On January 21, 2026, Eastern Standard Time, research institutions Delphi Digital and Fundstrat successively released a new round of predictions for the 2026 cryptocurrency market. At the same time, China's real estate giant Vanke once again stood at the center of public opinion due to adjustments in its bond repayment plan, casting a shadow over the traditional credit market. On one side are high-profile declarations like “Perp DEXs will become the new Wall Street,” along with a decentralized finance expansion blueprint represented by new credit verification technologies such as zkTLS and x402; on the other side is the approaching interest payment date of Vanke bonds on January 22, 2025, reflecting the tightening of real estate credit and expectations of a pullback. The reality's tightening grip quickly constrains market sentiment. The overarching expectation surrounding these timelines is a theme that may run throughout the year: 2026 could test whether the new financial order represented by Perp DEXs, zkTLS, and AI agents can truly rival the old world as the “new Wall Street,” or if it remains merely a shadow asset fluctuating with risk appetite cycles amid a backdrop of “painful declines and year-end recoveries.”
Prophecies and Warnings: Market Rhythm and Emotional Trajectory in 2026
Regarding the rhythm of 2026, the mainstream narrative from institutions and analysts such as Delphi Digital and Tom Lee (Fundstrat) has begun to converge on a single keyword: repricing after a pullback. Publicly, Tom Lee has been quoted by multiple channels as believing that “2026 will experience painful declines but recover by year-end,” indicating an initial phase dominated by deep pullbacks, followed by a year-end recovery as macro and liquidity conditions improve. Delphi Digital, in a more structural discussion, focuses on the resonance between cycles and infrastructure, suggesting that crypto finance will undergo a hierarchical reshuffle amid significant volatility. These statements are not precise price path predictions in a modeling sense but rather a framework for depicting market rhythm, emphasizing that “pain” and “recovery” may unfold in the same year.
In contrast, the market environment of 2024-2025 is more aligned with a phase of single-narrative-driven fluctuations at the macro level, where expectations of liquidity expansion and the halving cycle, combined with the ETF narrative, provide relatively clear upward momentum. As we enter 2026, increasing macro uncertainty and regulatory variables, along with the profit-taking from prior gains, create a stronger demand for institutional rebalancing and risk management, making “repricing after severe pullbacks” more frequently mentioned than “one-sided bull market euphoria.” Especially in the context of traditional institutions entering the market, as evidenced by products like Grayscale's NEAR Trust ETF, the behavior of crypto assets increasingly resembles that of high-beta risk assets, rather than being driven solely by internal technological narratives, which further emphasizes the expectation of a deep pullback phase.
These expectations are directly reflected in position planning and risk management practices. One type of institution is more inclined to align with the “painful decline” expectation, tightening leverage and positions in advance: adjusting exposure to high-volatility tokens and controlling the utilization of DeFi perpetual contracts and lending protocols to reduce passive exposure during potential severe liquidations. Another type of capital seeks to find allocation windows within the macro narrative of “year-end recovery,” focusing more on gradually building long-term positions during the pullback process, or even pre-designing hedging structures to amplify potential rebound gains through futures, options, or on-chain derivatives in the anticipated bottom region. The interplay of these two strategies has already begun to set the stage for a possible annual script of “first killing valuations, then re-evaluating growth” before entering 2026.
The Vision and Vulnerabilities of Perp DEXs Impacting Wall Street
In the narrative of technology and market structure, the most eye-catching slogan comes from Delphi Digital: “Perp DEXs will become the new Wall Street.” This statement clearly points to the expectation that decentralized exchanges for perpetual contracts will grow into important hubs for global risk pricing and liquidity allocation. Meanwhile, more extreme versions of this slogan, such as “Perp DEXs devouring Wall Street,” are circulating, but these have not been confirmed by official sources and belong to unverified, potentially exaggerated secondary dissemination, which should be strictly distinguished from confirmed original statements in serious analysis.
Returning to the data and structure itself, the current and projected future scale of DeFi lending protocol TVL is in the tens of billions of dollars, with perpetual contract DEXs adding high-frequency, around-the-clock leveraged trading activities on this basis. Compared to traditional Wall Street, they have clear advantages in terms of entry barriers, global accessibility, and product innovation speed: no account opening process, continuous matching 24 hours a day, and contract structures that can iterate quickly. However, the gaps in liquidity depth, market-making efficiency, and user structure are also evident—mainstream Perp DEXs still struggle to compete with large investment banks and traditional futures exchanges in terms of depth and order size, high-frequency market-making often relies on a few specialized institutions and bots, and retail and small-cap funds still make up a significant portion of the user base, which means that the risks of order asymmetry and slippage are still prominent in extreme market conditions.
Once this structure is placed in the context of a “painful decline,” the vulnerabilities faced by Perp DEXs become apparent. High-leverage positions may quickly hit liquidation lines in a short time, potentially triggering on-chain liquidation chain reactions, especially when a single asset or a few assets experience a sudden drop in liquidity. Liquidation bots, in pursuit of maximum recovery value, may concentrate selling in weak price segments, further amplifying volatility. At the same time, some liquidity providers may choose to withdraw from the liquidity pool during severe fluctuations, leading to liquidity withdrawal, which forces remaining participants to bear higher price impact costs. Against the backdrop of increasing regulatory scrutiny, if such volatility is deemed related to systemic risk, the pressure for scrutiny on contract design, leverage multiples, and access barriers in relevant jurisdictions will also rise. The so-called “new Wall Street” must undergo a real-world test in terms of liquidity, risk management, and compliance boundaries to withstand shocks at the level of traditional finance, rather than relying solely on daily trading volume and fee income data to demonstrate its maturity.
zkTLS and x402: The Technological Foundation for Unsecured Credit Testing
Beyond the surface noise of Perp DEXs, new technologies like zkTLS and x402 attempt to rewrite the underlying logic of DeFi from the foundational layer of credit verification. Their common goal is to allow on-chain protocols to verify off-chain credit records without exposing raw data: through the combination of zero-knowledge proofs and transport layer security protocols, they can prove whether a certain entity's reputation, assets, or transaction history in the traditional financial system or Web2 world meets certain conditions, without having to disclose their bank statements, income details, or full identity information. Solutions like x402 further explore how to turn such proofs into interfaces that can be automatically read and executed by contracts, making “credit” a resource that can truly be called upon on-chain, rather than just static materials manually uploaded by users at the front end.
Current DeFi lending still heavily relies on over-collateralization: in the vast majority of mainstream lending protocols, users must first deposit large assets into contracts to obtain loan amounts far less than the value of the collateral. This mechanism is relatively robust in terms of risk control but sacrifices capital efficiency and keeps many entities without sufficient on-chain collateral but with good credit records in the real world locked out. Although market sentiment around “unsecured or low-collateral lending” continues to heat up, there is currently no clear, credible timeline for implementation, and research briefs explicitly prohibit speculation or quantitative commitments regarding the realization of unsecured loans, meaning that over-collateralization will remain the mainstream pattern for the foreseeable future.
Under such premises, a hypothetical scenario can help understand the structural changes that zkTLS might bring if partially implemented in 2026: suppose lending protocols allow some institutional users to obtain a higher loan-to-value (LTV) ratio based on off-chain credit verified by zkTLS, without needing to lock up equivalent or higher collateral assets in the traditional manner, then the overall asset utilization rate would significantly increase, and the turnover speed of funds within DeFi would also accelerate. However, accompanying this would be a substantial increase in risk control complexity—the protocol would need to assess the reliability of both on-chain collateral and off-chain credit proofs simultaneously, designing more refined interest rate gradients and liquidation thresholds to compensate for potential default risks. In terms of interest rate structure, high-credit users might receive lower borrowing rates, compressing the traditional “collateral-only, credit-ignored” single risk pricing model, while ordinary users' borrowing costs may not significantly decrease. This rebalancing would shift DeFi lending from a single-factor model to multi-factor pricing, approaching the complex credit systems of traditional finance, yet still needing to find new compromises between transparency and privacy protection.
AI Agents and Autonomous Trading: New Proprietary Seats and Liquidation Risks
If zkTLS and x402 are reshaping the question of “who can borrow money,” then AI agents are quietly rewriting “who is trading.” In the world of Perp DEXs and lending protocols, an increasing number of automated agents are no longer simple arbitrage scripts but are “24-hour proprietary seats” with strategy evolution and environmental perception capabilities. They can synchronize price and depth across multiple exchanges and chains, automatically completing arbitrage, market-making, and liquidation decisions, and adjusting parameters based on historical performance. This trend resonates with the ongoing wave of tech giants like NVIDIA ramping up AI inference infrastructure in the real world: changes in the pricing structure of computing power and the decline in inference costs make it possible to deploy a large number of distributed trading agents, thus providing a natural testing ground for the AI agent economy in the crypto finance sector.
However, as trading has been partially outsourced to algorithms and models, regulatory and compliance issues come to the forefront. First is the identification of the true controller of accounts: if an on-chain address formally belongs to a certain individual or institution, but almost all instructions are autonomously issued by an AI agent, how should responsibility be divided among “developers—strategy providers—ultimate beneficiaries” in the event of extreme losses or market manipulation allegations? There is no mature precedent for this. Secondly, the boundaries of algorithmic market manipulation become blurred: when AI agents collaboratively push up or suppress prices across multiple Perp DEXs and lending protocols, whether this constitutes manipulation is difficult to apply directly to existing human-centric regulatory frameworks. Additionally, there is the issue of KYC applicability boundaries—if a contract interface allows any agent to access and execute large transactions, while the underlying economic beneficiaries continuously change, the traditional “account-based” due diligence logic will face fundamental challenges.
In the hypothetical scenario of a “painful decline,” AI agents may amplify volatility rather than mitigate risk. When a large number of strategies utilize similar signal sources and risk control models, once the same stop-loss conditions or risk thresholds are triggered, these agents may simultaneously reduce positions or withdraw from liquidity pools in a very short time, leading to severe instantaneous fluctuations similar to traditional market high-frequency trading cascades. Historically, traditional high-frequency trading has been seen as a contributing factor in multiple “flash crash” events, prompting regulators to reconsider circuit breaker mechanisms and order type restrictions. In the cryptocurrency market, there is currently a lack of equally mature protective mechanisms, and the irreversible execution at the contract level, along with widespread use of leverage, means that the destructive power of such cascades could be even more direct. Whether AI agents can become more efficient market-making and risk control tools, or whether they will turn into echo chambers amplifying risk in extreme market conditions, is a question that may receive its first clear answer during the volatility cycle of 2026.
The Shadow of Vanke's Repayment and the Nervousness of the Bond Market
Parallel to these forward-looking technological narratives is the tense nerve of the real credit world. As the interest payment and repayment arrangements for Vanke bonds approach the payment date of January 22, 2025, market attention has rapidly intensified, and subsequent news regarding adjustments to the repayment plan has further exacerbated concerns about the contraction of credit in China's real estate sector. Public information has yet to disclose specific details of the credit enhancement measures, and research briefs have explicitly requested restraint regarding related terms, refraining from any speculative design of missing components. However, this does not prevent the event itself from becoming a barometer of sentiment in the traditional bond market: when leading real estate companies need to adjust plans to maintain repayment order, the market's assessment of the overall credit quality of the real estate sector is bound to be repriced.
From an investor's perspective, the most direct manifestation of this repricing is the widening of bond spreads and the rise in risk aversion. As credit risk premiums are reintroduced, the willingness to hold weak credit assets declines, and funds migrate towards higher-rated, more liquid instruments, while the inclination to allocate to high-risk assets—especially high-volatility, narrative-driven crypto assets—becomes increasingly contradictory. On one hand, crypto assets are viewed by some funds as tools to hedge local credit risk due to their relatively weak correlation with the credit of a single economy; on the other hand, their own severe price volatility and expectations of pullbacks make them difficult to consider a “safe haven” in risk budgets. This contradictory mindset is further amplified against the backdrop of the 2026 narrative of “painful declines.”
If we extend our perspective a bit further, we can imagine that as trust in the traditional credit market further weakens, some funds may attempt to shift towards on-chain yield products and dollar-denominated assets for reasons of asset diversification, hedging local currency credit, or seeking higher returns. Such allocation behavior could bring significant incremental liquidity to the crypto market in the short term, but it also sows the seeds of new systemic risks: when these funds enter the market with shorter-term yield targets and lower emotional tolerance, their reactions to external events are often more rapid and severe, potentially leading to instant liquidity inflows and outflows when new negative shocks occur. In the crypto financial network woven together by Perp DEXs, on-chain lending, and AI agents, once this capital inflow and outflow is combined with leverage structures, it could amplify price volatility, translating credit shocks that were originally confined to the traditional bond market into another round of large-scale fluctuations on-chain.
Technological Gambling and Credit Collapse: The Real Test of 2026
Returning to the broader perspective, on one side are the Perp DEXs claiming to “become the new Wall Street,” along with DeFi credit innovations attempting to break the shackles of over-collateralization with zkTLS and x402, and the AI agents that are pervasive in trading and risk control, collectively constructing a new financial vision for crypto; on the other side is the shadow of real estate debt represented by Vanke's bond repayment pressure, along with the reality constraints that mainstream analysts and institutions continuously repeat regarding the expectation of “painful declines.” This stark contrast makes the 2026 crypto market resemble a dual pressure test: it must prove its value in a macro and credit contraction environment while also demonstrating its maturity at the internal technological and structural levels to withstand shocks from both external and internal sources.
The real key question is whether the crypto market can demonstrate resilience as a relatively independent financial system during the anticipated painful pullbacks, rather than merely serving as a price mirror reflecting global risk appetite cycles. If, during increased volatility in traditional bond and stock markets, crypto assets continue to passively follow the fluctuations of risk asset indices, then regardless of how impressive the trading volume of Perp DEXs is, how pioneering the technological route of zkTLS is, or how intelligent the AI agents are, the market will find it difficult to claim the narrative of “independent asset class” in front of regulators and mainstream institutions. Conversely, only by exhibiting distinctly different liquidity and pricing paths in the face of certain macro shocks, or by accommodating some reasonable financing and asset allocation needs in an environment of credit collapse, can crypto finance truly shed the single label of “high-risk speculative product.”
In this environment of concurrent uncertainty and conflict, a more prudent approach is to view technological narratives as potential upper limits rather than prerequisites for investment decisions. For market participants, before embracing cutting-edge stories like Perp DEXs, zkTLS, and AI agents, it is more important to first verify the regulatory progress in their respective jurisdictions, the actual situation of the cross-market credit transmission chain, and the current liquidity structure both on-chain and off-chain, rather than relying on any single price path or time point prediction to plan positions. 2026 may still write the script of “painful declines and year-end recoveries,” but for truly long-term participants, learning to identify structural changes between credit collapses and technological gambles is the necessary capability to navigate the next cycle.
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