$35,000 The Next Key Level To Break For Bitcoin, Here’s Why

newsbtcPublished on 2023-10-23Last updated on 2023-10-24

Abstract

Bitcoin has now broken the $31,000 mark with its latest rally. According to on-chain data, the level could be the next major milestone for BTC. Bitcoin Realized Price Of 2021...

Bitcoin has now broken the $31,000 mark with its latest rally. According to on-chain data, the level could be the next major milestone for BTC.
Bitcoin Realized Price Of 2021 Holders Is $35,000 At The Moment
In a new post on X,  analyst James V. Straten has discussed the profit/loss situation of the different yearly Bitcoin buyer cohorts. The indicator of interest here is the “realized price,” which keeps track of the average price at which investors in the BTC market bought their coins.
When the asset’s spot price is below this metric, the average holder in the sector is at a loss right now. On the other hand, it being above the indicator suggests the dominance of profits among the investors.
Here, Straten hasn’t shared the chart for the ordinary realized price for the entire circulating supply but rather a few versions of the metric that only consider buyers since the start of a particular year. The chart below shows the trend in the Bitcoin realized price for each year since 2017.

Bitcoin Realized Price

The data for the different realized price levels | Source: @jimmyvs24 on X
As is visible in the graph, the Bitcoin realized price for all years except 2021 is below the current spot price of the cryptocurrency. This implies that the different yearly cohorts of the asset are holding their coins at some net unrealized profit.
The latest groups to enter into a state of profit have been the 2022+ and 2023+ ones. The 2021+ group has a realized price of about $35,000 at the moment, which is still a significant distance away, but as Straten has noted, the gap between the spot price and the metric is now the narrowest since the two diverged back at the start of the bear market.
Interestingly, during the peak in 2021, this group’s cost basis was around $48,000. The analyst suggests their realized price, since decreasing significantly, indicates some impressive Dollar-Cost Averaging (DCA) in the market.
In on-chain analysis, major cost basis levels have always played an important role, as the BTC spot price has often observed support or resistance on retests of them.
The chart shows that the Bitcoin price had found support at the 2023+ realized price back in June. The recent seemingly endless consolidation that BTC saw before the latest rally happened around the 2022+ and 2023+ metrics after they had overlapped.
Given the historical examples, the 2021+ may realize price will cause the price to react somehow when it eventually reaches there. Thus, the $35,000 level would be a significant milestone for the asset, as successfully claiming it could imply clear waters ahead for the cryptocurrency.
At the same time, however, the chances of participants buckling and harvesting their gains are increasing with all these groups coming into profits. Such profit-taking can lead to a pullback in the price, at least in the short term.
BTC Price
At the time of writing, Bitcoin is trading at around $31,200, up 11% in the past week.

Bitcoin Price Chart


Looks like BTC has enjoyed some sharp upwards momentum in the last few days | Source: BTCUSD on TradingView
Featured image from Kanchanara on Unsplash.com, charts from TradingView.com, Glassnode.com

Trending Cryptos

ctr
CitreaCTR
wstusdt
wrapped stUSDTWSTUSDT
apr
aPrioriAPR
ctx
Cryptex FinanceCTX
audio
AudiusAUDIO
mantra
MantraMANTRA
xvs
VenusXVS
waxl
AxelarWAXL
bill
Billions NetworkBILL
pyth
PYTH (Pyth)PYTH
rune
THORChainRUNE
velodrome
Velodrome FinanceVELODROME
brev
BrevisBREV
zrx
ZRX（0X）ZRX
cake
PancakeSwapCAKE

Related Reads

NVIDIA's New Open-Source MoE: One Line of Import, Fine-Tuning Accelerated by 3.7x

NVIDIA has open-sourced NeMo AutoModel, a tool designed to significantly accelerate the fine-tuning of Mixture-of-Experts (MoE) large language models. By adding just one import line to existing code based on Hugging Face Transformers v5, users can achieve a 3.4x to 3.7x increase in training throughput and reduce GPU memory usage by 29% to 32% without altering their API. The key innovations include Expert Parallelism (EP) to distribute expert weights across GPUs, lowering memory pressure; DeepEP to fuse computation and communication; and TransformerEngine kernels for accelerated core operations. Benchmarks on models like Qwen3-30B-A3B show training throughput per GPU jumping from 3075 to 11340 tokens per second. The solution also enables the fine-tuning of very large models, such as the 550B parameter Nemotron 3 Ultra, which would exceed memory limits with the standard Transformers v5. Code and benchmarks are available on GitHub.

marsbit13m ago

NVIDIA's New Open-Source MoE: One Line of Import, Fine-Tuning Accelerated by 3.7x

marsbit13m ago

How to Detect AI-Generated Videos? A Review of Dynamic, Traceable, and Explainable Detection Systems

**How to Detect AI-Generated Videos: A Survey on Dynamic, Traceable, and Explainable Detection Systems** With rapid advances in AI video generation (e.g., Sora, Veo), creating highly realistic, multi-minute videos is now possible, widening the gap with detection research. Current AI video detection, often limited to unreliable binary classifications, is insufficient. This survey, accepted at ACL 2026, reframes the goal as **"factual fidelity verification"**—checking if a video's content (who, when, where, what) aligns with the real world perceptually and cognitively. It categorizes AI-generated videos into three paradigms: **Local Manipulation Videos (LMV**, e.g., face swaps), **Audio-Visual Editing (AVE**, e.g., lip-syncing), and **Generative Video Synthesis (GVS**, fully synthetic videos like Sora's). Detection challenges evolve from visual artifacts in LMV to multi-modal inconsistencies in AVE and higher-level world knowledge violations in GVS. The core proposal is a **Vision-Language Dual-View framework** with four hierarchical layers: 1. **Layer 1 (Intrinsic Visual Cues):** Analyzes low-level signal statistics, noise patterns, and physiological signals. 2. **Layer 2 (Spatiotemporal Consistency):** Checks for temporal coherence in object motion and scene dynamics. 3. **Layer 3 (Cross-Modal Consistency):** Verifies alignment between video, audio, and text within the video. 4. **Layer 4 (Language-Guided World-Level Reasoning):** Uses external knowledge, facts, and physical laws to judge semantic plausibility and factual correctness. The survey traces a shift in detection focus from lower layers (1 & 2) toward higher, language-involved layers (3 & 4). It also reviews evolving evaluation metrics and datasets tailored for each video paradigm. The conclusion advocates for a **dynamic, evidence-first detection system** that moves beyond simple classification. Future trustworthy detection requires combining visual evidence (from CV) with semantic reasoning and explanation (from NLP & multimodal AI), ultimately creating traceable and explainable judgments about a video's adherence to real-world constraints.

marsbit15m ago

How to Detect AI-Generated Videos? A Review of Dynamic, Traceable, and Explainable Detection Systems

marsbit15m ago

It Turns Out the First Real-World Application of AI x Crypto is in Security Auditing

The article explores the surprising trend where AI's first major impact on crypto has been in security auditing, not in areas like trading or analytics. It details how AI-powered tools are dramatically lowering the barrier to finding smart contract vulnerabilities, enabling attackers to scan thousands of contracts and execute exploits within minutes. This has rendered traditional, manually-produced audit reports with their month-long validity periods increasingly obsolete, creating a critical "structural crack" in the old security model. Cases like Drift Protocol and KelpDAO show that even extensively audited protocols can be hacked through social engineering, operational flaws, or infrastructure misconfigurations beyond pure code review. Attackers are also using AI to find and exploit vulnerabilities in years-old, deployed contracts. Notably, OpenZeppelin's co-founder has expressed a grim view that "all DeFi is insecure" due to AI's asymmetric advantage. In response, the audit industry is undergoing a fundamental shift. While there's a short-term spike in defensive re-audits, the long-term business model is changing. Firms are developing AI-assisted systems and moving from one-time report deliveries towards embedded, continuous services like real-time monitoring and formal verification. Examples include AI tools uncovering critical, previously missed vulnerabilities in heavily audited protocols like Curve Finance and Zcash. The conclusion is that security must become a continuous investment, not a one-time checkbox, and audit firms must rapidly evolve their tools and service models to survive.

marsbit21m ago

It Turns Out the First Real-World Application of AI x Crypto is in Security Auditing

marsbit21m ago

Never expected that the first tangible application of AI x Crypto is in security auditing

Unexpectedly, the initial major application of AI in the Crypto sphere has turned out to be security auditing. In 2026, DeFi has faced significant security challenges, with 121 hacking incidents resulting in approximately $942 million in losses. While AI was expected to first impact areas like quantitative trading, its initial breakthrough has instead transformed security auditing by drastically lowering the cost and skill barrier for finding smart contract vulnerabilities. The traditional audit model is facing obsolescence. Advanced AI models, such as Claude Mythos, enable attackers to scan thousands of contracts and identify vulnerability patterns at scale, compressing the time from discovery to execution to mere minutes. This renders the month-long validity of traditional audit reports ineffective. Notably, attacks now frequently target well-audited, established protocols by exploiting business logic flaws, operational security weaknesses, and even years-old historical contracts, demonstrating that old audit reports offer zero protection. This pressure is forcing a fundamental shift in the industry. In the short term, a wave of defensive re-auditing is occurring, driven by projects seeking to meet new AI-era security standards and regulatory requirements. In the long run, audit firms' business models are diverging. The one-time report delivery model is declining in value, as evidenced by platforms like Code4rena shutting down. Leading firms are now pivoting towards AI-powered defense, integrating continuous monitoring, real-time on-chain risk detection, and embedding security directly into the development phase, as seen with tools like OpenZeppelin's Skills system. Ultimately, the era of "audit once, secure forever" is over. Security must become a continuous, embedded infrastructure investment for projects. For audit companies, survival depends on proactively transforming from traditional service providers into platforms offering AI-native, ongoing security solutions.

链捕手29m ago

Never expected that the first tangible application of AI x Crypto is in security auditing

链捕手29m ago

$3M Exploit Hits Polymarket: Users to Receive Full Refunds After Third-Party Breach

Polymarket will fully reimburse users affected by a front-end exploit that stole approximately $3 million in crypto assets. The company stated the incident was not a flaw in its core protocol but a supply chain attack. A compromised third-party vendor injected a malicious script into the platform's front-end for a limited number of users, allowing the attacker to drain funds from about 15 wallets while they interacted with the site. The stolen assets, primarily Polymarket's pUSD stablecoin, were bridged to Ethereum and converted to roughly 1,893 ETH. This marks the second security incident for Polymarket in under two months, following a separate $700,000 loss. The event highlights growing risks associated with third-party dependencies in the crypto industry.

TheNewsCrypto30m ago

$3M Exploit Hits Polymarket: Users to Receive Full Refunds After Third-Party Breach

TheNewsCrypto30m ago

Trading

Spot

Hot Articles

What is $BITCOIN

DIGITAL GOLD ($BITCOIN): A Comprehensive Analysis Introduction to DIGITAL GOLD ($BITCOIN) DIGITAL GOLD ($BITCOIN) is a blockchain-based project operating on the Solana network, which aims to combine the characteristics of traditional precious metals with the innovation of decentralized technologies. While it shares a name with Bitcoin, often referred to as “digital gold” due to its perception as a store of value, DIGITAL GOLD is a separate token designed to create a unique ecosystem within the Web3 landscape. Its goal is to position itself as a viable alternative digital asset, although specifics regarding its applications and functionalities are still developing. What is DIGITAL GOLD ($BITCOIN)? DIGITAL GOLD ($BITCOIN) is a cryptocurrency token explicitly designed for use on the Solana blockchain. In contrast to Bitcoin, which provides a widely recognized value storage role, this token appears to focus on broader applications and characteristics. Notable aspects include: Blockchain Infrastructure: The token is built on the Solana blockchain, known for its capacity to handle high-speed and low-cost transactions. Supply Dynamics: DIGITAL GOLD has a maximum supply capped at 100 quadrillion tokens (100P $BITCOIN), although details regarding its circulating supply are currently undisclosed. Utility: While precise functionalities are not explicitly outlined, there are indications that the token could be utilized for various applications, potentially involving decentralized applications (dApps) or asset tokenization strategies. Who is the Creator of DIGITAL GOLD ($BITCOIN)? At present, the identity of the creators and development team behind DIGITAL GOLD ($BITCOIN) remains unknown. This situation is typical among many innovative projects within the blockchain space, particularly those aligning with decentralized finance and meme coin phenomena. While such anonymity may foster a community-driven culture, it intensifies concerns about governance and accountability. Who are the Investors of DIGITAL GOLD ($BITCOIN)? The available information indicates that DIGITAL GOLD ($BITCOIN) does not have any known institutional backers or prominent venture capital investments. The project seems to operate on a peer-to-peer model focused on community support and adoption rather than traditional funding routes. Its activity and liquidity are primarily situated on decentralized exchanges (DEXs), such as PumpSwap, rather than established centralized trading platforms, further highlighting its grassroots approach. How DIGITAL GOLD ($BITCOIN) Works The operational mechanics of DIGITAL GOLD ($BITCOIN) can be elaborated on based on its blockchain design and network attributes: Consensus Mechanism: By leveraging Solana’s unique proof-of-history (PoH) combined with a proof-of-stake (PoS) model, the project ensures efficient transaction validation contributing to the network's high performance. Tokenomics: While specific deflationary mechanisms have not been extensively detailed, the vast maximum token supply implies that it may cater to microtransactions or niche use cases that are still to be defined. Interoperability: There exists the potential for integration with Solana’s broader ecosystem, including various decentralized finance (DeFi) platforms. However, the details regarding specific integrations remain unspecified. Timeline of Key Events Here is a timeline that highlights significant milestones concerning DIGITAL GOLD ($BITCOIN): 2023: The initial deployment of the token occurs on the Solana blockchain, marked by its contract address. 2024: DIGITAL GOLD gains visibility as it becomes available for trading on decentralized exchanges like PumpSwap, allowing users to trade it against SOL. 2025: The project witnesses sporadic trading activity and potential interest in community-led engagements, although no noteworthy partnerships or technical advancements have been documented as of yet. Critical Analysis Strengths Scalability: The underlying Solana infrastructure supports high transaction volumes, which could enhance the utility of $BITCOIN in various transaction scenarios. Accessibility: The potential low trading price per token could attract retail investors, facilitating wider participation due to fractional ownership opportunities. Risks Lack of Transparency: The absence of publicly known backers, developers, or an audit process may yield skepticism regarding the project's sustainability and trustworthiness. Market Volatility: The trading activity is heavily reliant on speculative behavior, which can result in significant price volatility and uncertainty for investors. Conclusion DIGITAL GOLD ($BITCOIN) emerges as an intriguing yet ambiguous project within the rapidly evolving Solana ecosystem. While it attempts to leverage the “digital gold” narrative, its departure from Bitcoin's established role as a store of value underscores the need for a clearer differentiation of its intended utility and governance structure. Future acceptance and adoption will likely depend on addressing the current opacity and defining its operational and economic strategies more explicitly. Note: This report encompasses synthesised information available as of October 2023, and developments may have transpired beyond the research period.

459 Total ViewsPublished 2025.05.13Updated 2025.05.13

What is $BITCOIN

Discussions

Welcome to the HTX Community. Here, you can stay informed about the latest platform developments and gain access to professional market insights. Users' opinions on the price of BTC (BTC) are presented below.

活动图片

Top Questions