Still Some Time To Go Till The Bears Retreat

Bitcoin’s bear market may still have a year or more to run, according to Cryptoquant founder and chief executive Ki Young Ju, who spelled out the timeline in a post on X. “Once profit-taking cascades, Bitcoin investors’ PnL typically falls for about 18 months.” Ju wrote, using shorthand for aggregate investor profit and loss (PnL). “Since the trend turned in Oct 2025, the bear market could last until early 2027.”

His reasoning hinges on the direction of realized profits. Put simply, holders are still sitting on paper gains they are steadily cashing in, a dynamic that historically keeps pressure on price until that selling burns itself out. The PnL index he relies on blends several onchain valuation gauges (including the market-value-to-realized-value (MVRV) ratio and net unrealized profit and loss) into a single trend line that peaked around mid-2025 and has been sliding since.

The warning extends a position Ju has pressed for much of the past year, as he first declared bitcoin’s bull cycle over in 2025, citing a widening gap between the asset’s realized capitalization and its market capitalization.

Not Everyone, Including Cryptoquant’s Own Data, Agrees

The bleak timeline is far from settled even inside Ju’s own firm, as Cryptoquant’s Bull-Bear Cycle Indicator turned green on May 12 for the first time since March 2023, a signal that has historically coincided with the start of more constructive conditions.

Other analysts are more bullish still, with research firm K33 contending bitcoin’s roughly $60,000 February low already marked the maximum drawdown of this cycle (a decline of about 52% from the record $126,272 the asset printed on Oct. 6, 2025).

The split reveals a murky mid-cycle picture, because if Ju is right, traders face another grinding stretch before realized profits reset, and the next leg higher can begin. If the greening cycle indicator and steady ETF inflows win out, the bottom may already be in.

Either way, Ju has handed the market a clear tripwire to watch wherein the moment unrealized profits start climbing while realized profits fade, the 18-month clock he describes would finally be ready to flip.

This week, the industry produced another wave of evidence that the technology itself is working as advertised.

Project Agora, the Bank for International Settlements (BIS) initiative involving seven central banks and more than 40 private-sector financial institutions, successfully tested blockchain-based cross-border settlement flows. SoFi became the first national bank to issue a stablecoin on a public blockchain. Circle expanded its payout infrastructure through a partnership with Nium, while Mastercard secured a New York cryptocurrency license that broadens its stablecoin-related capabilities, and Cash App rolled out support for stablecoin payments.

But the digital dollar industry is now approaching a more difficult phase of development where success will be measured not by how quickly stablecoins move between wallets but by whether businesses and consumers can use those assets in the real economy without introducing new friction, cost or complexity.

The first challenge was proving that value can move on chain. The next challenge is figuring out how that value becomes economically useful once it moves off chain.

See also: Stablecoins Target B2B Settlement as Marketplaces Scale 

Interoperability Is More Important Than Issuance

The stablecoin market spent years focused on issuance scale. Tether and Circle competed for circulation dominance. New entrants launched chain-specific coins designed to drive ecosystem growth. But fragmentation is now becoming a structural challenge.

Stablecoins exist across multiple public blockchains, private ledgers, Layer 2 networks and emerging tokenized deposit systems. Financial institutions are simultaneously experimenting with permissioned blockchain environments while FinTechs continue building on open public chains.

But a payment system only becomes economically powerful when participants can transact across networks without introducing new operational complexity. If businesses must manage liquidity across multiple chains, maintain separate compliance processes or navigate inconsistent standards, the efficiency gains of blockchain settlement begin to erode. The future payments ecosystem is unlikely to converge around a single blockchain or a single stablecoin issuer. More likely, it will consist of multiple interoperable systems that require governance standards, messaging frameworks, compliance coordination and liquidity routing mechanisms.

“I think we go to a world built on digital network transfers of value rather than the message-based system we have today. The future of digital networks is going to be a multi-network world,” J. Christopher Giancarlo, former Commodity Futures Trading Commission (CFTC) chair and co-founder of the Digital Dollar Project, told PYMNTS on the latest episode of “From the Block.”

Project Agora’s significance lies partly in its recognition of this issue. The initiative explores how central bank money and commercial bank tokenization models can interact within shared programmable infrastructures rather than isolated silos.

See more: Fed Report Shows Crypto Still Has an Everyday Use Problem

Off-Ramps Are Becoming Stablecoins’ Biggest Adoption Bottleneck

The stablecoin ecosystem increasingly resembles a high-speed highway system that feeds into underdeveloped local roads. On-chain transfers may settle instantly, but businesses and consumers still operate inside local banking systems, regulatory frameworks, tax regimes, treasury processes and compliance structures that were not designed for tokenized money.

The result is that the “last mile” of stablecoin adoption often introduces many of the same frictions blockchain was supposed to eliminate. Findings in the March PYMNTS Intelligence report “Stablecoins Gain Ground: Why CFOs See More Promise There Than in Crypto” revealed that while 42% of middle-market companies have at least discussed stablecoins, only 13% have reported actual stablecoin use.

This is why partnerships like Circle’s integration with Nium matter as much as the blockchain itself. The competitive battleground is shifting away from token issuance and toward payout orchestration, banking connectivity, liquidity management and compliance automation.

SoFi’s entrance into public-blockchain stablecoins also illustrates that convergence. Traditional financial institutions are no longer merely partnering with crypto-native firms; they are directly participating in issuance and infrastructure development. Mastercard’s expanding regulatory footprint signals a similar shift.

The stablecoin networks that achieve mainstream scale are likely to be the ones that balance openness with institutional trust. Too much decentralization can create compliance uncertainty. Too much centralization can undermine the efficiency and programmability advantages that made blockchain attractive in the first place. 

Because the value proposition is not “crypto.” It is operational efficiency.

The Security Challenge

Blockchain and AI security firm Certik, on May 27, unveiled a new security platform designed to evaluate risks in third-party artificial intelligence (AI) skills. Dubbed the “anti-virus for AI agents,” the release comes amid growing industry concern over the security of AI skill marketplaces.

Security researchers have warned that many of these skills are unvetted, can execute system-level actions and may contain hidden malicious behavior, creating a new software supply chain risk for the AI era. Security audits across the sector have identified risks ranging from credential harvesting and data exfiltration to fund-transfer manipulation and prompt-based override attacks.

Despite these concerns, AI skill marketplaces have expanded rapidly as agent ecosystems mature. However, unlike traditional app stores, most skills are sourced from public repositories with little or no review. Analysts say this creates opportunities for attackers to embed harmful instructions, trigger unauthorized data access or manipulate autonomous execution flows.

In a recent blog post, Certik said its skill scanner platform is designed specifically to evaluate risks that emerge during execution, including scenarios involving financial transactions or fund calls. The scanner produces a numerical score from 0 to 100, along with “pass,” “warn” or “fail” verdicts and categorized findings. According to the company, the system achieves up to 90.5% precision in identifying security risks.

“As AI agents become more deeply integrated into financial systems, enterprise workflows and everyday digital interactions, the security model around third-party skills becomes critically important,” said Ronghui Gu, Certik’s CEO and co-founder. “CertiK Skill Scanner was built to establish a standardized trust layer before execution, helping users and platforms identify hidden risks before sensitive data, assets or systems are exposed.”

Certik said AI skill marketplaces can integrate the scanner directly into publishing pipelines, automatically reviewing skills before they go live and displaying security verdicts to users. Enterprises can deploy the tool as part of internal compliance and risk-management workflows, while independent developers can use it to self-audit skills before publishing.

The company said future updates will allow everyday users to scan skills themselves before installation. The scanner has already been deployed in select Web3 AI agent infrastructure environments. Certik is also expanding integrations with additional platforms, including Finchip.ai.

“Trust is the prerequisite for any skill economy to function at scale,” said Gary Yang, incubation investor at Finchip.ai. “CertiK’s work on skill security verification is exactly what this ecosystem needs. It’s what makes Finchip’s mission of programmable skill ownership and distribution worth building.”

The launch follows Certik’s expansion into AI-focused security infrastructure. Earlier this year, the company introduced its AI Auditor initiative to address risks tied to autonomous systems and AI-driven execution environments.

“AI applications are moving toward increasingly autonomous execution, which creates a new category of security and trust challenges,” Gu said. “We believe security infrastructure for the AI era must function proactively, not reactively.”