediction market Polymarket, aiming to integrate Parcl’s daily housing price indices into Polymarket’s new real estate prediction market. Influenced by this news, Parcl’s native token PRCL surged by over 150% at its peak before retracing. Its current price is approximately $0.042, with a market capitalization of $19 million.

 

PRCL Price Chart

 

Operational Details of Polymarket’s Real Estate Prediction Market Segment

 

Partnership Details:

 

Parcl provides daily housing price indices, serving as an independent, transparent reference data source for market settlement;

Polymarket is responsible for listing and operating the markets, where users can trade using USDC on the Polygon chain;

Market settlements are based on Parcl’s publicly verifiable indices, avoiding the delays (typically monthly) and subjectivity associated with traditional real estate data.

 

Market Types:

 

Predicting whether housing prices will rise or fall within a month, quarter, or year;

Threshold-based markets: e.g., whether prices will exceed a specific level;

Each market links to a dedicated settlement page on Parcl, displaying final values, historical data, and index calculation methodology.

 

Coverage:

 

Initially launching with high-liquidity U.S. cities such as New York, Miami, San Francisco, Austin, etc.;

Plans to expand to more cities and market types based on user demand.

 

Current Status:

 

Currently, this segment has only launched 7 monthly real estate prediction events with relatively low liquidity. The event with the highest trading volume, “Los Angeles, USA – House Median Price on Feb 1st,” has only $3,700 in volume.

 

New Real Estate Prediction Market Segment on Polymarket

 

In traditional real estate markets, whether bullish or bearish, such expectations are difficult to express directly, let alone form continuous market signals. Polymarket’s introduction essentially separates “judgments on housing prices” from asset transactions. As long as there is a clear settlement standard, the expectation itself can be priced independently.

 

Real Estate Markets Finally Have a “Shorting Tool”

 

An easily overlooked fact is that the potential demand for real estate-related markets does not solely originate from native speculators in the crypto world.

 

In the traditional financial system, “falling housing prices” is almost a risk that cannot be directly hedged. Whether holding property or having an asset structure and income source highly dependent on a particular city’s real estate cycle, the practical response is often to continue holding or directly sell the physical asset—both involve high transaction costs, long cycles, and lack flexible intermediate options. As KOL 0xMarioNawfal (@RoundtableSpace) stated: “This is far more than betting; it’s bringing liquidity to one of the world’s most illiquid markets. Imagine housing prices are at historic highs, you expect a crash but can’t sell your house—now you can hedge, short the market.”

 

The introduction of prediction markets abstracts the risk of falling housing prices into a tradable judgment. When prices are high and market expectations begin to weaken, the price trend of real estate itself can be priced separately without having to manage risk by disposing of the underlying asset.

 

Through Polymarket, the downside risk of real estate prices is abstracted into a tradable judgment rather than necessitating the disposal of physical assets. From this perspective, Polymarket’s real estate prediction markets resemble a simplified macro hedging mechanism more than a mere speculative game around price movements. It does not change the liquidity structure of real estate assets themselves but provides a tradable layer for a traditionally low-liquidity market that can reflect expectations in real-time.

 

Polymarket CMO Matthew Modabber stated: “Prediction markets work best for events with clear, verifiable data. Parcl’s daily housing price indices provide us with a transparent, consistent settlement foundation. Real estate should be a first-class category in prediction markets.”

 

This collaboration between Polymarket and Parcl also introduces traditional real estate price signals into the crypto system: Originally low-frequency, closed, and high-barrier-to-entry assets are decomposed into settleable, verifiable, and tradable index outcomes, taking a form closer to stock indices or crypto derivatives. This may represent a more practical and demand-aligned implementation path within the RWA narrative.

 

Read the original text

 

Read More:

Why Gold Is Surging: Central Banks, Sanctions, and Trust-1

Bitwise: Why Crypto Is Moving Beyond the Four-Year Cycle-2

〈Real Estate “Shorting Tool” Emerges, Polymarket Launches Real Estate Prediction Market〉這篇文章最早發佈於《CoinRank》。

#Coinbase CEO: The vast majority of his personal net worth remains in Coinbase stock
Tempo releases the TIP-20 token standard designed specifically for stablecoins and payment scenarios
#opBNB mainnet completes Fourier hard fork, reducing block time to 250 milliseconds
#Polymarket denies US invasion of Venezuela, sparking strong user dissatisfaction
Multiple regions warn against "trial card" scams involving virtual currencies, using "free benefits" as a guise to lure victims to telecom fraud.

#CoinRank #GM

Privacy becomes a foundational competitive moat in crypto, with privacy chains creating strong network effects and high migration costs, reshaping value distribution.

Decentralized messaging must eliminate private servers to ensure ownership and resilience, transcending encryption to prioritize open protocols and user-controlled identity.

“Secrets-as-a-service” is proposed as core infrastructure, offering programmable data access, client-side encryption, and decentralized key governance for secure, compliant innovation.

he surge of Zcash in 2025 has reignited the privacy narrative within the crypto industry. Often, we only see rising sentiment and capital inflows, with many likely believing this is just a temporary wave of emotion, lacking conviction in the sustainability of the narrative itself. a16z crypto’s latest report, “Privacy trends for 2026,” attempts to reframe the privacy discussion within the context of infrastructure and long-term evolutionary logic. By gathering collective observations from several seasoned crypto industry practitioners, the article outlines their judgments on “how privacy will shape the next phase of the crypto ecosystem” across multiple dimensions, from decentralized communication and data access control to security engineering methodologies.

1. Privacy Will Become the Most Important “Moat” in Crypto This Year

 

Privacy is one of the key functions for the global financial system’s transition on-chain; simultaneously, it is a function severely lacking in almost all blockchains today. For most chains, privacy has long been an afterthought. But now, “privacy” alone is enough to create a substantial distinction between one chain and all others.

 

Privacy brings an even more important point: chain-level lock-in effects—or, if you prefer, the “privacy network effect.” Especially in a world where competing solely on performance is no longer sufficient to win.

 

Thanks to cross-chain bridge protocols, migrating between different chains is almost costless as long as all data is public. But once privacy is involved, the situation changes completely: Cross-chain token transfers are easy; cross-chain “secret” transfers are extremely difficult. Operating outside the privacy zone always carries the risk of identity inference by monitors through on-chain data, mempool, or network traffic. Whether switching from a privacy chain to a public chain, or between two privacy chains, a large amount of metadata is leaked, such as transaction timing, size correlations, etc., making users easier to track.

 

Compared to new public chains that lack differentiation and whose fees are likely to be compressed to near zero in competition (block space is essentially becoming a commodity), blockchains with privacy capabilities can form stronger network effects. The reality is: If a “general-purpose” blockchain lacks a thriving ecosystem, killer applications, or asymmetric distribution advantages, there is almost no reason for users to use it, let alone build on it and remain loyal.

 

In a public chain environment, users can interact very easily with users on other chains—it doesn’t matter which chain they join. But on a privacy chain, the user’s choice becomes crucial because once they enter a privacy chain, they are less willing to migrate and risk identity exposure. This mechanism creates a winner-takes-all (or at least winner-takes-most) dynamic. And since privacy is necessary for most real-world application scenarios, ultimately, a handful of privacy chains may control the majority of value activity in the crypto world.

 

— Ali Yahya (@alive_eth), General Partner, a16z crypto

 

2. The Key Question for Messaging Apps This Year Isn’t Just Quantum Resistance, But Decentralization

 

As the world prepares for the era of quantum computing, many messaging apps built on encryption (like Apple, Signal, WhatsApp) are already ahead and doing quite well. But the problem is, all mainstream communication tools still rely on private servers run by a single organization. And these servers are the easiest targets for governments to shut down, implant backdoors, or compel to hand over private data.

 

If a country can directly shut down the server; if a company holds the keys to the private server; or simply because a company owns the private server—then what’s the point of even the strongest quantum encryption?

 

Private servers inherently require users to “trust me”; the absence of private servers means “you don’t have to trust me.” Communication doesn’t need a single company in the middle. Messaging systems need open protocols that let us trust no one.

 

The way to achieve this is to decentralize the network entirely: no private servers, no single app, completely open-source code, and top-tier encryption—including encryption resistant to quantum threats. In an open network, no single individual, company, non-profit, or country can deprive us of the ability to communicate. Even if a country or company shuts down one app, 500 new versions will appear the next day. Even if one node is shut down, new nodes will immediately replace it—mechanisms like blockchains provide clear economic incentives.

 

When people control their messages—through private keys—just like they control their money, everything changes. Apps can come and go, but users always hold their messages and identity; even without the app itself, end-users can still own their messages.

 

This goes beyond “quantum resistance” and “encryption”; it’s about ownership and decentralization. Without either, what we’re building is an encryption system that “cannot be cracked, but can still be shut down with one click.”

— Shane Mac (@ShaneMac), Co-founder and CEO, XMTP Labs

 

3. “Secrets-as-a-Service” Will Become Core Privacy Infrastructure

 

Behind every model, agent, and automated system lies a fundamental dependency: data. But most current data pipelines—whether data fed into models or data output by models—are opaque, mutable, and unauditable.

 

This might be acceptable for some consumer applications, but in industries like finance and healthcare, users and institutions often have strong privacy requirements. This is also becoming a major obstacle for institutions currently advancing the tokenization of real-world assets.

 

So, how do we enable secure, compliant, autonomous, and globally interoperable innovation while protecting privacy?

There are many solution paths, but I want to focus on data access control: Who controls sensitive data? How does data flow? And who (or what system) can access this data under what conditions?

 

In the absence of data access control, any entity wishing to maintain data confidentiality currently must rely on centralized services or build custom systems themselves—which is time-consuming, expensive, and severely hinders entities like traditional financial institutions from fully unlocking the potential of on-chain data management. And as autonomous agent systems begin to browse, trade, and make decisions independently, users and institutions across industries need cryptographic-level deterministic guarantees, not “best-effort trust.”

 

This is precisely why I believe we need “secrets-as-a-service”: A new type of technical architecture that provides programmable, native data access rules; client-side encryption; and decentralized key management mechanisms that enforce on-chain “who can decrypt what data, under what conditions, and for how long.”

 

When these mechanisms are combined with verifiable data systems, “secrets” themselves can become part of the internet’s foundational public infrastructure, no longer just an afterthought patched onto the application layer—making privacy truly underlying infrastructure.

 

— Adeniyi Abiodun (@EmanAbio), Co-founder and Chief Product Officer, Mysten Labs

 

4. Security Testing Will Evolve from “Code Is Law” to “Specification Is Law”

 

The multiple DeFi hacks last year did not target new projects, but rather protocols with established teams, multiple rounds of audits, and years of operation. These incidents highlight a troubling reality: Current mainstream security practices still heavily rely on rules of thumb and case-by-case judgment.

 

To achieve true maturity this year, DeFi security must shift from “vulnerability pattern recognition” to “design-level property guarantees,” and from “best-effort” to “principled methodology”:

 

In the static / pre-deployment phase (testing, auditing, formal verification), this means no longer verifying only a few selected local properties, but systematically proving global invariants. Currently, multiple teams are building AI-assisted proof tools that can help write specifications, propose invariant hypotheses, and take on the historically extremely expensive manual proof engineering work.

In the dynamic / post-deployment phase (runtime monitoring, runtime constraints, etc.), these invariants can be transformed into real-time guardrails, serving as a last line of defense. These guardrails will be directly encoded as runtime assertions that every transaction must satisfy.

 

This way, we no longer assume “all vulnerabilities have been found,” but instead enforce critical security properties at the code level, with any transaction violating these properties being automatically rolled back.

 

This is not just theoretical. In fact, almost all attacks to date would have triggered one of these checks during execution, potentially directly aborting the attack. Therefore, the once-popular “code is law” philosophy is evolving into “specification is law”: even novel attack vectors must satisfy the security properties that maintain system integrity, and the final viable attack surface is compressed to a very small or extremely difficult-to-execute space.

 

— Daejun Park (@daejunpark), Engineering Team, a16z

 

Read the original text

 

Read More:

Why Gold Is Surging: Central Banks, Sanctions, and Trust-1

Bitwise: Why Crypto Is Moving Beyond the Four-Year Cycle-2

〈Zcash is Just the Beginning, How Will a16z Redefine the Privacy Narrative in 2026?〉這篇文章最早發佈於《CoinRank》。

Market cap in crypto is calculated as price multiplied by circulating supply, providing a standardized way to compare cryptocurrencies beyond misleading unit prices.

 

Understanding market cap helps investors assess relative size, liquidity, volatility, and risk, while avoiding common misconceptions such as equating low price with undervaluation.

 

Market cap is a foundational but incomplete metric, best used alongside supply dynamics, liquidity, and fundamentals for long-term crypto investment strategies.

What does market cap mean in crypto explains how market capitalization works, why it matters for valuation, risk, and liquidity, and how investors can use it to make more informed crypto investment decisions.

 

Introduction: Understanding what does market cap mean in crypto

 

What does market cap mean in crypto is one of the most frequently asked questions by beginners entering the cryptocurrency market, yet it is also one of the most misunderstood concepts among retail investors. Market capitalization, commonly shortened to market cap, is often treated as a simple ranking metric, but in reality it carries deeper implications about valuation, liquidity, risk perception, and market structure. In crypto, where thousands of digital assets coexist with vastly different supply models and use cases, understanding what does market cap mean in crypto is essential for making informed decisions.

 

At its most basic level, market cap represents the total value of a cryptocurrency’s circulating supply multiplied by its current price. While this definition appears straightforward, its interpretation in crypto markets differs significantly from traditional equities. Crypto assets trade continuously, have transparent on-chain supply data, and often experience extreme volatility. As a result, market cap in crypto is not just a snapshot of value, but a reflection of collective market expectations at a specific moment in time.

 

Many investors mistakenly assume that a low price means a coin is “cheap” or that a high price means it is “expensive.” This misconception arises from ignoring market cap entirely. Understanding what does market cap mean in crypto helps investors avoid these pitfalls by focusing on overall valuation rather than unit price. Whether evaluating Bitcoin, Ethereum, or emerging altcoins, market cap provides a standardized lens for comparison.

 

In this guide, we will explore what does market cap mean in crypto from multiple perspectives, including how it is calculated, how it differs from traditional finance, why it matters for investment decisions, and what its limitations are. By the end, you will have a structured, practical understanding of market cap as a core analytical tool in crypto markets.

 

Figure 1: Top Market Cap Coins

 

How market cap is calculated in crypto markets

 

The basic formula behind crypto market capitalization

 

 

To understand what does market cap mean in crypto, it is essential to start with the calculation itself. The formula is simple:

 

Market Cap = Current Price × Circulating Supply

 

In crypto markets, circulating supply refers to the number of coins or tokens that are currently available and tradable on the market. This excludes locked tokens, unmined coins, or assets held in long-term vesting contracts. Because blockchain data is transparent, circulating supply figures are often more visible than in traditional markets, although interpretation can still vary by data provider.

 

This formula allows investors to compare cryptocurrencies with vastly different price levels. For example, a token priced at $0.10 with a large supply may have a higher market cap than a token priced at $1,000 with a much smaller supply. Understanding what does market cap mean in crypto prevents investors from equating low price with undervaluation or high price with overvaluation.

 

Another important nuance is that crypto prices can change rapidly, causing market cap to fluctuate significantly within short periods. Unlike stock markets with fixed trading hours, crypto markets operate 24/7. As a result, market cap is a dynamic metric that reflects real-time market sentiment rather than a static valuation.

 

Circulating supply vs total supply vs fully diluted value

 

When analyzing what does market cap mean in crypto, investors must distinguish between circulating supply and total or maximum supply. Circulating supply is used in market cap calculations, but many projects have additional tokens scheduled for future release. This introduces the concept of fully diluted valuation (FDV), which estimates market cap if all tokens were in circulation.

 

FDV can provide insight into potential future dilution, but it should not be confused with current market cap. A project may appear small based on market cap but carry significant inflation risk if a large portion of its supply has yet to enter circulation. Understanding these distinctions is critical for interpreting what does market cap mean in crypto beyond surface-level rankings.

 

Why market cap matters for crypto investors

 

Market cap as a tool for comparing cryptocurrencies

 

 

One of the primary reasons investors care about what does market cap mean in crypto is its role as a comparative metric. Market cap allows investors to assess the relative size of different cryptocurrencies regardless of their individual token prices. This is especially important in a market where token denominations vary widely.

 

For example, Bitcoin and Ethereum dominate the market by market cap, reflecting their established networks, liquidity, and adoption. Smaller market cap assets, often referred to as mid-cap or small-cap coins, may offer higher growth potential but also carry greater risk. By understanding market cap categories, investors can align their portfolios with their risk tolerance and investment horizon.

 

Market cap also influences market perception. Assets with higher market caps are generally perceived as more stable and less susceptible to manipulation, while low market cap assets can experience dramatic price swings from relatively small capital inflows. Understanding what does market cap mean in crypto helps investors contextualize volatility rather than reacting emotionally to price movements.

 

Liquidity, risk, and market cap dynamics

 

Market cap is closely linked to liquidity, although the two are not identical. Higher market cap cryptocurrencies tend to have deeper order books, higher trading volumes, and more active markets. This reduces slippage and allows investors to enter or exit positions more efficiently.

 

However, market cap alone does not guarantee liquidity. Some assets may have inflated market caps due to thin trading or concentrated ownership. Therefore, understanding what does market cap mean in crypto requires combining it with other metrics such as volume, distribution, and on-chain activity.

 

From a risk perspective, market cap can act as a proxy for maturity. Large-cap cryptocurrencies are often considered lower risk relative to small-cap assets, but they may also offer lower upside potential. Smaller market cap projects may deliver outsized returns but carry higher probabilities of failure. Market cap thus becomes a foundational tool for portfolio construction and risk management.

 

Common misconceptions about market cap in crypto

 

Why a low token price does not mean a crypto is undervalued

 

One of the most persistent misunderstandings around what does market cap mean in crypto is the belief that a low-priced token is inherently undervalued. This misconception ignores the role of supply. A token with billions of units in circulation can have a low unit price while still carrying a high market cap.

 

This misunderstanding often leads investors to chase “cheap” coins without considering total valuation. Market cap corrects this bias by shifting focus from unit price to aggregate value. Understanding what does market cap mean in crypto helps investors avoid narratives driven by psychological price anchors rather than fundamentals.

 

Another related misconception is assuming that a coin can easily reach the price level of another asset without accounting for market cap implications. For example, expecting a low-cap token to reach the same price as Bitcoin often implies an unrealistic total valuation. Market cap analysis grounds expectations in mathematical reality.

 

Market cap manipulation and its limitations

 

While market cap is useful, it is not immune to manipulation. In crypto markets, low liquidity assets can experience sharp price increases from relatively small trades, temporarily inflating market cap. This can create misleading impressions of value or adoption.

 

Therefore, understanding what does market cap mean in crypto also involves recognizing its limitations. Market cap reflects price multiplied by supply, not necessarily real capital invested or sustainable value. Investors should treat market cap as a starting point for analysis rather than a definitive measure of worth.

 

Featured Table: Market Cap Categories in Crypto

 

 

what does market cap mean in crypto for long-term strategy

 

Understanding what does market cap mean in crypto is especially important for long-term investors. Market cap influences how much capital is required to move an asset’s price and shapes expectations around growth potential. Large-cap assets may grow steadily as adoption increases, while smaller-cap assets may experience exponential growth or collapse entirely.

 

For long-term strategies, market cap should be evaluated alongside fundamentals such as network usage, developer activity, token economics, and regulatory positioning. Market cap alone does not determine success, but it provides context for interpreting these factors. Investors who understand what does market cap mean in crypto are better equipped to build balanced portfolios and avoid speculative traps.

 

Market cap also evolves over time. Assets can move between categories as networks grow or decline. Tracking market cap trends rather than static rankings allows investors to identify emerging leaders and fading projects. In this sense, market cap is both a snapshot and a narrative tool that reflects the evolving structure of the crypto market.

 

Conclusion: what does market cap mean in crypto as an investment framework

 

What does market cap mean in crypto is not simply a definition, but a framework for understanding value, risk, and market behavior in digital asset markets. Market cap provides a standardized way to compare cryptocurrencies, cut through misleading price narratives, and anchor expectations in economic reality. It helps investors distinguish between perceived affordability and actual valuation, and between speculative excitement and structural growth.

 

At the same time, market cap should never be used in isolation. It is most powerful when combined with liquidity metrics, supply dynamics, and fundamental analysis. Understanding what does market cap mean in crypto allows investors to contextualize volatility, assess risk more accurately, and construct portfolios aligned with their long-term goals.

 

As crypto markets continue to mature, market cap will remain one of the most widely referenced metrics. However, its true value lies not in rankings alone, but in the insight it provides into how markets collectively price belief, utility, and future potential. For anyone serious about navigating crypto markets, mastering what does market cap mean in crypto is a foundational step toward informed and disciplined investing.

〈what does market cap mean in crypto: A Complete Guide for Beginners and Investors〉這篇文章最早發佈於《CoinRank》。

DePINSim represents a shift in DePIN design from hardware deployment to software defined connectivity, using eSIM and protocol coordination to scale global access without building new physical infrastructure.

 

By combining decentralized connectivity with an agent based simulation engine, DePINSim addresses one of the biggest historical risks in DePIN and GameFi projects: poorly tested token economics that fail under real demand conditions.

 

DePINSim positions itself between Web2 eSIM providers and hardware based DePIN networks, trading full infrastructure sovereignty for faster expansion, lower user friction, and a globally scalable incentive model.

For decades, global mobile connectivity has followed the same logic. Physical infrastructure comes first. Regulation follows. Users pay the cost.

 

Mobile network operators invest billions in spectrum and base stations. Coverage expands slowly. International roaming remains expensive and opaque. Identity and usage data stay under operator control. Innovation happens at the edge, not at the core.

 

Decentralized Physical Infrastructure Networks, or DePIN, emerged as an attempt to break this structure. Early projects focused on ownership. If users owned the hardware, they could also own the network.

 

The results were mixed.

 

Hardware based DePIN networks struggled with cold start problems, uneven coverage, and high capital requirements. Growth depended on shipping devices, not software adoption. Incentives worked, but scalability lagged.

 

 

DePINSim enters the sector with a different assumption. Infrastructure does not have to be rebuilt to be decentralized. It can be abstracted.

 

Instead of deploying new towers or routers, DePINSim treats existing mobile networks as a substrate and focuses on coordination, incentives, and settlement at the software layer. This shift defines its entire strategy.

 

FROM HARDWARE FIRST TO SOFTWARE DEFINED DEPIN

 

The first generation of decentralized wireless networks tied participation to physical deployment. Users bought devices, installed them, and earned rewards for coverage. This model aligned incentives, but it also limited reach.

 

Hardware is expensive. Distribution is slow. Coverage clusters in urban areas while rural gaps remain. Most importantly, network growth depends on logistics rather than demand.

 

DePINSim moves away from this constraint by building around eSIM technology.

 

Any smartphone that supports eSIM can become a network participant. There is no dedicated device. No upfront hardware cost. No shipping delay. The existing global base of mobile phones becomes the potential infrastructure layer.

 

This choice changes the economics of participation. Joining the network becomes a software action, not a capital decision. Scale depends on downloads and usage, not manufacturing capacity.

 

The project positions itself as a decentralized mobile virtual network operator, but the label understates the ambition. DePINSim is not only reselling connectivity. It is redefining how connectivity is measured, rewarded, and settled in a decentralized context.

 

FMIP AND THE ARCHITECTURE OF DECENTRALIZED ROAMING

 

At the core of DePINSim sits the Free Mobile Internet Protocol, or FMIP. It is designed to abstract the complexity of traditional telecom systems and expose connectivity as a programmable service.

 

FMIP is structured across three layers.

 

The first is the mining layer, which runs directly on user devices. Mining in this context does not mean cryptographic hashing. It refers to verifying real network conditions. Signal strength, latency, throughput, and handover success are continuously measured. These metrics form a proof of connection that represents actual network contribution.

 

The second is the network layer, which handles routing and roaming. FMIP maintains a global pool of eSIM profiles sourced from licensed operators. When a user changes location, the protocol dynamically selects the most efficient local carrier profile. Data no longer routes back to a home network, reducing latency and cost.

 

The third is the value layer, where blockchain infrastructure handles settlement, incentives, and identity. Payments, rewards, and staking logic operate onchain, while sensitive usage data remains abstracted.

 

This layered design allows DePINSim to decentralize coordination without rebuilding physical networks. It also avoids direct confrontation with spectrum regulation, since the protocol works through compliant wholesale partners.

 

The result is a system where global roaming behaves like a software service rather than a negotiated exception.

 

CONNECTION AS VALUE AND THE ROLE OF SIMULATION

 

The name DePINSim carries a second meaning. Beyond SIM cards, it refers to simulation.

 

One of the recurring failures in token driven infrastructure projects has been economic fragility. Incentives attract users quickly, but collapse once emissions outweigh real demand. Many projects discover this only after launch.

 

DePINSim attempts to address this upfront by embedding an agent based simulation engine into its platform.

 

The simulation models different participant types. Providers decide whether to stay online based on expected rewards versus data costs. Users generate demand across multiple behavioral curves, ranging from steady usage to hype driven spikes. The protocol adjusts parameters such as emissions, pricing, and burn rates.

 

These simulations allow stress testing before changes are deployed. Developers can observe how the system behaves under growth, decay, or volatility scenarios. This does not guarantee success, but it reduces blind risk.

 

Strategically, this tool positions DePINSim as more than a consumer product. It becomes a modeling platform for DePIN economics. Other projects can use the simulation framework to design and test their own incentive structures.

 

This dual role, operator and simulator, is unusual in the sector and may become one of the project’s strongest differentiators.

 

TOKEN DESIGN AND ECONOMIC ALIGNMENT

 

DePINSim uses a dual asset structure to separate user experience from market volatility.

 

The ESIM token functions as the network’s utility and governance asset. It is used for staking, rewards, and protocol level settlement. A secondary internal unit represents mined connectivity value and is used for service consumption.

 

This structure mirrors approaches used in other DePIN networks. The goal is to shield everyday users from price swings while still allowing the protocol to capture value from usage.

 

The economic core follows a burn and mint equilibrium model. When users purchase data services, part of the revenue is used to buy and burn ESIM tokens. At the same time, new tokens are minted to reward verified network contribution.

 

In theory, usage growth offsets emissions. In practice, sustainability depends on real demand.

 

Early data shows strong engagement and high transaction volume, but also significant volatility. This is expected in early phases, especially with aggressive airdrop strategies and active market making.

 

The critical metric moving forward is not price, but burn rate. If service usage grows faster than token issuance, the model tightens. If not, incentives weaken.

 

COMPETITION AND STRATEGIC POSITIONING

 

DePINSim sits between two competitive fronts.

 

On one side are traditional eSIM providers. They offer simplicity and reliability, but no ownership or upside for users. Consumption is purely a cost.

 

On the other side are hardware based DePIN networks. They offer ownership and rewards, but require physical deployment and operate with geographic limits.

 

DePINSim chooses a middle path. It offers global coverage through existing networks, while layering incentives and ownership through crypto primitives.

 

This creates asymmetrical competition. Against Web2 providers, DePINSim competes on economics and community. Against hardware based DePINs, it competes on speed and scalability.

 

The tradeoff is dependency. DePINSim does not control base stations. It relies on wholesale agreements and regulatory tolerance. This limits sovereignty but accelerates expansion.

 

Whether this balance holds depends on execution and regulatory navigation.

 

THE BET AHEAD

 

DePINSim is ultimately making a bet on abstraction.

 

It assumes that decentralization does not require replacing physical infrastructure. It requires redefining how infrastructure is accessed, measured, and rewarded.

 

If connectivity can be treated as a software defined resource, then global networks can scale through coordination rather than construction.

 

The challenge is durability. Incentives must outlast speculation. Regulation must be navigated without compromise. Real users must value the service beyond rewards.

 

If DePINSim succeeds, it offers a template for a new class of DePIN projects. Lightweight, software driven, and economically modeled before deployment.

 

If it fails, it will still leave behind an important lesson. Infrastructure decentralization is not only about who owns the hardware. It is about who controls the rules.

〈DePINSim and the Shift Toward Software Defined Connectivity〉這篇文章最早發佈於《CoinRank》。

Brevis Network reframes blockchain scalability by separating execution from verification, allowing smart contracts to rely on complex offchain computation while preserving onchain trust through zero knowledge proofs.

 

By combining a hybrid zkVM architecture with a decentralized proving marketplace, Brevis turns proof generation into an open, market driven infrastructure rather than a closed or centralized service.

 

Brevis enables a new class of data driven onchain applications, from behavior based DeFi logic and trust minimized crosschain security to verifiable AI outputs that balance correctness and privacy.

Smart contracts have always had a structural weakness. They are good at the present, but bad at memory.

 

On most blockchains, contracts can read current state with little friction. The moment they need to reason about history, costs rise sharply. Checking long term user behavior, aggregating activity across months, or referencing past states from other chains quickly becomes impractical.

 

Developers adapted by moving computation offchain. Indexers, servers, and private databases filled the gap. Results were pushed back onchain, and most users accepted the trust assumptions behind them.

 

Brevis Network enters with a different approach. Heavy computation does not need to live onchain, but trust still must. Zero knowledge proofs make this separation possible. Instead of re executing work, the chain verifies that the work was done correctly.

 

This is not a small optimization. It changes what blockchains are designed to do.

 

FROM RE EXECUTION TO VERIFIABLE COMPUTE

 

Blockchain security has long depended on repetition. Every node re executes every transaction. This redundancy creates trust, but it also imposes hard limits.

 

 

As applications mature, those limits become more visible. DeFi products no longer only move assets. They price risk, adjust parameters, and react to behavior over time. These functions depend on historical data and complex computation.

 

Onchain execution struggles with this load. Offchain execution introduces trust.

 

Brevis proposes a third path. Computation happens offchain. Verification stays onchain. Zero knowledge proofs connect the two.

 

In this model, the blockchain focuses on consensus and finality. External systems handle data intensive work. Contracts receive results together with proofs they can verify cheaply.

 

Brevis refers to this as an infinite compute layer. The phrase does not suggest unlimited resources. It describes a system where application complexity no longer scales directly with chain congestion.

 

Developers stop asking what fits onchain. They start asking what can be proven.

 

WHY HISTORICAL DATA MATTERS MORE THAN THROUGHPUT

 

Throughput is easy to measure. Utility is harder.

 

Many applications care less about how many transactions a chain processes per second and more about what those transactions reveal over time. Risk engines depend on behavior. Markets depend on participation patterns. Governance depends on activity history.

 

Smart contracts do not handle these needs well. Storing large datasets onchain is expensive. Processing them repeatedly is worse.

 

As a result, most protocols rely on offchain pipelines. Data is collected elsewhere, processed privately, and reflected onchain through trusted updates.

 

Brevis changes this workflow.

 

A developer submits a query through the Brevis system. Relevant blockchain data is retrieved and verified against the canonical chain. The requested computation runs offchain. A proof is generated and sent back to the contract.

 

The contract never sees raw data. It only verifies the proof and accepts the result.

 

 

This makes historical data usable again, without reintroducing centralized trust.

 

THE ROLE OF PICO zkVM IN MAKING PROOFS PRACTICAL

 

Verifiable compute only works if proofs are fast enough to sit in real user flows.

 

Brevis built Pico zkVM with this constraint in mind. Instead of relying on a purely general virtual machine, it uses a hybrid design. General logic runs in the zkVM. Heavy operations move to specialized coprocessors.

 

This approach keeps development flexible while lowering proving cost. Expensive primitives no longer dominate performance.

 

The result is a system optimized for production workloads rather than theoretical purity.

 

In testing focused on Ethereum block proving, Brevis demonstrated proof generation within real time constraints. This matters because latency determines relevance. If proofs arrive too late, applications cannot depend on them.

 

Brevis also treats proving as a distributed problem. Pico Prism supports cluster level proving, allowing workloads to scale horizontally instead of depending on single machine performance.

 

This design aligns with how proving will operate at infrastructure scale.

 

PROVERNET AND THE ECONOMICS OF PROOF GENERATION

 

Even the best proving system fails if supply is fragile.

 

If applications depend on a single prover, they inherit downtime risk and unpredictable pricing. Brevis addresses this with ProverNet, a decentralized proving marketplace.

 

Applications submit proving tasks with budget and latency preferences. Provers submit offers based on cost and capacity. The network matches supply and demand dynamically.

 

Not all proofs are equal. Some require low latency. Others prioritize cost efficiency. ProverNet allows provers to specialize instead of forcing uniform performance.

 

The system uses a market design that rewards honest pricing. Participants benefit from reporting real costs rather than gaming the system. This helps maintain long term stability.

 

BREV underpins this economy. Applications pay fees in the token. Provers stake it to participate. Failure to deliver valid proofs leads to penalties.

 

This creates a direct link between usage and value. It also introduces accountability at the infrastructure level.

 

Hardware concentration remains a challenge. High performance proving requires capital investment. Whether ProverNet can broaden participation without losing reliability will be a key test.

 

WHAT BREVIS ENABLES ACROSS APPLICATIONS

 

Brevis matters when it changes how applications behave.

 

In DeFi, it enables behavior based logic. Protocols can adjust fees or rewards using provable user history. Loyalty systems become verifiable rather than discretionary.

 

In crosschain systems, Brevis supports trust minimized state verification. Assets do not need to move across bridges. Only state proofs do. This reduces risk while preserving interoperability.

 

In AI driven workflows, Brevis enables verifiable outputs. Models can produce results that contracts can trust without exposing sensitive inputs. This supports reputation systems and automated decision making.

 

Across these use cases, the pattern remains consistent. Compute offchain. Verify onchain.

 

THE STRATEGIC BET AHEAD

 

Brevis is not competing on narrative. It is competing on necessity.

 

Its success depends on whether verifiable compute becomes a default expectation rather than a specialized feature. If applications embed proofs into normal flows, Brevis occupies a critical position in the stack.

 

The roadmap focuses on migrating real traffic into ProverNet, expanding proving capacity, and reducing coordination costs through dedicated execution layers.

 

If this works, blockchains stop trying to compute everything themselves.

 

They become systems that verify the work of an external compute economy.

 

That is the future Brevis is building toward.

〈Why Brevis Network Matters in a World That Needs Verifiable Compute〉這篇文章最早發佈於《CoinRank》。

#Telegram founder Pavel Durov stated in a post that despite recent #FUD , Telegram has no capital ties to Russia. He emphasized that there were absolutely no Russian investors involved in its recent $1.7 billion bond issuance. The older bonds issued in 2021 have largely been repaid and do not pose any issues.
He also stressed that bondholders are not shareholders, and that he remains Telegram’s sole shareholder.
#CryptoNews

Since December 17, 2025, large Bitcoin holder cohorts have increased balances by more than 56,000 BTC, while smaller retail wallets have shown net distribution.

 

This divergence suggests an ownership rebalancing process, with supply moving toward holders with longer time horizons and greater liquidity capacity.

 

While methodology varies across data providers, the trend highlights a possible shift from retail-driven volatility toward more institutionally influenced market structure.

On-chain data shows large Bitcoin holders accumulating while retail wallets reduce exposure, signaling a potential structural shift in Bitcoin ownership toward longer-term, institution-aligned holders.

 

Large Holders Are Buying While Retail Takes Profit

 

On January 7, 2026, on-chain data highlighted a sharp behavioral split in Bitcoin ownership: wallets labeled “whales and sharks” (commonly defined as addresses holding 10 to 10,000 BTC) increased their collective holdings by 56,227 BTC since December 17, 2025, while small retail wallets (often proxied as <0.01 BTC) reduced exposure and took profits.

 

This matters because it frames Bitcoin’s current market not as a simple price-driven cycle, but as an ownership rebalancing process in which large holders are willing to absorb supply during consolidation, even when broader sentiment is mixed and smaller cohorts are de-risking.

 

 

Why This Pattern Is Treated as a Market-Structure Signal

 

The “whales accumulate as retail sells” setup is often treated as a market-structure signal because it implies that marginal supply is increasingly being held by entities with longer time horizons, deeper liquidity buffers, and less sensitivity to short-term volatility, which can reshape how Bitcoin behaves during drawdowns and breakouts.

 

A late-December Glassnode-based view reported that large holders (e.g., 1,000–10,000 BTC cohorts) were among the primary accumulators around the $80,000 price region, reinforcing the idea that, at least during that window, bigger balance sheets were acting as a stabilizing bid rather than a source of forced selling.

 

The Macro Implication: Bitcoin Ownership Keeps Institutionalizing

 

If this accumulation trend persists, the macro implication is straightforward: Bitcoin’s ownership base continues to institutionalize—not only through regulated products like ETFs, but also through large-holder balance growth that concentrates supply in fewer hands, often associated with funds, treasury allocators, high-net-worth entities, and custodial structures.

 

In practical market terms, that kind of concentration can reduce “weak hand” supply in the short run, but it can also increase the market’s sensitivity to what large holders decide to do at key levels, meaning volatility can shift from retail-driven noise to institution-driven repositioning.

 

A Critical Caveat: “Whale Accumulation” Can Be Misread

 

Because “whale balances” are derived from address clustering heuristics, exchange wallet movements, and cohort definitions that differ across data vendors, headline accumulation numbers can sometimes be overstated or misinterpreted—especially when exchange-related flows distort who “really” owns coins.

 

A recent CryptoQuant-cited rebuttal argued that once exchange-related distortions are filtered out, large holders may still be distributing rather than accumulating, and that overall whale balances can continue to trend down depending on methodology and cohort selection.

 

The editorial takeaway is not that one side is definitively “right,” but that the most rigorous interpretation treats the 56,227 BTC figure as a cohort-based signal from a specific data definition (Santiment’s whale/shark cohorts) rather than an absolute statement about every large holder in the system.

 

What To Watch Next

 

If you want to validate whether this is truly a structural shift (and not a measurement artifact), the cleanest next indicators are: whether large-holder cohorts keep trending up across multiple vendors, whether exchange balances continue to fall (supporting the idea of net accumulation), and whether retail-sized cohorts keep distributing during sideways price action, which historically tends to happen when risk appetite is returning unevenly rather than uniformly.

 

For now, the most defensible, data-grounded conclusion is narrow but important: since December 17, 2025, one widely referenced cohort definition shows a material net increase in large-holder balances, occurring alongside retail profit-taking, which is exactly the kind of divergence that often appears during ownership transitions rather than late-stage speculative blow-offs. 

 

Read More:

Morgan Stanley’s Bitcoin and Solana ETF Filings Signal a New Institutional Phase

〈Whale Accumulation Signals a Structural Shift in Bitcoin Ownership〉這篇文章最早發佈於《CoinRank》。

Morgan Stanley has filed Bitcoin and Solana ETF applications, moving from distribution-based crypto exposure to direct issuance of regulated digital asset products.

 

The inclusion of Solana alongside Bitcoin suggests institutions are beginning to explore diversified crypto exposure within compliant investment frameworks.

 

The filings reflect growing regulatory confidence and signal a structural shift as crypto assets become embedded in mainstream asset management infrastructure.

Morgan Stanley’s filing for Bitcoin and Solana ETFs marks a shift from indirect access to direct product issuance, signaling a deeper phase of institutional integration in crypto markets.

 

WALL STREET MOVES FROM ACCESS TO OWNERSHIP IN CRYPTO MARKETS

 

On January 6, 2026, Morgan Stanley filed applications with the U.S. Securities and Exchange Commission for both a Bitcoin exchange-traded fund and a Solana-linked ETF, marking a notable escalation in Wall Street’s engagement with digital assets. Unlike earlier institutional participation focused on brokerage access or custodial services, this move positions a major U.S. investment bank directly within the crypto asset management landscape.

According to Reuters, the filings represent Morgan Stanley’s first attempt to sponsor crypto ETFs, following a year in which spot Bitcoin ETFs attracted tens of billions of dollars in inflows across U.S. markets. The inclusion of Solana alongside Bitcoin further signals that institutional interest is beginning to extend beyond a single flagship asset.

 

 

FROM DISTRIBUTION CHANNELS TO PRODUCT ISSUANCE

 

For much of the past cycle, large banks approached crypto cautiously, offering limited exposure through wealth-management channels or third-party funds. Morgan Stanley’s ETF filings indicate a shift from distribution-only participation toward direct product issuance, where banks assume responsibility for structuring, compliance, and long-term investor alignment.

 

This transition matters because ETF sponsorship places institutions at the center of regulatory accountability. Unlike trading access or advisory exposure, ETF products must operate continuously within securities law frameworks, subject to disclosure standards, custody requirements, and ongoing oversight. In this context, Morgan Stanley’s move suggests growing confidence that crypto assets can be managed within established regulatory boundaries.

 

WHY SOLANA MATTERS ALONGSIDE BITCOIN

 

While Bitcoin remains the dominant institutional crypto asset, the decision to pursue a Solana-linked ETF carries broader implications. Solana represents a different risk and utility profile, tied more closely to smart-contract activity, decentralized applications, and ecosystem throughput rather than purely monetary characteristics.

 

By pairing Bitcoin and Solana in its ETF strategy, Morgan Stanley appears to be testing whether regulated capital markets are ready to absorb diversified crypto exposure, rather than treating digital assets as a single-asset category. This could mark an early step toward tiered institutional portfolios that distinguish between settlement assets and application-driven networks.

 

REGULATORY SIGNALS AND MARKET STRUCTURE

 

The timing of the filings is notable. After the approval of spot Bitcoin ETFs, regulatory dialogue has shifted from whether crypto belongs in regulated markets to how far that integration can extend. ETF filings from a global bank reinforce the perception that crypto regulation in the United States is moving from exception-based approvals toward repeatable frameworks.

 

If approved, Morgan Stanley’s products would further normalize crypto ETFs as standard portfolio instruments, reducing reliance on offshore venues and unregulated intermediaries. Over time, this could concentrate liquidity within regulated channels, reshaping market structure in favor of institutions capable of meeting compliance and reporting expectations.

 

FROM EXPERIMENT TO INFRASTRUCTURE

 

Viewed in isolation, an ETF filing may appear incremental. Viewed in context, Morgan Stanley’s entry reflects a deeper structural transition: crypto exposure is no longer confined to specialist firms or early adopters, but is being absorbed into the core machinery of global asset management.

 

As major banks move from offering access to issuing products, the crypto market increasingly resembles other institutional asset classes, governed less by narrative momentum and more by regulatory clarity, product design, and capital allocation discipline. Whether this shift ultimately broadens market participation or narrows it around regulated incumbents will shape the next phase of crypto’s evolution.

 

Read More:

JPMorgan MONY: institutional cash goes on-chain

JPMorgan Opens Crypto Collateral Era with Bitcoin and Ethereum

〈Morgan Stanley’s Bitcoin and Solana ETF Filings Signal a New Institutional Phase〉這篇文章最早發佈於《CoinRank》。

Analysts: Three wallets suspected of insider trading during #Infinex public offering
#Bitcoin Core v30 has a vulnerability: Upgrading older wallets may result in financial losses
#GoPlus : Beware of fake Ponzi schemes and Pixiu tokens with the same name as $114514
Morgan Stanley submits S-1 filings for the Solana Trust and Bitcoin Trust to the US #SEC
#Coinbase Research Head: Wallets holding approximately one-third of the Bitcoin supply are vulnerable to quantum attacks