Hyperliquid’s market share surges to 33% – Can HYPE target $36 next?

ambcryptoОпубліковано о 2026-01-31Востаннє оновлено о 2026-01-31

Анотація

Hyperliquid's market share surged from 18% in December to 33% by the end of January, driven by the introduction and success of its equity and commodity perpetuals (perps). Non-crypto assets, such as silver and gold, now account for 30% of the platform's trading volume, positioning it as a key cross-asset trading platform. This growth has positively impacted the native token HYPE, with increased trading volume generating higher fees, which fuel token buybacks and burns. Weekly revenue rose from $11 million to $15.5 million, and HYPE's price increased by 70%. Maintaining support above $28 could lead to a breakout toward $36, while a drop below may push it back to the $20-$28 range.

Hyperliquid [HYPE] has regained a portion of the market share it lost in 2025 following heated competition from Aster [ASTER], Lighter [LIT], and other rivals.

According to Dune data, the platform’s market dominance rose from a recent low of 18% seen in December to over 33% at the end of January.

That’s a 15% jump in market share, thanks to booming equity perpetuals (perps) that have positioned it as a key cross-asset platform.

How equity perps fueled Hyperliquid’s growth

Hyperliquid was initially focused on crypto perps or derivatives that allow traders to speculate on prices with leverage.

They are called perpetuals because they don’t expire with strict deadlines like Options, so one can hold them indefinitely, provided they pay fees to keep the positions open.

The platform unveiled a similar offering for equity and commodities via an upgrade, HIP-3, enabled by third-party integrations.

Interestingly, the recently volatile precious metals market has cemented Hyperliquid as a crucial cross-asset trading platform.

On Friday, silver and gold ranked among the top five assets by trading volume on Hyperliquid. Silver traded $3 billion in volume, while gold closed at nearly $700 million. The other top assets were Bitcoin, Ethereum, and HYPE, while Solana [SOL] ranked sixth.

According to crypto VC partner and trader McKenna, 30% of Hyperliquid’s overall trading volume is driven by non-crypto assets. He added,

“Let me repeat, Hyperliquid will bring in more daily volume from TradFi perpetuals than digital asset perpetuals.”

Impact of the equity perps boom on HYPE

The equity perps boom was expected to be net positive for the native token, HYPE.

It is a bullish catalyst because the higher the equity perps’ trading volume climbs, the more fees are generated, which drives HYPE buybacks and burns.

In fact, DeFiLlama data showed the positive correlation between the recent rebound in generated revenue, perps volume, and HYPE price.

The average weekly revenue has increased from $11 million to $15.5 million, and the HYPE price has mooned by 70% over the same period.

On the price charts, the altcoin had given back some of the gains amid bearish pressure on Bitcoin. But defending $28 zone as support could reinforce a potential breakout above $36 if the equity perps’ traction extends.

However, breaking below $28 support would invalidate the bullish outlook and trap HYPE back in the December price range of $20-$28.

Final Thoughts

Hyperliquid’s market share has increased from 18% to 33% amid equity and commodity perps trading surge
Non-crypto assets now account for 32% of Hyperliquid’s overall trading volumes

Пов'язані питання

QWhat was Hyperliquid's market share at the end of January, and what was this a significant increase from?

AHyperliquid's market share rose to over 33% at the end of January, which was a significant increase from a recent low of 18% seen in December.

QWhat new type of perpetuals, introduced via HIP-3, was a key driver behind Hyperliquid's recent growth?

AThe introduction of equity and commodities perpetuals (perps) via the HIP-3 upgrade was a key driver behind Hyperliquid's recent growth.

QAccording to the data, what percentage of Hyperliquid's overall trading volume is now driven by non-crypto assets?

AAccording to the data, 30% of Hyperliquid's overall trading volume is now driven by non-crypto assets.

QHow does the increase in trading volume from equity perps directly benefit the native token, HYPE?

AThe increase in trading volume generates more fees, which are used to drive HYPE token buybacks and burns, making it a bullish catalyst for the token's price.

QWhat is the critical price level for HYPE that, if broken, would invalidate the bullish outlook and trap it in its December price range?

AThe critical price level is $28. Breaking below this support would invalidate the bullish outlook and could trap HYPE back in the December price range of $20-$28.

Пов'язані матеріали

Zcash Suffers Historic Collapse As Billions Vanish From Market Value

Zcash, a privacy-focused cryptocurrency, suffered a historic collapse in price, losing over 50% of its value in 24 hours and erasing billions from its market cap. The dramatic sell-off was triggered by the disclosure of a major vulnerability in the Zcash Orchard privacy pool that had remained undetected since May 2022. A security researcher, using AI, developed a proof-of-concept to generate counterfeit ZEC. While the bug was patched by June 2, Zcash's privacy design makes it impossible to verify if any fake coins were minted before the fix, fueling market panic and uncertainty. This event highlights the trade-off between privacy and transparency. In response, Shielded Labs is exploring a network upgrade to allow supply verification. Despite the crisis, proponents argue that the discovery by world-class security researchers demonstrates the network's commitment to proactive hardening and resilience.

bitcoinist29 хв тому

Zcash Suffers Historic Collapse As Billions Vanish From Market Value

bitcoinist29 хв тому

Has the 'Digital Gold' Narrative for BTC Failed?

**Title: Has the "Digital Gold" Narrative for Bitcoin Failed?** The article argues that Bitcoin's "digital gold" narrative remains valid despite a recent sharp price decline (from a peak near $126k in Oct 2025 to briefly under $61k in Feb 2026). It presents a long-term investment framework based on three core points: **1. Viewing Bitcoin as an Asset:** Bitcoin is presented as a superior potential store of value compared to gold. Key arguments are its absolute scarcity (21 million cap), superior portability, and transparent auditability via its public ledger. While acknowledging its current use in early, volatile stages (~3-4% global adoption), the author draws parallels to the early, disruptive phases of the internet and e-commerce. **2. Understanding the Recent Downturn:** The current ~50% correction is framed as a predictable, consensus-driven cycle following its post-halving peak (the 2024 halving preceded the Oct 2025 high). A crucial factor is a historic "changing of hands": the influx of new institutional buyers via ETFs allowed early, low-cost holders (miners, OG believers) to take profits. The author notes that while severe, Bitcoin's historical drawdowns (e.g., 93% in 2011, 77% in 2021-22) have been progressively smaller, suggesting maturing holder structure and decreasing volatility over time. **3. The Long-Term Perspective:** The long-term thesis hinges on Bitcoin capturing a portion of gold's market value. With Bitcoin's market cap at ~$1.4 trillion (at $70k) versus gold's ~$20 trillion, significant upside potential exists if the "digital gold" narrative is partially realized. However, the author strongly cautions that short-term risks remain, the bottom is unpredictable, and high volatility is inherent. The real risk is not Bitcoin failing but poor personal position management (over-leverage, wrong capital) and a lack of deep understanding, which can force investors out during severe downturns. The conclusion uses Amazon's 95% crash post-2000 dot-com bubble and subsequent 42x recovery as an analogy. The ultimate question is not if Bitcoin's price will rise, but if an investor's strategy and conviction can withstand the volatility to see the long-term play out. The recent divergence (gold up, Bitcoin down) is posed not as a narrative failure, but as potential evidence of this ongoing, painful transition from a speculative asset to a mainstream allocation.

marsbit55 хв тому

Has the 'Digital Gold' Narrative for BTC Failed?

marsbit55 хв тому

Has BTC's 'Digital Gold' Narrative Failed?

The article discusses Bitcoin's "digital gold" narrative, its recent price drop, and long-term outlook through the perspective of "Jason". It argues the narrative is not a failure but that Bitcoin represents a superior, new asset class due to its fixed supply (21 million), portability, and auditability. The piece compares its current ~3-4% global adoption rate to early internet/e-commerce, suggesting significant growth potential. Regarding the 2025-2026 price decline (from ~$126k to briefly under $61k), the author views it as a predictable, consensus-driven sell-off within Bitcoin's ~4-year cycle post-halving, exacerbated by a major "handover" from early, low-cost holders to new institutional buyers via ETFs. A key observation is that historical peak-to-trough drawdowns have lessened over time (e.g., 93% in 2011 to ~50% in 2026), indicating maturing volatility as holder structure changes. For the long term, the author uses a simple framework: Bitcoin's total market cap (~$1.4T at $70k) is only about 7% of gold's (~$20T). Even capturing 30-50% of gold's value would imply substantial upside. However, the article strongly cautions against viewing this as investment advice, emphasizing extreme volatility and the critical importance of risk management, position sizing, and deep fundamental understanding to survive severe drawdowns. It concludes by drawing a parallel to Amazon's 95% crash in 2000 and subsequent 42x recovery, stressing that the key is surviving market cycles to realize long-term potential.

链捕手1 год тому

Has BTC's 'Digital Gold' Narrative Failed?

链捕手1 год тому

From Code to Cognition: A Ten-Thousand-Word Guide to the Evolution of the Robot Brain

"From Code to Cognition: The Evolution of Robot Brains" The journey of robotic intelligence has shifted dramatically from manually coded systems to AI-driven brains. For decades, robots relied on layered software stacks—perception, state estimation, planning, control—each handcrafted. While predictable, they lacked adaptability. The 2010s saw deep learning revolutionize perception (e.g., object detection) and control (via reinforcement learning), but learned skills remained narrow. The arrival of Large Language Models (LLMs) marked a turning point. LLMs acted as high-level planners, interpreting natural language instructions and generating sequences of actions for traditional robotic systems to execute. However, true integration came with Visual-Language-Action (VLA) models, which fused vision, language, and motion prediction into a single network. Pioneered by models like RT-2 and open-source projects like OpenVLA, VLAs enable robots to reason and act directly from visual input and commands. The most advanced humanoid robots now employ a "dual-brain" architecture: a slow-thinking, large VLA (System 2) for reasoning and planning, and a fast-reacting, small network (System 1) for high-frequency motion control, sometimes with an even lower-level System 0 for balance. This split balances cognition with the physics of real-time movement. Computation is split between onboard hardware (e.g., NVIDIA Jetson) for safety-critical control loops and cloud/edge servers for non-critical tasks like learning and interfaces. A crucial driver is the open-source ecosystem—models like GR00T and OpenVLA allow startups to build upon pre-trained brains and fine-tune them with their own data, accelerating development. Despite progress, current systems struggle with recovery from errors, sample inefficiency, and long-horizon tasks. This has spurred the rise of **World Models**—neural networks that predict the consequences of actions. By simulating possible futures before acting (like NVIDIA Cosmos or Meta V-JEPA), robots can plan, recover, and generalize better. This represents the next frontier: shifting intelligence from learned reactions to an internal model of physics and cause-and-effect. The field is rapidly evolving. While not yet at its "ChatGPT moment," the convergence of cheaper hardware, scalable simulation, and world models points toward robots that are increasingly capable, adaptive, and useful. The question is shifting from "what can robots do?" to "what *should* they do?"

marsbit1 год тому

From Code to Cognition: A Ten-Thousand-Word Guide to the Evolution of the Robot Brain

marsbit1 год тому

AI Bubble Is Bursting

The AI Bubble is Bursting: A Necessary Purge on the Path to Ubiquitous Intelligence Market volatility has reignited debates about an AI bubble, with figures like Ray Dalio pointing to high valuations. However, this parallels the dot-com bubble, which, despite its crash, laid the physical infrastructure for today's internet era. The current AI investment frenzy, with tech giants planning trillions in infrastructure spending far outstripping current AI application revenues, appears similarly imbalanced. This 'bubble' is seen as an inevitable phase for a disruptive technology, paying the "innovation tax." Critically, AI inference costs have plummeted over 99.7% since 2023, making intelligence nearly free at the margin. This hasn't reduced spending but has instead unlocked massive new demand, as seen in enterprise AI cloud expenditure tripling. This follows the Jevons Paradox: efficiency gains lead to greater total consumption. The market is now entering a cleansing phase, weeding out speculative ventures lacking real moats. The deeper shift is a move from capital expenditure (CapEx) on hardware to value creation in operational expenditure (OpEx) through AI applications that solve real industry problems. While infrastructure valuations are high, rapid earnings growth from widespread AI adoption across sectors—from manufacturing and finance to law and healthcare—may digest these valuations over time. Ultimately, this creative destruction will leave behind robust infrastructure and optimized models, cheaply powering an AI-augmented future for all industries, much as the internet became indispensable after its own bubble burst. The core productive potential remains undiminished.

链捕手1 год тому

Торгівля

Спот

Ф'ючерси