Dubai, UAE — The emergence of autonomous trading as a practical capability is reshaping how capital is deployed in crypto markets. CoinQuant, the Dubai-based AI trading platform, is responding by upgrading from a no-code trading tool to a unified trading intelligence architecture that serves both human traders and autonomous AI agents. The move signals a broader shift in the market: as agents move from prototype experiments to live execution, a rigorous infrastructure for validation, risk management, and data processing becomes essential.

CoinQuant says more than 15,000 users have engaged with its platform since launch. Founder and CEO Maan Ftouni emphasizes that autonomous trading is no longer purely theoretical, but the next phase requires a defensible operating framework. “Autonomous trading is happening,” Ftouni notes, “but the next phase requires structured validation, disciplined risk management, and intelligence infrastructure. That is what CoinQuant delivers.”

Structured validation bridges intent and capital

As AI agents increasingly connect directly to exchanges and wallets, they often rely on raw APIs without the benefit of backtesting, risk analysis, or validated data pipelines. CoinQuant introduces a structured intelligence layer that sits between trading intent and live capital deployment. In practice, no strategy — whether crafted by a human or generated by an AI agent — goes live without validation. The workflow embeds backtesting, risk metrics, and parameter optimization so capital is deployed only after a systematic evaluation.

The approach aims to address a core gap in agent-enabled trading: the absence of a disciplined governance framework that can scale across dozens or hundreds of strategies. By enforcing validation steps at every stage, CoinQuant seeks to align automated execution with proven performance under varying market conditions. This emphasis on reliability is particularly critical as agents increasingly operate at high frequency and scale, where unvalidated trades can quickly translate into meaningful losses if not properly constrained.

From no-code to a unified intelligence engine

At the center of CoinQuant’s evolution is a unified intelligence system that blends institutional-grade backtesting, curated market data, optimization — powered by AI — and the firm’s Domain Expert capability. The platform sources data from providers such as Kaiko and Financial Modeling Prep to ensure that traders and agents work from structured, high-quality datasets. On the human side, the interface is designed for natural-language interaction, allowing users to describe, test, optimize, and deploy strategies without writing code. For AI agents, connectivity comes through programmatic APIs and MCP integrations to access data and validate strategies at scale.

According to the company, the goal is simple but ambitious: the same engine that underpins a first backtest for a human user should be able to validate hundreds of strategies for autonomous systems in parallel. “The interface is surface-level. The intelligence engine beneath it is the product,” Ftouni explains. The architecture thus positions CoinQuant as a dual-use platform that can support traditional traders and AI-driven agents within a single, coherent framework.

Two growth vectors driving adoption

CoinQuant frames its expansion as a natural extension of its existing business model. With a growing user base of over 15,000 traders, the platform has demonstrated demand for structured trading intelligence that can guide both manual strategies and autonomous validation workflows. The anonymized, aggregated intelligence layer that emerges as more strategies are built and tested contributes to a proprietary dataset mapping trading intent to logic, validation metrics, and performance outcomes across multiple market regimes. This data backbone is intended to improve decision-making for all users, while protecting individual strategies through anonymization.

Ftouni reiterates that the intelligence engine is designed to power both human and AI-driven validation pipelines. “The same engine that powers a trader’s first backtest can validate hundreds of strategies for autonomous systems in parallel,” he says. This parallel validation capability is what enables CoinQuant to scale its operations without sacrificing rigor, a critical balance as the ecosystem moves toward greater automation and institutional-grade workflows.

Automation on the horizon and a new funding phase

Looking ahead, CoinQuant is preparing to launch an automated strategy execution layer on HyperLiquid, which will become the company’s second major revenue stream. The automation layer is designed to translate validated backtests into live deployments within the same intelligence framework, creating a seamless spectrum from concept to execution. For traders and developers, this integration promises a more efficient path from testing to real-market activity, while for the platform, it represents a significant expansion of the value proposition.

Concurrently, CoinQuant has outlined a plan to raise a $3 million Seed round to accelerate product development, scale infrastructure, and support global growth. The company is also developing HYDRA, a hierarchical multi-agent architecture intended for advanced research, risk modeling, and strategy optimization. Taken together, the initiatives reflect a concerted push to formalize the role of AI and automation in professional trading workflows while building out a robust, scalable backbone that can accommodate increasing volumes and more complex agent configurations.

With more than 15,000 users validating demand for structured trading intelligence, CoinQuant aims to become the intelligence backbone of algorithmic trading in an era where agent-driven activity is becoming mainstream. The combination of a mature validation framework, access to institutional-grade data, and an expanding set of automation capabilities positions the Dubai-based platform as a notable entrant in the field of AI-assisted market making and systematic trading.

What to watch next for traders and investors

As CoinQuant scales its architecture, the key indicators investors will likely focus on are the robustness of the validation pipeline under diverse market conditions, the performance of live deployments enabled by the HyperLiquid integration, and the efficacy of HYDRA in multi-agent coordination and risk modeling. The quality and granularity of the anonymized intelligence dataset will also be a closely watched metric, given its potential to improve cross-strategy validation and inform safer, more scalable automation.

In the near term, the market will also be watching how the automation layer affects execution quality, latency, and capital efficiency when strategies move from backtests to live trading. If CoinQuant can demonstrate consistent, risk-adjusted performance at scale, it could accelerate adoption of agent-driven trading across a broader segment of the crypto ecosystem — from individual traders to professional funds seeking programmable, governance-backed automation.

Readers should keep an eye on how HYDRA develops and how the HyperLiquid integration performs once live deployments begin. The coming months will reveal whether CoinQuant’s unified approach can sustain rigorous validation while delivering the practical automation capabilities that increasingly define the frontier of quantitative crypto trading.

SHIB futures netflow plunged 306% as outflows exceeded inflows, according to CoinGlass derivatives data.

CoinGlass tracked SHIB futures netflow dropping 306%, with the total value of SHIB leaving derivatives exchange wallets outpacing inflows. The metric tracks movement of tokens in and out of derivatives platform wallets and is used as an indicator of how traders are positioning in the perpetual futures market.

The 306% negative netflow signals that derivatives traders are actively reducing exposure rather than opening new leveraged positions. Open interest stands at $61.2 million, with $42,485 in SHIB futures positions liquidated in the latest 24-hour session.

What the derivatives data tells us about SHIB trader sentiment

Negative futures netflow does not necessarily indicate an impending price crash, but it does reflect a reduction in the number of traders willing to hold derivative exposure to SHIB at current prices.

SHIB was trading near $0.00000575 at time of writing, down approximately 54% over the past 12 months from a peak near $0.000012. The token broke below key support near $0.0000054 this week according to technical analysis on CoinMarketCap, raising concern about a possible retest of March 2026 lows.

Crypto.news has reported on over 3 billion SHIB tokens hitting exchanges in a single session earlier this month, adding sell-side pressure as broader crypto market liquidations accelerated.

The pattern of negative futures flow alongside exchange inflows suggests holders are repositioning rather than accumulating. Crypto.news has also covered how declining SHIB futures open interest and funding rate pressure had already signalled weak conviction among derivatives traders in February 2026.

The Shiba Inu (SHIB) price page tracks live movements as the futures data raises questions about SHIB’s near-term direction heading into the US Memorial Day holiday weekend.

Onchain analytics firm Bubblemaps says a Hyperliquid whale linked to former BitForex CEO Garrett Jin and the infamous 10 10 short trade would have been up more than $70 million if he had never traded Ethereum, but is instead sitting on roughly $128 million in net losses after catastrophic ETH longs erased huge prior gains.

In a new onchain breakdown shared on X, Bubblemaps reconstructs the PnL of the wallet cluster it associates with Garrett Jin, arguing that if the trader had simply held BTC and avoided the ETH leverage spiral, his net profit would stand north of $70 million; instead, the account is now “down $128M overall” after a brutal series of Ether trades.

The cluster has been in the spotlight since the so called 10/10 crash on October 10, 2025, when a Hyperliquid whale built massive short exposure into Bitcoin and Ethereum shortly before President Donald Trump announced 100 percent tariffs on Chinese imports, triggering a violent risk off move.

How did a 10 10 legend flip from +$70M to –$128M?

Binance Square’s retrospective on the “10 11 flash crash” notes that the whale held more than 100,000 BTC equivalent and was behind a $735 million BTC short on Hyperliquid, with Arkham Intelligence later estimating between $190 million and $200 million in profit on those shorts across BTC and ETH as prices cratered.

Yahoo Finance separately described the same trader as the “Hyperliquid whale who made nearly $200M on the Oct. 10 crash,” and reported that blockchain sleuths linked the address to Garrett Jin, though Jin denied owning the wallet while acknowledging that he knew the person behind it.

Binance coverage of a March 2025 liquidation recounts how an address on Hyperliquid opened a more than $200 million long position on ETH using 50x leverage, staking about $4.3 million in USDC to control 113,000 ETH before being liquidated in a move that left the protocol itself with a roughly $4 million loss due to insurance fund slippage.

Panoptic’s market intelligence notes and other whale tracking reports suggest that similar oversized ETH longs followed, taking the wallet’s aggregate realized loss on ETH north of $200 million as repeated attempts to time reversals ran into continued volatility and margin calls.

Against that backdrop, Bubblemaps’ claim that the trader swung from a hypothetical +$70 million to –$128 million net is entirely plausible: the original 10 10 BTC short win was massive, but the later ETH leverage series appears to have more than erased it.

Despite the drawdown, the same cluster is back on Hyperliquid with a familiar mix of high conviction bets.

Bubblemaps says a connected address has recently deposited several million dollars of collateral to the perpetuals exchange, bought approximately $10 million worth of HYPE, the platform’s native token, and opened a $38 million short position on privacy coin Zcash (ZEC).

That dovetails with other recent whale tracking reports.

Bitcoin.com News described how a trader dubbed “Evaded” accrued about $7.5 million in profit in under four days from leveraged longs on ZEC and HYPE on Hyperliquid, then rolled into a $38.63 million ETH long using 25x leverage, a position that would be automatically liquidated on a roughly 4 percent adverse move.

Whale Alert and PANews have documented the same address pattern closing profitable HYPE, ZEC and ETH longs for about $4.6 million in gains, then opening a 990 BTC short worth nearly $75 million on Hyperliquid as BTC came under pressure from ETF outflows and derivatives liquidations.

While those reports focus on a pseudonymous trader called Evaded, Bubblemaps’ new thread argues that at least one of these high frequency, high notional Hyperliquid whales can be tied through address clustering and historical flows back to the 10 10 short and the entity it links to Garrett Jin.

The picture that emerges is of a trader who oscillates between periods of spectacular success and ruinous overreach, with the core pattern unchanged: concentrated directional bets on BTC and ETH around macro events, and now similarly aggressive positioning in platform tokens like HYPE and high beta names such as ZEC.

Why this whale matters for markets

On an absolute scale, a net PnL of –$128 million is a rounding error in a multi trillion dollar crypto market, but the 10 10 whale saga is a vivid illustration of how even elite operators with accurate reads on one regime can blow up when they assume the same playbook will work forever.

It also underscores how much of the Hyperliquid and perps venue narrative is driven by a handful of very large accounts whose wins and losses can distort funding rates, liquidity and sentiment for the rest of the market in the short term, especially when they pivot from being the bid to being the offer on assets like BTC, ETH, HYPE or ZEC.

For traders watching flows, Bubblemaps’ work adds another lens: rather than treating each new whale as an isolated story, it invites you to look at the entire career arc of a wallet cluster, and to ask whether you are front running a disciplined asymmetric player or shadowing a gambler who just torched nearly nine figures trying to replay last cycle’s script.

Chris Larsen’s XRP wallets have resumed on-chain activity ahead of Tuesday’s Texas primary runoff.

Ripple co-founder Chris Larsen’s associated wallets have resumed on-chain activity, according to blockchain data, ahead of Tuesday’s Texas Democratic primary runoff. The reactivation draws immediate attention given Larsen’s history of significant XRP transfers at notable market and political junctures.

Larsen serves as executive chairman of Ripple Labs. His estimated 2.58 billion XRP holdings across eight wallets tracked on XRPScan represent one of the largest known individual positions in any single cryptocurrency, worth approximately $3.5 billion at current prices near $1.35.

Why Larsen’s wallet activity draws attention from the XRP community

In January 2025, wallets that had been idle for six to seven years reactivated and sent more than $109 million in XRP to exchanges including Coinbase, Bitstamp, and Bybit. In July 2025, on-chain researcher ZachXBT reported an additional $140 million in XRP transfers from Larsen-linked addresses coinciding with XRP trading near an all-time high above $3.40.

“Since July 17, 2025, an address linked to Ripple co-founder Chris Larsen transferred out 50M XRP ($175M) to four addresses. ~$140M ended up at exchanges/services,” ZachXBT wrote on X in July 2025. Larsen had not commented publicly on today’s activity at time of writing.

Whether the current movement precedes exchange transfers or represents internal wallet management is not confirmed from on-chain data available at time of publication. Crypto.news has covered Ripple CEO Brad Garlinghouse’s legislative activity in 2026 as the Clarity Act moves through Congress.

Crypto.news has also reported on why the Clarity Act’s progress is particularly consequential for XRP, context that gives any Larsen wallet movement added political timing significance ahead of Tuesday’s runoff.

TLDR

• XRP whale transactions worth over $1 million dropped by 57% in nine days.
• The XRP price declined from $1.54 on May 14 to around $1.35.
• The token recorded five consecutive intraday losses for the first time in two months.
• Large transactions fell from 157 trades to just 67 during the period.
• Analyst Ali Martinez linked the drop in whale activity to weakening market participation.

XRP whale activity has dropped sharply over the past nine days as large transactions declined across the network. Data shows trades worth at least $1 million fell by 57% while the XRP price also weakened. The slowdown points to reduced participation from large holders during a period of falling prices.

XRP Whale Activity Drops as Price Records 5 Straight Losses

XRP fell to $1.35 after declining from $1.54 recorded on May 14. The token posted five consecutive intraday losses between May 15 and May 19. The decline marked the first time in over two months that XRP recorded such a streak. The price dropped about 8% during this five-day period. Market analyst Ali Martinez highlighted a drop in large transactions during the same timeframe.

According to the data, whale transactions fell from 157 trades to just 67. These trades each represented transfers worth at least $1 million. This equals a 57% decline in large transaction activity within nine days. The reduction aligned closely with XRP’s downward price movement.

Martinez stated that large investors reduced participation as prices weakened. He added that this drop reflected lower confidence among major holders. The slowdown in trading activity occurred while XRP traded below $1.40. Selling pressure remained steady throughout the period.

Compression Phase Forms as Whales Quietly Accumulate XRP

Martinez described the current market state as a compression phase. He said whales appear to be waiting as the price stabilizes within a tighter range. He noted that such conditions often reduce short-term volatility. They also help establish clear support and resistance levels. Despite fewer large trades, some wallets continued accumulating XRP. Data shows selective buying among mid-sized holders during the dip.

Wallets holding between 1 million and 10 million XRP increased their balance. Holdings rose from 3.72 billion XRP to 3.79 billion XRP. This group added about 70 million XRP over the observed period. Smaller whale wallets also increased their holdings slightly.

Addresses holding between 100,000 and 1 million XRP added around 20 million XRP. Their total rose from 6.31 billion XRP to 6.33 billion XRP. Martinez said the accumulation remains limited in impact on price movement. The broader market still reflects reduced activity from larger participants.

He also pointed to a tightening Bollinger Band on the three-day chart. He said it marks the lowest volatility level seen in over a year. Martinez identified $1.50 and $1.29 as key levels to monitor. He called this range a “no-trade zone” in his analysis.

He stated that a close above $1.50 could push XRP toward $1.80. A move below $1.29 could weaken the outlook and test $1.00 support. At the time of writing, XRP continues trading near $1.35 while whale activity remains subdued.

BlackRock recorded its largest Bitcoin ETF outflow of 2026 after steady withdrawals throughout the past week. The asset manager sold more than $1 billion worth of Bitcoin, while the broader ETF market also posted heavy losses. Meanwhile, Bitcoin remained under pressure despite a modest recovery near the start of the week.

BlackRock Leads Weekly Bitcoin ETF Outflows

BlackRock reported continuous Bitcoin sales during every trading day last week. Consequently, the total value of those sales reached approximately $1.01 billion by week’s end. The figure marked the firm’s largest weekly Bitcoin ETF outflow since November 2025.

Data from crypto analytics platform Arkham showed BlackRock accounted for most of the sector’s withdrawals. Moreover, the broader Bitcoin ETF market experienced significant selling activity across multiple funds. Market participants reduced exposure as volatility increased across digital assets.

Bitcoin faced persistent downward pressure during the same period. As a result, ETF demand weakened despite BlackRock maintaining its leading market position. The latest withdrawals reflected a notable shift from stronger inflows seen earlier this year.

The outflow trend emerged as cryptocurrency prices struggled to sustain momentum. Furthermore, several major digital assets traded in negative territory throughout much of the week. The market environment contributed to reduced demand for spot Bitcoin ETFs.

Institutional activity played a major role in the week’s market performance. Consequently, large-scale fund withdrawals added pressure to Bitcoin and related investment products. The combined ETF outflow reached approximately $1.26 billion during the reporting period.

BlackRock represented the largest share of those withdrawals. Moreover, the fund manager continued to dominate overall Bitcoin ETF holdings despite recent selling activity. The latest figures highlighted the scale of the market’s recent shift.

Bitcoin Holds Above Key Levels Despite Selling Pressure

Bitcoin traded at $77,443 at the time of reporting. However, the cryptocurrency remained well below levels seen during stronger periods earlier this month. The price still managed a modest gain of 0.45% from recent lows.

The asset began the month with positive momentum across major exchanges. However, sentiment weakened as volatility returned to the broader cryptocurrency market. Selling pressure increased as prices struggled to maintain upward movement.

Several market indicators pointed to growing uncertainty across digital assets. Consequently, traders adjusted positions while risk appetite declined. Bitcoin faced resistance as buyers attempted to stabilize recent losses.

The recent ETF withdrawals added another challenge for the market. Moreover, reduced institutional demand coincided with weaker price performance across major cryptocurrencies. The combination created additional pressure on Bitcoin’s short-term outlook.

Market forecasts remained divided regarding Bitcoin’s next move. Some analysts expected consolidation near current levels, while others projected further declines. Meanwhile, resistance levels continued to limit stronger recovery attempts.

Bitcoin maintained support above key price zones despite the recent weakness. However, continued selling activity could influence future market direction. The cryptocurrency remained sensitive to both institutional flows and broader market sentiment.

Market Context Highlights Changing Institutional Activity

Spot Bitcoin ETFs played a significant role in Bitcoin’s performance throughout the past year. Consequently, inflows and outflows often influenced short-term market sentiment and trading activity. Large fund movements frequently attracted attention across financial markets.

BlackRock emerged as the dominant participant in the Bitcoin ETF sector after its launch. Moreover, the firm’s products consistently attracted substantial capital compared with competitors. That position made recent withdrawals particularly notable.

The latest outflows followed months of stronger institutional participation. However, changing market conditions encouraged a more defensive approach among large market participants. As a result, Bitcoin ETFs experienced one of their weakest weeks of 2026.

The broader cryptocurrency market continues to navigate heightened volatility. Meanwhile, Bitcoin remains the primary benchmark for digital asset performance. Future ETF flow data will likely remain an important factor for market direction.