After Privacy Coins Surge, Does It Mean a Bear Market Is Coming?

marsbitPublished on 2026-01-31Last updated on 2026-01-31

Abstract

The article explores the sharp rise in privacy coins like ZEC and XMR as a potential signal of an impending bear market in the crypto cycle. Historically, privacy tokens tend to surge when other narratives—such as DeFi or NFTs—lose momentum, often marking a final speculative push before a downturn. In 2017, coins like ZEC and XMR gained attention as "better Bitcoin" alternatives, fueled by technological appeal and hype. By late 2021 and early 2022, privacy projects like Aleo attracted massive investments, though they ultimately failed to deliver practical, mainstream adoption. The recent surge in late 2025, with ZEC rising 20x in three months, lacked clear catalysts but may reflect growing unease with increasing regulatory scrutiny and reduced financial privacy in crypto. While figures like Arthur Hayes and firms like a16z promoted "privacy-as-a-service," the author suggests this may have been a tactic to facilitate sell-offs rather than genuine growth. The piece argues that extreme privacy features—such as Monero’s fully anonymous transactions—often cater to illicit use cases rather than mainstream needs, making them a target for regulators and exchanges. Most users and regulators seek balanced privacy—protection without complete anonymity—which current privacy tokens fail to provide. Without addressing real-world utility and acceptable levels of privacy, these coins may remain the last resort in cyclical market pumps, often leaving investors at a loss.

Author: Eric, Foresight News

Every bull market has its signs of ending. Looking back, among these signs, the sudden explosion of privacy tokens has never been absent.

This recurring phenomenon has the same reason each time: there's nothing left to hype. After all concepts and narratives have been exhausted, the final dance of capital usually chooses "privacy," a topic that has persisted since 2014.

Hype around privacy at the end of a bull market has logical rationality. After experiencing the noise, many people often suddenly realize, in the void of the bull-to-bear transition, what the original intention of Web3 was, then shout about making privacy and decentralization great again—but the result is just another round of speculation.

Although the process is the same, the triggers each time are not entirely identical.

2017 was the heyday of privacy tokens because there were no impressive DApps, and the sector was still in a phase of finding direction. Back then, ZEC, XMR, and DASH were absolute "hot stars," with discussion levels even surpassing Bitcoin. ZEC and XMR were launched with the "technological innovations" of zero-knowledge proofs and ring signatures, respectively, while DASH combined PoW and PoS.

Readers who didn't experience that period might not understand the market's fervor for such tokens at the time. Back then, whether Bitcoin was the absolute core of cryptocurrency was controversial; many such tokens charged ahead under the banner of "better Bitcoin." ZEC's price once surged to $30,000 in early 2018, while Bitcoin's peak price in that cycle was less than $20,000.

Late 2021 and early 2022 were purely about forcing the privacy concept. After experiencing DeFi, NFT, and the metaverse, projects including Aleo received hundreds of millions in funding, with SoftBank, a16z, and Tiger Fund among the investors. The market at that time briefly believed that after the application explosion, privacy could finally move from concept to practical implementation.

Perhaps because everyone was making money and was euphoric, no one truly cared whether privacy was a mass need, or even if there was demand, whether demanders were willing to bear significant costs just to ensure privacy. The result was that it landed—but face-first.

In this cycle, the rise of privacy tokens represented by ZEC began in September 2025. Looking back, it's hard to pinpoint any specific reason at that time to explain why it rose 20 times in three months. If we must find a reason, it might be because it was "not so compliant."

2025 can be said to be the year cryptocurrency was fully legitimized. Multiple countries in Europe and America successively introduced regulatory laws. Even supporting cryptocurrency development couldn't escape scrutiny under regulations like identity verification and anti-money laundering—DeFi was no exception. Thus, although cryptocurrency was no longer considered a security, it essentially wasn't much different from trading securities. Government scrutiny of individuals didn't relax at all; it only temporarily eased regulations on projects and institutions to avoid hindering innovation.

Additionally, the arrest of fraudster Qian Zhimin in the UK, and later the exposure of Chen Zhi whose Bitcoin was confiscated, revealed an open secret: although only you hold the private key, it's not difficult for law enforcement to make you hand it over. When this fact is laid bare again, it might trigger some investors to switch to privacy tokens.

But including BitMEX co-founder Arthur Hayes's shilling and a16z's mention of "privacy as a service" all happened after November. Judging from the price trend, this seems more like cover for dumping rather than driving the rise. XMR might have held on for two more months due to reasons like Iranian officials fleeing with funds or hackers who stole hundreds of millions in Bitcoin converting it to XMR, but it also peaked and fell rapidly.

Although we can't definitively say the bull market is over now, at least at the end of the last bull market, there were no shortage of well-known figures and institutions shilling privacy. The extremely similar plot should at least make us more vigilant.

The privacy concept has persisted from 2014 to today without dying out because it genuinely meets some gray demands, but it conflicts with actual "privacy" needs. In reality, what most people recognize as privacy protection isn't making data completely untraceable, but more about not being easily exposed. In financial transactions, dark pools exist to prevent large capital actions from affecting the market or being targeted by other funds, but this doesn't mean the transaction information itself can't be verified.

The privacy concept in Web3 is sometimes overly extreme. Zcash's privacy transactions are optional, while XMR is private by default—sender, receiver, and amount can't be verified on-chain, which is also the core reason XMR was delisted by over 70 global cryptocurrency exchanges in 2025. For most people, there seems to be insufficient reason to use XMR to hide traces. Moreover, the process of buying XMR itself is traceable; when you buy XMR, you might be suspected of engaging in illegal activities.

Simply put, most people just want their behavioral records protected and respected, not completely hidden; regulatory agencies especially cannot accept channels almost tailor-made for money laundering. With current technology, anonymous on-chain transfers of USDT are also achievable, so there's really not much reason to use a targeted asset just for privacy.

Web3 has been talking about privacy for over 10 years but seems to always avoid the question: "What level of privacy do we actually need?" Without finding real scenarios, privacy tokens may forever be the last bagholders in sector rotation.

Related Questions

QAccording to the article, what is a common sign that a bull market in cryptocurrency might be ending?

AThe article states that a sudden surge in privacy coins is a common sign that a bull market might be ending, as it often represents the 'last dance' for capital when other narratives have been exhausted.

QWhat was the primary reason given for the rise of privacy coins like ZEC in September 2025?

AThe article suggests the main reason was that privacy coins were 'less compliant' with the increasing regulatory scrutiny on mainstream cryptocurrencies, which led some investors to seek assets that offered more anonymity.

QWhy does the author believe the 'privacy' narrative in Web3 is problematic?

AThe author argues that the Web3 privacy narrative is often too extreme, focusing on complete anonymity which is at odds with what most people and regulators actually want—protection and respect for data, not complete untraceability, which is often associated with illicit activities.

QWhat historical example does the article use to show the market's past enthusiasm for privacy coins?

AThe article cites the 2017 bull market where ZEC's price briefly reached $30,000, surpassing Bitcoin's price at the time, due to intense market speculation and the belief that these coins were 'better versions of Bitcoin'.

QWhat fundamental question does the article claim the Web3 privacy space has avoided for over a decade?

AThe article states that the space has avoided the crucial question: 'What degree of privacy do we actually need?', leading to a lack of real-world use cases and making privacy coins the last resort in market cycles.

Related Reads

Former CFTC Chairman, Circle President Tarbert: Preaching Long-Termism While Cashing Out $30 Million Himself

Former CFTC Chairman and Circle President Heath Tarbert has consistently advocated for a long-term vision in public, urging patience from investors as Circle’s stock price has fallen significantly from its peak. However, it has been revealed that since Circle’s IPO, Tarbert has continuously sold his CRCL shares through pre-arranged trading plans, cashing out approximately $30 million, without making any public market purchases. This contrast between his public messaging and personal actions has drawn criticism. Tarbert joined Circle in July 2023 as Chief Legal Officer, leveraging his regulatory experience to help guide the company through its IPO and expansion. Despite promoting stablecoins as long-term infrastructure, he established a 10b5-1 trading plan just before Circle went public, leading to substantial stock sales over the following year. In March 2026, he initiated another plan to sell more shares. His career trajectory highlights a pattern of moving between high-level regulatory roles and influential positions in the financial sector. After resigning as CFTC Chairman in early 2021, he joined Citadel Securities as Chief Legal Officer just 27 days later, during a period of intense regulatory scrutiny for the firm. He later joined Circle, aiding its efforts to navigate regulatory challenges for its public listing. While Tarbert's expertise in policy and compliance is valuable to companies like Circle, his actions—advocating long-term confidence while personally divesting—raise questions about the alignment between his public statements and his private financial decisions, leaving investors who followed his advice to bear the market risks.

marsbit18m ago

Former CFTC Chairman, Circle President Tarbert: Preaching Long-Termism While Cashing Out $30 Million Himself

marsbit18m ago

Gate Research Institute: The 'Wall Street-ization' Wave of Crypto Financial Products – Competition or Integration?

The article titled "Gate Research Institute: Are Crypto Financial Products Sparking a 'Wall Street' Wave—Competition or Convergence?" explores the evolving relationship between the crypto ecosystem and traditional finance (TradFi). The piece begins by reflecting on Bitcoin's original 2009 vision of decentralization, disintermediation, and moving away from banks. It then contrasts this with the 2024 landscape, where key crypto assets like Bitcoin are increasingly held through Wall Street products like ETFs issued by giants like BlackRock. The article questions whether this signifies that TradFi is systematically taking over the rights to issue, price, custody, and distribute crypto financial assets. The core argument is that this is not a zero-sum takeover but rather a bidirectional convergence where each side addresses the other's weaknesses. Crypto offers 24/7 global markets, programmable settlement, and open access but lacks compliant channels, institutional-grade custody, deep fiat liquidity, and mainstream distribution. TradFi possesses these but is constrained by legacy systems, limited operating hours, and slow settlement. Two primary convergence paths are highlighted: * **Path A (CEX to TradFi):** Exemplified by Gate, which has progressed from offering tokenized stocks and CFDs to providing direct, real stock trading (US, Hong Kong, South Korea) within its platform, using USDT. * **Path B (TradFi to Crypto):** Exemplified by Robinhood, which has integrated crypto trading, acquired exchanges like Bitstamp, and is moving traditional assets like stocks onto the blockchain via tokenization and its own Layer 2. Both paths are ultimately competing to become the next-generation, unified financial account—a "super account" where users can seamlessly trade cryptocurrencies, stocks, ETFs, RWA (Real World Assets), and tokenized treasury products in one interface. The growth of RWA and tokenized treasuries (e.g., BlackRock's BUIDL) is presented as the asset-layer fusion, providing stable, yield-bearing assets on-chain and acting as a bridge between the two worlds. In conclusion, the "Wall Street-ization" of crypto is framed as a mutual transformation. Decentralized ideals persist in the protocol layer, while at the application layer, a more efficient, global, and accessible unified capital market is emerging from this convergence. The future competition lies not between crypto exchanges and stockbrokers, but between platforms vying to offer the most comprehensive asset coverage, liquidity, and user experience within a single account.

marsbit22m ago

Gate Research Institute: The 'Wall Street-ization' Wave of Crypto Financial Products – Competition or Integration?

marsbit22m ago

Claude's Major New Feature: Screen Recording + Voice, Distilling Your Skills into AI Tasks in One Click

Claude has introduced a major new feature called "Record a Skill," available for Pro, Max, and Team users. This function, found in the Claude desktop app's CoWork menu, allows users to create reusable AI skills simply by recording their screen and providing voice narration while performing a task. Claude then automatically analyzes the recording and generates a functional Skill. A hands-on test confirmed the feature works seamlessly. Users start recording via the Skills manager, perform their workflow while verbally explaining the steps and logic, and avoid including sensitive information. After recording, Claude processes the content and creates the Skill, which can be saved and later invoked with a slash command (/). This eliminates the need for manual adjustments or writing complex instruction files. The innovation goes beyond mere efficiency. Previously, creating a Skill required writing a detailed SKILL.md file in Markdown—a significant barrier for non-technical users. "Record a Skill" bypasses this by directly capturing both actions and the implicit reasoning shared in the narration. This lowers the barrier to knowledge transfer and automation, addressing a core challenge in corporate knowledge management: the difficulty of getting experts to write and maintain documentation. However, the feature also highlights a shift in the nature of work. A case study from March 2026 showed a freelancer whose five-year client relationship was effectively replaced by a hand-coded Claude Skill automating their content workflow. With the even lower barrier of screen recording, the ability to distill personal expertise into automatable skills accelerates this trend. The "moat" for work is moving from simply knowing how to do a task to mastering tasks that are difficult or impossible to automate.

marsbit27m ago

Claude's Major New Feature: Screen Recording + Voice, Distilling Your Skills into AI Tasks in One Click

marsbit27m ago

Feeding AI "Noise" Can Also Boost Scores, This Work Enables Positive Transfer with Noise

Feeding "Noise" to AI Can Improve Performance: A Method Enables Positive Transfer from Noise This work, Semi-Supervised Noise Adaptation (SSNA), introduces a Noise Adaptation Framework (NAF) that challenges traditional transfer learning. Instead of requiring a labeled source domain of real data (e.g., images, text), NAF uses randomly generated Gaussian noise as the source. For a target task with C classes, it constructs C noise clusters by sampling from Gaussian distributions. Although this synthetic noise contains no semantic meaning, NAF trains it to form a discriminative class structure in a shared representation space—clustering same-class noise and separating different classes. The key is aligning this learned structure from the noise domain to the real, sparsely labeled target domain. A small number of target labels are still essential to establish the correspondence between noise clusters and actual classes. The training objective combines: 1) supervised loss on the few labeled target samples, 2) classification loss for the noise to build its structure, and 3) a distribution alignment loss (using Negative Domain Similarity) to minimize the gap between the noise and target domains in the shared space. Experiments show significant gains in few-label settings. With just 4 labels per class, NAF with a ResNet-18 backbone improves accuracy over a standard supervised baseline (ERM) by +12.35% on CIFAR-10, +7.61% on CIFAR-100, +4.38% on DTD-47, and +2.74% on Caltech-101. It also benefits fine-grained datasets and scales to ImageNet-1K (with 100 labels/class) and text classification (AG News). NAF can be integrated into existing semi-supervised methods like FixMatch for further gains. Ablation studies confirm the transferred benefit comes from the discriminative structure of the noise, not randomness itself. Collapsing all noise into a single point causes negative transfer, while increasing separation between noise cluster centers improves performance. The amount of noise per class is less critical once a basic structure forms. In conclusion, this work demonstrates that for positive transfer, the semantic content of source data may not be necessary. What can be effectively transferred is the *organizational structure* of categories within a representation space. This offers a promising alternative for scenarios where real source data is unavailable due to privacy, copyright, or procurement constraints.

marsbit28m ago

Feeding AI "Noise" Can Also Boost Scores, This Work Enables Positive Transfer with Noise

marsbit28m ago

Trading

Spot
活动图片