When Crypto Projects Run Out of Supply, What Can Traders Trade?

比推2026-02-02 tarihinde yayınlandı2026-02-02 tarihinde güncellendi

Özet

The article examines the severe downturn in the crypto market, particularly the sharp decline in Bitcoin and altcoin prices, and raises a critical question: what will traders be able to trade in a year if the supply of new crypto-native projects dries up? Data shows a structural collapse in early-stage funding for crypto projects (like L1s, L2s, DeFi), with a 63.9% drop in seed/angel rounds over four years. This "first-level market death" means fewer new tokens will launch, leaving exchanges and traders with a shrinking pool of native assets. Even established crypto funds are struggling with poor returns and low cash distributions post-2020. While memes surged as an alternative, they have evolved into short-term, attention-based assets driven by liquidity and speculation—not sustainable replacements for traditional altcoins. The industry is now looking outward for solutions: - **Tokenization of real-world assets (RWA)**: Platforms are listing tokenized stocks, metals, and indices to attract traders with traditional market volatility and narratives. - **Prediction markets**: Platforms like Polymarket are growing rapidly by allowing direct betting on real-world events (e.g., elections, macro trends), simplifying speculation to yes/no outcomes based on probability. In conclusion, as native project pipelines shrink, the market is shifting from "new token-driven trading" to speculating on external uncertainties and tradable narratives from the broader world. Trader...

Author: Mandy, Azuma

Original Title: One Year Later, What Can the Crypto Market Still Trade?


This weekend, amid internal and external challenges, the crypto market was once again bloodied. BTC is currently hovering around the strategic cost price of $76,000, while altcoins are so dismal that looking at their prices makes one want to poke their eyes out.

Behind the current bleak scene, after recent conversations with projects, funds, and exchanges, one question keeps recurring in my mind: What will the crypto market be trading one year from now?

The more fundamental question behind this is: If the primary market no longer produces "the secondary market of the future," what will the secondary market be trading in a year? How will exchanges change?

Although the death of altcoins has long been a cliché, the market has not been short of projects over the past year. Every day, projects are still queuing up for TGE. As media, we are still frequently coordinating market promotions with project teams.

(Note: In this context, when we say "projects," we mostly refer narrowly to "project teams"—simply put, those benchmarking against Ethereum and the Ethereum ecosystem: underlying infrastructure and various decentralized applications, and specifically "token-issuing projects." This is the cornerstone of so-called native innovation and entrepreneurship in our industry. So, for now, we’ll set aside Memes and platforms emerging from traditional industries entering crypto.)

If we look back a bit further, we’ll discover a fact we’ve all been avoiding: these upcoming TGE projects are "legacy old projects." Most of them raised funds 1–3 years ago and are only now finally reaching token issuance—or, under internal and external pressure, are forced to take this step.

This seems like a kind of "industry inventory clearance," or, to put it more harshly, queuing up to complete their lifecycle: issue the token, give the team and investors closure, and then lie down quietly awaiting death, or spend the money on the books hoping for a miraculous turnaround.

The Primary Market Is Dead

For "old-timers" like us who entered the industry during the ICO era or even earlier, have experienced several bull and bear cycles, and witnessed industry红利 empowering countless individuals, there’s a subconscious belief: given enough time, new cycles, new projects, new narratives, and new TGEs will always emerge.

However, the reality is that we are far from our comfort zone.

Let’s look at the data. Over the recent four-year cycle (2022–2025), excluding special primary market activities such as M&A, IPO, and public fundraising, the number of financing deals in the crypto industry has shown a clear downward trend (1639 ➡️ 1071 ➡️1050➡️829).

The reality is uglier than the data. The change in the primary market is not just an overall shrinkage in amount but a structural collapse.

Over the past four years, the number of early-stage rounds (including angel, pre-seed, and seed rounds), which represent the industry’s fresh blood, has shown a greater decline (825 ➡️ 298, a drop of 63.9%) compared to the overall decrease (49.4%). The primary market’s ability to supply blood to the industry has been shrinking.

The few sectors showing an upward trend in financing deals are financial services, exchanges, asset management, payments, AI, etc., which apply crypto technology but have limited actual relevance to us. Frankly, most of these won’t "issue tokens." In contrast, native "projects" like L1, L2, DeFi, and social have seen a more significant decline in financing.

Odaily Note: Chart sourced from Crypto Fundraising

One easily misinterpreted data point is that while the number of financing deals has drastically reduced, the average amount per deal has increased. The main reason is the "mega projects" mentioned earlier, which have captured large amounts of capital from traditional finance, significantly raising the average. Additionally, mainstream VCs tend to double down on betting on a few "super projects," such as Polymarket’s multiple hundred-million-dollar funding rounds.

From the crypto capital side, this top-heavy vicious cycle is even more pronounced.

Not long ago, an outsider friend asked me about a well-known, super-old crypto fund currently raising capital. After looking at the deck, he asked me in confusion why their returns were "so poor." The table below shows the real data from that deck. I won’t name the fund, but I’ve extracted its fund performance data from 2014–2022.

It’s clear that between 2017 and 2022, this fund’s IRR and DPI changed significantly—the former represents the fund’s annualized return level, reflecting "paper profitability," while the latter represents the multiple of cash returns actually returned to LPs.

Looking at different vintages, this set of fund returns shows a very clear "cycle断层": Funds established between 2014–2017 (Fund I, Fund II, Fund III, Fund IV) significantly outperformed, with TVPI generally in the 6x–40x range, Net IRR maintained at 38%–56%, and also already having a high DPI, indicating that these funds not only had high paper returns but also completed large-scale realizations, eating the era红利 of early crypto infrastructure and top protocols from 0 to 1.

In contrast, funds established after 2020 (Fund V, Fund VI, and the 2022 Opportunity Fund) clearly dropped a grade, with TVPI mostly concentrated in the 1.0x–2.0x range, DPI close to zero or very low, meaning returns mostly still on paper and not converted into real exit profits. This reflects that against the backdrop of valuation inflation, intensified competition, and declining project quality, the primary market can no longer replicate the excess return structure driven by "new narratives + new asset supply."

The real story behind the data is that after the DeFi Summer hype in 2019, valuations for crypto-native protocols in the primary market were inflated. When these projects finally issued tokens two years later, they faced weak narratives, industry tightening, exchanges controlling their fate and临时 modifying terms, etc., generally performing poorly, even with市值倒挂. Investors became the disadvantaged group, and funds found it difficult to exit.

But these周期错配 funds could still create a false appearance of prosperity in parts of the industry, until the真实惨烈 data became直观 apparent during fundraising by some massive star funds in the past two years.

The fund I used as an example currently has an AUM of nearly $3 billion, which further illustrates that it is a mirror of the industry cycle—doing well or not is no longer a matter of individual project selection; the大势已去.

While old牌 funds, though now struggling to raise capital, can still survive, lie flat, eat management fees, or pivot to investing in AI, many more funds have already shut down or turned to secondary markets.

For example, the current "Ethereum Bull King" in the Chinese market, Boss Yi Lihua—who remembers that not long ago he was a representative figure in primary, investing in over a hundred projects annually?

The Alternative to Altcoins Was Never Meme

When we say crypto-native projects are drying up, a counterexample is the explosion of Memes.

Over the past two years, one说法 repeatedly mentioned in the industry is: The alternative to altcoins is Meme.

But looking back now, this conclusion has actually been verified as wrong.

In the early days of the Meme wave, we played Memes the way we played mainstream altcoins—screening a large number of Meme projects for so-called fundamentals, community quality, narrative rationality, trying to find the one that could survive long-term, continuously refresh, and eventually grow into Doge, or even the "next Bitcoin."

But today, if someone still tells you to "hold Meme," you’d think they’ve lost their mind.

Current Memes are a mechanism for the instant monetization of热度: a博弈 of attention and liquidity, products批量 manufactured by Dev and AI tools,

an asset form with an extremely short lifecycle but a continuous supply.

They no longer aim to "survive" but to be seen, traded, and utilized.

Our team also has several long-term, consistently profitable Meme traders. Clearly, they focus not on the project’s future but on rhythm, diffusion speed, sentiment structure, and liquidity paths.

Some say Memes are unplayable now, but in my view, after Trump’s "final割," Meme has truly matured as a new asset form.

Meme was never a substitute for "long-term assets"; it has returned to the essence of attention finance and liquidity博弈. It has become purer, more brutal, and also less suitable for most ordinary traders.

Seeking Solutions Outward

Asset Tokenization

So when Memes become professionalized, Bitcoin becomes institutionalized, altcoins萎靡, new projects are about to断层, what can we ordinary folks who nonetheless enjoy value research, comparative analysis, possess speculative attributes, yet aren’t purely high-frequency probability gamblers, and want sustainable development, actually play?

This question doesn’t just belong to retail.

It also lies before exchanges, market makers, and platforms—after all, the market cannot forever rely on higher leverage and more aggressive contract products to maintain activity.

In fact, as this entire固有 logic begins to collapse, the industry has long started seeking solutions向外.

The direction we are all discussing is repackaging traditional financial assets as on-chain tradable assets.

Stock tokenization, precious metal assets, are becoming the top priority for exchange layouts. From a host of centralized exchanges to the decentralized platform Hyperliquid, this path has been seen as the key to breaking the deadlock, and the market has given positive feedback—during the craziest days for precious metals last week, daily silver trading volume on Hyperliquid once exceeded $1 billion, with tokenized stocks, indices, precious metals, and other assets once occupying half of the top ten trading volume spots, boosting HYPE by 50% short-term under the "full-asset trading" narrative.

Admittedly, some current slogans, such as "providing new choices, low门槛 for traditional investors," are still premature and unrealistic.

But from a crypto-native perspective, it might solve internal problems: after the supply and narratives of native assets slow down, old coins萎靡, new coins断供, what new trading rationale can crypto exchanges still provide to the market?

Tokenized assets are easy for us to pick up. In the past, we researched: public chain ecosystems, protocol revenue, token models, unlock schedules, and narrative space.

Now, the research objects are starting to become: macroeconomic data, financial reports, interest rate expectations, industry cycles, and policy variables. Of course, we’ve already been researching many of these parts.

Essentially, this is a migration of speculative logic, not simply a category expansion.

Listing gold tokens, silver tokens, isn’t just about adding a few more币种; what they are truly trying to introduce are new trading narratives—bringing the volatility and rhythm originally belonging to traditional financial markets into the internal crypto trading system.

Prediction Markets

Besides bringing "external assets" on-chain, another direction is bringing "external uncertainty" on-chain—prediction markets.

According to Dune data, although the crypto market crashed last weekend, prediction market trading activity反而 increased instead of decreasing, with weekly transaction count hitting a new historical high of 26.39 million. Leading Polymarket had 13.34 million transactions, followed closely by Kalshi with 11.88 million.

We won’t elaborate on the development prospects and scale expectations of prediction markets here—Odaily has been writing over two analysis articles on prediction markets daily recently... You can search for them yourself.

I want to talk from the perspective of币圈 users: Why do we play prediction markets? Is it because we are all degenerate gamblers?

Of course.

Actually, for a long time, altcoin traders weren’t本质上 betting on technology but on events: Will it get listed? Is there a partnership announcement? Is it about to issue a token? Is it launching a new feature? Is there a regulatory利好? Can it ride the next narrative wave?

Price is just the result; the event is the starting point.

Prediction markets, for the first time,拆 this matter from an "implied variable in the price curve" into an object that can be directly traded.

You no longer need to buy a token to indirectly bet on whether a certain outcome will happen; you can directly bet on "whether it will happen" itself.

More importantly, prediction markets fit the current environment of "new project断供, narrative scarcity."

When tradable new assets become fewer, market attention反而 concentrates more on macro, regulation, politics, big shot behavior, and major industry nodes.

In other words, the tradable "标的" are decreasing, but the tradable "events" are not减少; they are even increasing.

This is also why the liquidity that has truly emerged in prediction markets in recent years almost entirely comes from non-crypto-native events.

It本质上 introduces the uncertainty of the external world into the internal crypto trading system. From a trading experience perspective, it is also more friendly to original币圈 traders:

The core question is extremely simplified to one—Will this outcome happen? And, is this current probability expensive?

Unlike Meme, the门槛 of prediction markets isn’t execution speed but information judgment and structural understanding.

Hearing this, doesn’t it feel like maybe I can try this too.

Conclusion

Perhaps the so-called币圈 will eventually die out in the not-too-distant future, but before消亡, we are still struggling hard. After "new-coin-driven trading" gradually exits the stage, the market will always need a new, low-participation-barrier, narrative-spreading, sustainable speculative载体.

Or rather, the market won’t disappear; it will only migrate. When the primary market no longer produces the future, what the secondary market can truly trade are these two things—the uncertainty of the external world, and tradable narratives that can be repeatedly重构.

What we can do is perhaps adapt in advance to yet another migration of the speculative paradigm.


Twitter:https://twitter.com/BitpushNewsCN

Bitpush TG Discussion Group:https://t.me/BitPushCommunity

Bitpush TG Subscription: https://t.me/bitpush

Original link:https://www.bitpush.news/articles/7608051

İlgili Sorular

QWhat is the main concern raised in the article regarding the crypto market's future?

AThe article expresses concern that the primary market for crypto-native projects (e.g., L1s, L2s, DeFi) is dying, leading to a future shortage of new assets for secondary markets to trade, which could fundamentally change the landscape of crypto exchanges and trading.

QAccording to the data presented, what trend has been observed in early-stage crypto funding rounds?

AThe data shows a significant decline of 63.9% in the number of early-stage funding rounds (angel, pre-seed, seed) from 825 to 298 over a recent four-year period, indicating a severe contraction in the primary market's ability to fund new, innovative crypto projects.

QHow does the article characterize the evolution of Meme coins as an asset class?

AThe article argues that Meme coins have evolved into a potential substitute for traditional' altcoins but are now a mature asset class focused on instant attention monetization and liquidity博弈博弈, with extremely short lifecycles and are generated in bulk by developers and AI tools, making them a pure,残酷, and professionalized form of speculation unsuitable for most retail traders.

QWhat two main external solutions is the crypto industry exploring to address the internal asset shortage?

AThe industry is exploring two main external solutions: 1. Asset tokenization (e.g., tokenized stocks, precious metals) to introduce traditional financial assets and their associated narratives and volatility into the crypto trading system. 2. Prediction markets, which allow for direct betting on real-world events and uncertainties, leveraging the market's focus on macro events and providing a simpler, event-based trading experience.

QWhat does the article conclude will be the primary objects of trade in the crypto secondary market if new project issuance dries up?

AThe article concludes that the secondary market will primarily trade on two things: the uncertainty of the external world (via prediction markets and similar instruments) and tradable narratives that can be constantly reconstructed, representing a migration of投机投机 paradigms rather than the market's disappearance.

İlgili Okumalar

It Took Me a Year to See the Bitter Truth About Agent Payments

After a year building infrastructure for the Agent economy, engaging with major players like Stripe, Visa, and Coinbase, the author shares a sobering analysis of the current state of Agent payments. The core finding is a stark lack of genuine, immediate demand across most envisioned use cases. The article breaks down four key market segments: 1. **Agent-to-Merchant (Consumer Shopping):** For most product categories (e.g., clothing, electronics), conversational AI shopping is a step backwards from visual e-commerce interfaces. While agents excel at understanding needs, they can't replace side-by-side product comparison. Real merchant interest is defensive "Agent Engine Optimization," not driven by current customer demand. Potential exists for high-frequency, low-decision purchases (like food delivery) or navigating complex store UIs, but these require massive B2C distribution channels dominated by giants like Amazon. 2. **Agent-to-API (Developer Services):** Developers already have subscriptions and billing relationships for APIs (compute, data). Prepaid balances solve micro-payment issues for low transaction volumes. A deeper structural problem is that major SaaS vendors' business models rely on enterprise contracts, resisting granular pay-per-call pricing. While protocols like MPP and x402 serve the long tail of niche services, this market is small and developers are historically low-willingness-to-pay. 3. **Agent-to-Agent:** This remains largely theoretical with minimal transaction volume. While it represents a long-term bet on a fundamentally new transaction infrastructure (sub-second, micro-penny to million-dollar, multi-party settlements), it does not constitute a present market. 4. **Agent-to-Finance:** This is the only category with existing, paying demand. Integrating AI into financial workflows (trading, portfolio management) is a natural evolution and enables new capabilities like autonomous rebalancing. However, competition favors established, regulated institutions. The "real problem" is not moving money between agents, but the broader challenge of **coordination**—orchestrating work between agents and humans, verifying outcomes, and settling results. Payment is just one component of settlement, which is itself part of coordination. Companies that solve the coordination layer will subsume payment, not the other way around. While well-funded incumbents build defensively for a long-term future, startups must find where the market is today—which, for the author's team, lies outside these four categories in an area of real, growing, and underserved activity.

marsbit11 dk önce

It Took Me a Year to See the Bitter Truth About Agent Payments

marsbit11 dk önce

It Took Me a Year to See the Hard Truth About Agent Payments

**Title: It Took Me a Year to See the Hard Truth About Agent Payments** Over the past year, I've worked on infrastructure for the Agent economy, engaging with major players like Stripe, Visa, Coinbase, and numerous startups. The findings reveal a stark reality: genuine, widespread demand for Agent-based payments does not yet exist. **Key Observations:** * **Agent-to-Merchant (Shopping):** The user experience for AI shopping often falls short, especially for visual product discovery. While AI excels at understanding needs, conversational interfaces can't yet replace browsing and comparing multiple products visually. Current merchant interest is largely defensive ("Agent Engine Optimization") for a future that hasn't arrived. High-frequency, low-friction purchases (like food delivery) are potential fits, but lack open APIs and face high AI inference costs. Simpler, more affordable, or cross-language interactions for complex UIs are a niche opportunity but require massive consumer distribution to scale. * **Agent-to-API (Developer Tools):** Developer payment needs for APIs (computing, data, models) are already met through subscriptions and prepaid credits. The core challenge is not payment friction but supplier economics: most large SaaS providers prefer enterprise contracts over micropayments for API calls. Protocols like MPP and x402 suit the long-tail of smaller services but cater to a developer market historically reluctant to pay for these tools. Major infrastructure needs at the top of the stack are already being addressed. * **Agent-to-Agent (Machine Commerce):** This is a long-term vision with almost no current transaction volume. While a future with high-speed, high-frequency, multi-party machine-to-machine transactions would require novel infrastructure, it remains theoretical. The market is not here yet. * **Agent-to-Finance:** This is the only category with clear, present demand. Financial professionals and DeFi users already pay for tools, and AI augmentation is a natural evolution. Autonomous AI agents can enable entirely new financial strategies. However, competition is fierce from established, regulated incumbents who can more easily layer AI onto their existing products. **The Core Insight:** Companies, especially giants with long time horizons, are building defensively for a potential future of mass machine commerce. For them, early investment is a low-cost hedge. For startups, the current market reality is different. The primary challenge isn't just moving money between agents (payments). The larger, unsolved problem is **orchestration** – coordinating work between agents and humans, verifying outcomes, and then settling. Payment is just a part of settlement, which is just a part of orchestration. Companies that solve the orchestration problem will subsume payments, not the other way around. After a year of building, we see the real, growing, and underserved market opportunity lies in this broader domain of orchestration.

链捕手34 dk önce

It Took Me a Year to See the Hard Truth About Agent Payments

链捕手34 dk önce

Claude Opus 4.8 Finds a $4.5 Billion Bug: The AI Era is Mass-Producing Hackers

A researcher discovered a critical "infinite mint" vulnerability in the Zcash cryptocurrency's Orchard protocol using Claude Opus 4.8, leading to a swift fix but also a 50% market drop, erasing billions in value. This incident highlights a new era where powerful, accessible AI models are dramatically lowering the barrier to finding software vulnerabilities. Previously, the security community feared specialized models like Claude Mythos Preview, capable of finding decades-old zero-day exploits. The Zcash case, however, involved a publicly available, general-purpose model. This shift makes advanced security auditing—and attack capabilities—accessible to far more people, not just experts. The mass democratization of vulnerability discovery brings a dual challenge: a flood of low-quality, AI-generated false reports that overwhelm maintainers, and the real, rapid uncovering of deep, dangerous bugs. Open-source projects, often understaffed and unfunded, are particularly vulnerable to this "attention DDoS." The article cites examples like curl shutting down its bug bounty program due to the unsustainable workload. Our perceived digital safety has often been luck, relying on the high cost and effort required to find deeply hidden flaws in complex systems, as seen with historical vulnerabilities like Heartbleed or Baron Samedit. AI changes this cost structure, effectively "mass-producing flashlights" to illuminate every corner of our codebase. While large companies operate extensive security chains involving external white-hat hackers and massive defensive operations, the global cybersecurity workforce faces a severe shortage, especially of experienced personnel capable of analyzing complex threats and coordinating fixes. The core dilemma emerges: AI makes *finding* bugs cheap and scalable, but *fixing* them remains a slow, expensive, and human-intensive process. The article concludes that AI won't destroy the internet but acts as a bright light, revealing that our digital existence is not inherently secure but is precariously maintained by ongoing human effort. The true cost in the AI era may not be discovery, but whether there will be enough people left willing and able to do the hard work of repair.

marsbit1 saat önce

Claude Opus 4.8 Finds a $4.5 Billion Bug: The AI Era is Mass-Producing Hackers

marsbit1 saat önce

Codex Goal Mode Usage Guide: How to Make AI Continuously Pursue a Specific Objective

"Codex Goal Mode: How to Make AI Work Continuously Toward a Specific Goal" OpenAI's Codex "goal mode" (/goal) transforms the AI from a reactive code assistant into a proactive execution agent capable of working autonomously for hours or even days to achieve a defined objective. To maximize its effectiveness, follow these key principles: 1. **Define Clear, Verifiable Exit Criteria:** The goal prompt should be a concise, measurable success condition, not a lengthy specification. Use quantifiable metrics like "reduce build time by 30%" or "achieve 100% test parity." 2. **Provide Initial Guidance and Tools:** Direct Codex toward likely problem areas and specify available tools (e.g., browsers, testing environments) to prevent it from exploring unproductive paths. 3. **Enable Progress Measurement:** Equip Codex with ways to track advancement, such as creating comparison tools for visual tasks or evaluation sets, ensuring it can gauge its own progress. 4. **Use a Realistic Execution Environment:** For tasks like performance optimization, provide access to environments that closely mimic production (e.g., similar configs, databases) to yield valid results. 5. **Be Cautious with Visual Goals:** Avoid vague "pixel-perfect" instructions. Instead, supplement visual references with functional checklists or design system specifications to prevent Codex from obsessing over minor details. 6. **Implement Progress Tracking:** For long-running tasks, have Codex commit code to draft PRs, update progress documents, or send Slack updates to maintain visibility into its work. 7. **Review and Consolidate Results:** Once the goal is met, instruct Codex to review its work, clean up ineffective experimental code, and reflect on what strategies succeeded or failed. Ultimately, using goal mode shifts the developer's role from writing prompts to managing a persistent engineering agent—defining objectives, establishing metrics, configuring environments, and conducting final reviews.

marsbit2 saat önce

Codex Goal Mode Usage Guide: How to Make AI Continuously Pursue a Specific Objective

marsbit2 saat önce

İşlemler

Spot
Futures

Popüler Makaleler

ONE Nasıl Satın Alınır

HTX.com’a hoş geldiniz! Harmony (ONE) satın alma işlemlerini basit ve kullanışlı bir hâle getirdik. Adım adım açıkladığımız rehberimizi takip ederek kripto yolculuğunuza başlayın. 1. Adım: HTX Hesabınızı OluşturunHTX'te ücretsiz bir hesap açmak için e-posta adresinizi veya telefon numaranızı kullanın. Sorunsuzca kaydolun ve tüm özelliklerin kilidini açın. Hesabımı Aç2. Adım: Kripto Satın Al Bölümüne Gidin ve Ödeme Yönteminizi SeçinKredi/Banka Kartı: Visa veya Mastercard'ınızı kullanarak anında Harmony (ONE) satın alın.Bakiye: Sorunsuz bir şekilde işlem yapmak için HTX hesap bakiyenizdeki fonları kullanın.Üçüncü Taraflar: Kullanımı kolaylaştırmak için Google Pay ve Apple Pay gibi popüler ödeme yöntemlerini ekledik.P2P: HTX'teki diğer kullanıcılarla doğrudan işlem yapın.Borsa Dışı (OTC): Yatırımcılar için kişiye özel hizmetler ve rekabetçi döviz kurları sunuyoruz.3. Adım: Harmony (ONE) Varlıklarınızı SaklayınHarmony (ONE) satın aldıktan sonra HTX hesabınızda saklayın. Alternatif olarak, blok zinciri transferi yoluyla başka bir yere gönderebilir veya diğer kripto para birimlerini takas etmek için kullanabilirsiniz.4. Adım: Harmony (ONE) Varlıklarınızla İşlem YapınHTX'in spot piyasasında Harmony (ONE) ile kolayca işlemler yapın.Hesabınıza erişin, işlem çiftinizi seçin, işlemlerinizi gerçekleştirin ve gerçek zamanlı olarak izleyin. Hem yeni başlayanlar hem de deneyimli yatırımcılar için kullanıcı dostu bir deneyim sunuyoruz.

368 Toplam GörüntülenmeYayınlanma 2024.12.12Güncellenme 2026.06.02

ONE Nasıl Satın Alınır

Tartışmalar

HTX Topluluğuna hoş geldiniz. Burada, en son platform gelişmeleri hakkında bilgi sahibi olabilir ve profesyonel piyasa görüşlerine erişebilirsiniz. Kullanıcıların ONE (ONE) fiyatı hakkındaki görüşleri aşağıda sunulmaktadır.

活动图片