Crypto World
Why AI Integration is Now Mandatory for Crypto Exchange Development?
MEXC’s AI suite, launched in August 2025, marks the advent of a new standard in cryptocurrency exchange development. The leading crypto exchange software recognized that legacy crypto exchanges aren’t losing users because they’re slow, but because they’re not innovating.
It’s a 2019-era assumption that traders will stay if you offer enough trading pairs, decent liquidity, and a clean UI.
A crypto exchange software in 2026 that merely executes orders is no longer enough. Markets move in milliseconds, narratives shift in minutes, and information spreads faster than human reaction time.
Traders are left drowning in data, juggling between charts, indicators, on-chain dashboards, social feeds, whale trackers, and news alerts. Since trading decisions require them to integrate several tools across different platforms, exchanges just become a trading engine, which is easy to replace.
At a higher level, Institutional investors own an AI-powered trading infrastructure that detects patterns in seconds, analyzes indicators, and executes positions. Retail traders don’t have access to such tools, which is why they struggle to compete in markets. By integrating AI-tools inspired by MEXC, cryptocurrency exchange software can enable average users to access institutional-grade analysis, leveling the playing field for retail traders and institutional desks.
Why AI is no longer optional in Crypto Exchange Development?
For years, AI in crypto exchange was treated as a cosmetic upgrade. Crypto exchanges experimented with basic bots, basic alerts, surface-level analytics, and labelled them intelligent. The phase is now over. What changed isn’t the technology alone but the market and trader behavior as well.
Modern crypto markets are events and narrative-driven and reflexive. Prices react not just to order flow, but to tweets, governance proposals, whale movements, ETF speculations, regulatory headlines, and memecoin virality. When the retail reaction time cannot scale to this velocity, it is not the traders’ constraint but a trading infrastructure limitation.
AI embedded at the cryptocurrency exchange development infrastructure level can transform trading platforms from a passive execution venue to an active intelligence layer. And this shift addresses four structural weaknesses that traditional exchange systems cannot solve on their own.
1. Information Latency
Markets often react to new developments before most traders have had time to interpret them. By the time someone finishes reading the headline, the price adjustment may already be in progress or nearly complete.
AI-powered cryptocurrency exchange software can potentially reduce this lag by building agents that:
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- Continuously scan multi-source inputs (news feeds, social streams, wallet flows, macro signals)
- Classify relevance in real time
- Rank signals based on the probability of market impact
By doing this, they can list top trading pairs, high-potential-tokens and best trading strategies in real time. This does not replace traders but compresses the delay between signal emergence and signal recognition.
2. Cognitive Overload
Data abundance has become counterproductive. As stated above, traders juggle charts, on-chain dashboards, sentiment trackers, and news feeds across multiple platforms. Scattered data slows decisions and increases error rates.
Smart AI integrations in crypto exchange development address this by:
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- Filtering low-signal noise
- Correlating sentiment, capital flow, and price structure
- Presenting contextualized insight instead of raw feeds
This way, AI-powered news boards or chat assistants present real-time structured interpretations before the traders, who are just one click away from executing a trade.
3. Non-Linear Market Risk
Crypto volatility rarely unfolds in straight lines. Liquidation cascades, sentiment reversals, and liquidity shocks amplify themselves. Static thresholds and rule-based triggers often struggle in these environments.
Strategically crafted and integrated AI models in crypto exchange software, by contrast, adapt dynamically:
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- Recognizing pattern shifts across regimes
- Updating probability distributions as conditions change
- Anticipating stress conditions rather than reacting after breakdown
Such models can be leveraged to create smart trading assistants for traders and intelligent risk management and security mechanisms for cryptocurrency exchange software.
4. Retention in a Low-Switching-Cost Environment
Crypto users face almost zero friction when switching platforms. Most platforms today have brief onboarding cycles and no custodial lock-ins. Funds move instantly. APIs connect everywhere. Liquidity is increasingly multi-platform.
In this environment, execution quality alone is insufficient for differentiation as a crypto exchange software. Traders increasingly prefer platforms that assist decision-making by surfacing opportunities, contextualizing risk, and shortening analysis time.
AI-powered trading integration in cryptocurrency exchange development addresses this retention problem by embedding decision-support into the trading experience itself. When an exchange:
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- Surfaces relevant opportunities in real time
- Contextualizes price movements automatically
- Flags risk before exposure escalates
It reduces the trader’s dependency on external tools, slashing the chances of crypto exchange software abandonment.
What Role Does AI Play in Modern Crypto Exchange Infrastructure?
AI in cryptocurrency exchange development isn’t about adding more indicators or prettier dashboards, but giving your exchange a brain of its own. It compresses the chaos into clarity by detecting signals before they appear and linking events, sentiment, on-chain flows, and price action into a single decision context.
Its impact spans core infrastructure, compliance logic, capital protection systems, and trader cognition layers. Let’s locate exactly where it operates inside the stack when a cryptocurrency exchange software implements MEXC-inspired AI tools integration.
| Layer | AI Role | Deployment Location |
|---|---|---|
| Execution Layer | Slippage prediction | Off-chain engine |
| Surveillance | Behavioral modeling | Backend analytics layer |
| Risk Engine | Predictive liquidation scoring | Core risk module |
| Intelligence Layer | Signal aggregation & NLP | Data processing cluster |
1. AI at the Matching Engine & Trade Execution Layer
The order matching engine is traditionally deterministic. It matches orders based on a price-time priority and predefined logic, which fails under regime shifts, liquidity shocks, and high-volatility bursts.
- AI-Augmented Adaptive Order Matching Under Volatile Conditions
AI models analyze:
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- Real-time order book depth changes
- Liquidity imbalances
- Spread expansion velocity
Instead of blindly matching based on static rules, an AI-based order matching system can:
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- Adjust routing logic during volatility spikes
- Detect spoof-driven depth distortions
- Optimize execution sequencing under stress
Implementing this during crypto exchange development improves order fill quality without rewriting trading fundamentals.
- Slippage Prediction & Execution Path Optimization
Rather than calculating slippage after execution, AI models estimate:
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- Expected impact cost
- Liquidity fragmentation
- Cross-market price deviations
AI-enhanced execution engines in crypto exchange software can then:
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- Split large orders dynamically
- Delay or accelerate routing based on impact probability
- Optimize for reduced adverse selection
This results in measurable improvement in order execution efficiency.
- Load-Aware & Volatility-Sensitive Fee Logic
Static fee tiers appear flat and irrelevant. AI/ML-based load-aware and volatility-sensitive adjust fee based on:
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- Network congestion
- Liquidity supply elasticity
- Market stress indicators
This enables cryptocurrency exchange software to:
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- Protect liquidity during extreme volatility
- Incentivize depth when spreads widen
- Stabilize trading conditions programmatically
Power Up Your Crypto Exchange with AI — Start Building Today
2. AI in Market Surveillance & Trade Integrity Systems
Rule-based surveillance systems rely on predefined thresholds. Manipulators evolve faster than static rules, making them irrelevant in the face of rapidly shifting markets. AI introduces behavioral modeling and real-time market surveillance systems.
- Moving Beyond Static Rule-Based Surveillance
Instead of detecting fixed patterns, AI-based models integrated in crypto exchange software development learn:
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- Normal order flow behavior per account
- Clustered wallet activity
- Correlated spoof cycles
Anomalies are detected relative to behavioral baselines, not arbitrary thresholds.
- Behavioral Modeling for Wash Trading & Spoofing Detection
AI systems integrated inside cryptocurrency exchange software analyze:
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- Order placement and cancellation cadence
- Volume recycling patterns
- Cross-account coordination signals
This allows crypto exchanges to identify:
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- Synthetic liquidity inflation
- Coordinated wash rings
- Layered spoof walls designed to mislead depth perception
This enables cryptocurrency exchanges to neutralize manipulation before it distorts price formation, safeguarding both liquidity providers and platform credibility.
- Real-Time Intervention vs Post-Trade Enforcement
Traditional enforcement occurs after trades settle. Cryptocurrency exchanges review the activities later and then react. This creates distrust among the exchange users.
AI-powered reaction time intervention systems integrated in crypto exchange software enable:
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- Pre-trade risk scoring
- Order throttling
- Temporary restrictions before damage propagates
This protects both liquidity providers and platform reputation if implemented properly.
3. AI-Powered Risk Engines & Capital Protection
Most liquidation systems in traditional crypto exchange software rely on fixed formulas:
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- If the margin ratio falls below X → liquidate
- If maintenance margin is breached → force close
This breaks during cascading leverage events, where price drops trigger liquidations, which trigger further price drops.
AI upgrades the liquidation engine from a static trigger system to a dynamic stress model.
- Predictive Liquidation Modeling
Instead of waiting for accounts to cross a fixed threshold, AI-powered liquidation models continuously evaluate how close an account is to becoming unstable under changing market conditions.
They analyze:
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- Volatility clustering – Is volatility accelerating in a way that increases liquidation probability?
- Position concentration – Is the trader heavily exposed to a single high-risk asset?
- Correlated leverage exposure – Are multiple leveraged positions likely to fall together?
This allows the system to:
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- Flag accounts likely to breach the margin before they actually do
- Adjust maintenance requirements gradually instead of triggering sudden liquidation
- Issue early warnings when risk probability spikes
The practical impact is fewer sudden liquidations and reduced cascade amplification during stress events.
- Volatility-Aware Leverage & Margin Controls
In traditional crypto exchange software margin systems, leverage limits are static. A trader can use 20× leverage regardless of whether volatility is low or exploding.
AI allows the leverage policy to adapt in real time based on:
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- Current volatility regime
- Liquidity depth stability
- Funding rate stress signals
For example:
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- During extreme volatility, allowable leverage can automatically compress
- During stable conditions, it can expand
This prevents systemic overexposure without halting trading activity. The cryptocurrency exchange software remains operational, but risk intensity is regulated dynamically.
- AI-Driven Account Health Scoring
A single margin ratio does not reflect real risk.
AI systems compute a composite risk profile that includes:
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- Asset correlation across open positions
- Cross-market contagion risk
- Liquidity fragility of held assets
- Probability-weighted drawdown scenarios
Instead of treating accounts as either “safe” or “liquidate,” an AI-enhanced cryptocurrency exchange evaluates risk as a probability curve.
That matters because risk is rarely binary. It builds progressively. AI makes that progression measurable.
4. AI-Powered Market Intelligence & Trader Decision Systems
Execution intelligence optimizes how trades are processed. Market intelligence determines which trades get placed in the first place.
This layer sits above the core exchange engine and functions as a decision-compression system. Its role is not to automate trading, but to reduce signal discovery time, contextualize volatility, and quantify probability in environments where information arrives faster than humans can process it.
The problem it solves is not execution but decision latency and fragmented signal interpretation.
A. AI Signal Aggregation & Asset Opportunity Discovery
Traders today monitor dozens of inputs:
-
- On-chain token inflows/outflows
- Social velocity shifts
- Funding rate anomalies
- Derivatives open interest spikes
- Liquidity migration across pairs
Individually, none of these guarantees opportunity. The edge appears when they converge.
AI systems built inside crypto exchange development can:
- Continuously ingest multi-source market data
- Normalize heterogeneous signals (on-chain, sentiment, derivatives)
- Detect confluence clusters where multiple early indicators align
Instead of ranking tokens by volume or price change, the system ranks them by:
-
- Attention acceleration
- Capital rotation probability
- Early-stage momentum asymmetry
This changes asset discovery from reactive scanning to probabilistic opportunity surfacing.
The impact: traders identify rotation before it becomes obvious on the 4H chart.
B. Real-Time Event Intelligence & News Reaction Systems
Modern market catalysts originate outside the order book:
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- Regulatory statements
- ETF developments
- Whale wallet activity
- Protocol upgrades
- Narrative shifts
Traditional cryptocurrency exchange software display price after impact where AI-integrated exchanges perform:
-
- NLP-based classification of incoming events
- Historical pattern comparison against similar past catalysts
- Real-time impact scoring based on liquidity conditions
When a signal crosses defined probability thresholds, the system:
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- Flags the event
- Quantifies potential impact range
- Links context directly to trade interfaces
This reduces the informational advantage gap between institutions and retail participants.
C. Conversational AI for Market Reasoning & Trade Context
Markets are multi-variable systems. Traders often ask layered questions:
- “Why is this token outperforming the sector?”
- “How does this macro event affect L2 assets?”
- “Is this funding spike sustainable?”
Instead of manually correlating data across dashboards, conversational AI:
- Maps natural language queries to structured market datasets
- Performs cross-asset inference
- Produces explainable, data-backed summaries
This accelerates structured reasoning without replacing strategy. The analysis cycles are reduced from minutes to seconds.
D. AI-Augmented Charting & Contextual Market Visualization
Charts traditionally show price. Traders must overlay context manually.
AI-enhanced visualization integrates:
- Event annotations tied to precise time intervals
- Whale transaction overlays
- Sentiment inflection markers
- Pattern probability projections
More importantly, models can assign confidence intervals to detected formations rather than labeling patterns categorically.
Instead of:
“Head and shoulders detected.”
The system communicates:
“Pattern probability: 68% under current liquidity regime.”
That difference matters. It reframes technical analysis from visual intuition to statistical inference.
Takeaway
The next generation of crypto exchange development won’t compete on who has more features. They’ll compete on who helps traders think faster, react earlier, and manage risk before the market turns hostile. That shift from execution-first crypto exchange software platforms to intelligence-driven trading environments is already underway. And exchanges that ignore it aren’t being conservative. They’re falling behind.
Cryptocurrency exchanges that integrate AI natively, on the other hand, transition from being transaction venues to becoming decision engines.
At Antier, we design crypto exchange software infrastructure with this transition in mind. Our AI-ready exchange architectures are built to integrate predictive analytics, behavioral risk modeling, and multi-source signal intelligence directly into the core trading stack, not as surface-level add-ons.
Share your requirements today!
Frequently Asked Questions
01. What is the significance of MEXC’s AI suite launched in August 2025?
MEXC’s AI suite represents a new standard in cryptocurrency exchange development, addressing the need for innovation beyond just offering trading pairs and liquidity, enabling traders to access advanced tools for better decision-making.
02. Why is AI considered essential in modern crypto exchange development?
AI is essential because it transforms trading platforms into active intelligence layers, allowing for real-time analysis and execution, which is crucial in fast-paced markets driven by events and narratives.
03. How does AI integration benefit retail traders compared to institutional investors?
AI integration provides retail traders with access to institutional-grade analysis and tools, leveling the playing field and helping them compete more effectively in markets dominated by institutional investors.
Crypto World
XRP Must Reclaim This Level to End the Bearish Trend
Ripple’s XRP remains under clear bearish pressure, but instead of accelerating lower, the market has transitioned into a compression phase. The price action is now stabilizing near a key psychological floor, with volatility declining as both sides hesitate to commit aggressively.
Ripple Price Analysis: The Daily Chart
On the daily timeframe, XRP’s decisive breakdown below the descending channel’s midline triggered a strong impulsive sell-off that drove the price toward the $1 demand region. That breakdown confirmed a structural shift in favor of sellers. Although a rebound followed, it stalled beneath the $1.5 resistance zone, which now acts as a firm supply area.
The inability to reclaim $1.5 signals that the recent upside move was corrective rather than impulsive. Sellers remain active on rallies, defending overhead supply. As long as XRP trades below $1.5, the broader structure remains tilted to the downside.
Currently, the price is consolidating between $1 and $1.5, with $1 acting as the primary daily demand. A decisive breakdown below $1 could expose the market to deeper downside continuation, while only a strong daily close above $1.5 would shift short-term momentum back in favor of buyers.
XRP/USDT 4-Hour Chart
On the 4-hour timeframe, the rebound from $1 appears as a sharp reaction move fueled by short-term profit-taking. The recovery pushed the price toward $1.5, but the structure shows clear hesitation and rejection inside that supply region.
The market is now compressing between $1 demand and $1.5 supply, forming a range-bound structure. This reflects temporary equilibrium rather than trend reversal. Buyers are defending $1, but they lack the strength to challenge $1.5 convincingly.
If Ripple manages a clean breakout above $1.5 with momentum, the next meaningful supply zone sits around $1.8. Conversely, a breakdown below $1 would likely reintroduce aggressive selling pressure and resume the broader bearish leg.
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Disclaimer: Information found on CryptoPotato is those of writers quoted. It does not represent the opinions of CryptoPotato on whether to buy, sell, or hold any investments. You are advised to conduct your own research before making any investment decisions. Use provided information at your own risk. See Disclaimer for more information.
Crypto World
David Einhorn says the Fed will cut ‘substantially more’ than two times. So he’s betting big on gold

Greenlight Capital’s David Einhorn anticipates the Federal Reserve will issue more interest rate cuts this year than what’s being anticipated and that’s giving him greater confidence in his gold bet.
While rate cut expectations diminished a bit Wednesday following the much better-than-expected January jobs report, traders are still currently pricing in a more than 88% chance that the central bank will make two quarter percentage point cuts by the end of the year, according to the CME FedWatch Tool.
But Einhorn said that the market viewing the latest jobs figures as a reason not to cut is “wrong.” In fact, he thinks the rate cuts number could be higher than that, as he expects Kevin Warsh – President Donald Trump’s pick to succeed Jerome Powell as Fed chair – is going to be able to persuade the committee to do so.
“If we have 4% or 5% inflation, sure, then he won’t be able to persuade people, but otherwise he’s going to argue productivity,” Einhorn said on CNBC’s “Money Movers” to Sara Eisen on Wednesday, adding that Warsh, in his view, is going to take the position of cutting “even if the economy is running hot.”
“I think by the time we get to the end of the year, it’s going to be substantially more than two cuts,” he continued.
The hedge fund manager also owns gold, which sold off at the end of last month after Trump announced Warsh as his nominee for Fed chair, as the move eased anxieties on Wall Street surrounding Fed independence.
The yellow metal – typically viewed as an inflation hedge – has since seen some recovery, with gold futures being up more than 17% this year. That’s after it surged more than 60% in 2025 amid threats to central bank independence as well as heightened geopolitical tensions and unstable trade policy. Since 2024, it’s surged more than 120%.
Gold futures prices since 2024
Einhorn — who gained notoriety in 2008, when he bet against Lehman Brothers at the Sohn Investment Conference just months before the investment bank declared bankruptcy — pointed out that gold has actually gone up over the past couple years as a result of “becoming the reserve asset” to own among central banks around the world.
“U.S. trade policy is very unstable, and it’s causing other countries to say we want to settle our trade in something other than U.S. dollars,” he said.
In the long term, he said that a reason to own gold is due to the fact that the current relationship between our fiscal and monetary policies “don’t make any sense.” He also said that other major developed currencies around the world are “as bad or worse” than the U.S. The U.S. dollar suffered its biggest single-day drop since April 2025 last month after Trump said he wasn’t concerned about the currency’s recent weakness.
“There are some issues that sometime over the next number of years could play out with some of the major currencies,” he said.
Deeming betting on more cuts as “one of the best trades out there right now,” Einhorn said he was also long futures on SOFR (Secured Overnight Financing Rate), which essentially is a bet that short-term rates will continue to go lower.
Crypto World
Beta Technologies (BETA) Stock Rallies as Amazon Discloses 5% Ownership
TLDR
- Beta Technologies stock surged 25.5% after-hours following Amazon’s SEC filing disclosure of 11.8 million shares
- Amazon’s stake represents roughly 5% of Beta’s total outstanding shares in the electric aircraft company
- Beta went public in November 2025 at $34 per share but had fallen 41% year-to-date before the disclosure
- The company competes with Joby Aviation and Archer Aviation in the electric vertical takeoff and landing market
- Wall Street analysts maintain a Strong Buy rating with an average price target of $34.43
Beta Technologies stock rocketed higher after Amazon revealed its investment position in the electric aircraft maker. The disclosure sent shares up more than 25% in extended trading Tuesday.
Amazon owns 11.8 million shares of Beta Technologies. The position equals about 5% of the company’s total stock outstanding.
The stock closed regular trading at $16.77 before jumping to $21.04 after-hours. Beta gained just 0.3% during the standard session.
The revelation came through an SEC filing that detailed Amazon’s holdings. What makes this interesting is that Amazon initially invested in Beta back in 2021.
Amazon’s Clean Energy Play
Amazon backed Beta through its Climate Pledge Fund in 2021. The e-commerce giant has long shown interest in alternative delivery technologies.
Beta Technologies builds electric aircraft designed for quiet operation. This feature could unlock new urban flight paths previously unavailable to traditional aircraft.
The company’s ALIA platform comes in two versions. The ALIA CTOL functions as a conventional fixed-wing electric plane. The ALIA VTOL offers vertical takeoff and landing capabilities.
Beta has also built out charging infrastructure. The company operates over 50 charging sites spread across the U.S. and Canada.
Competitive Landscape
Beta faces direct competition from Joby Aviation and Archer Aviation. All three companies are racing to commercialize electric vertical takeoff and landing technology.
GE Aerospace also holds a major stake in Beta. The jet engine manufacturer was listed as a 5% or more shareholder in Beta’s IPO prospectus.
The two companies are collaborating on hybrid aircraft propulsion systems. GE Aerospace appears extensively in Beta’s regulatory filings.
Beta completed its IPO in November 2025. The company priced shares at $34 each during the public offering.
Stock Outlook
The stock struggled after going public. Shares dropped 41% year-to-date through Tuesday’s close.
Wednesday’s pre-market trading showed continued momentum. Beta stock rallied approximately 17% before the opening bell.
Analyst sentiment remains positive despite recent price weakness. Seven analysts rate Beta a Buy with one Hold recommendation.
The consensus price target stands at $34.43. That implies potential gains of more than 105% from current levels.
Neither Amazon nor Beta responded to media requests for comment. The companies have not disclosed any strategic plans related to the shareholding.
Amazon’s investment history in delivery technology is extensive. The company has tested drone deliveries and continues exploring automation options.
Beta Technologies stock opened Wednesday’s regular session with strong gains following the Amazon stake news.
Crypto World
Best Smart Contract Auditors and Web3 Security Companies (2026): Ranked by Verifiable Public Evidence
Executive Summary
- Top 3 overall: Sherlock, Trail of Bits, OpenZeppelin (ranked by verifiable methodology, published proof of work, depth of verification, scope breadth, and service completeness).
- Rankings reflect comparative positioning, not hype: platforms score higher when they show repeatable processes and transparent artifacts, and score lower when claims can’t be corroborated publicly.
- In this ranking, ‘best smart contract auditors’ and ‘best Web3 security companies’ means the strongest combination of documented methodology, inspectable proof of work, verification depth, scope coverage, and repeatable capacity.
Intro
We wanted to produce the most accurate and verifiable compilation of Web3 smart contract security providers we could: one with clear reasoning and evidence for why each firm deserves its placement. Security vendors are easy to market and hard to evaluate from the outside, so we built a rubric first and then required every inclusion to be supported by public artifacts that a reader can confirm independently.
We focused on observable signals: documented methodology, published work (report libraries, audit archives, contest indices), verification approach (manual review, testing/tooling, formal methods when applicable), breadth of scope across real production surfaces (contracts, integrations, privileged controls, and relevant offchain components), and capacity signals that indicate repeatable execution. Where we draw a 2026 takeaway, it is based on current public positioning and recent public activity visible in those sources rather than hearsay or private claims.
Methodology
We assembled and ranked providers using a reproducible process designed to reduce subjectivity.
Step 1: Candidate set construction. We started from providers that appear consistently across developer shortlists and third-party roundups, then expanded the set through public cross-references (audit archives, contest platforms, tooling documentation, and published reports).
Step 2: Evidence threshold. We validated each candidate using primary sources that directly document (a) how they work (methodology), (b) what work exists (report libraries/archives), and/or (c) how verification is structured (contest rules, program docs, formal verification docs). Providers that could not substantiate core claims with these artifacts were excluded.
Step 3: Scoring rubric. We scored each remaining provider across six dimensions, using comparisons that can be checked from public material:
- Methodology clarity (is the review process described in a concrete, repeatable way?)
- Proof of work & transparency (public reports, archives, consistent published artifacts)
- Verification depth (manual review plus testing/tooling and/or formal methods where applicable)
- Scope breadth (contracts, integrations, privileged controls, and relevant offchain surfaces when in scope)
- Service completeness / unique value proposition (ability to support the full security need for modern protocols—e.g., pre-launch review options, remediation support, and adjacent security programs)
- Capacity signals (evidence of repeatable execution): published volume metrics (e.g., number of audits/contests), size of public report/contest archives, and visible cadence of engagements.
H2 Top Web3 Auditing and Smart Contract Security Providers (Ranked)
- Sherlock — Best choice overall for complete security coverage (development → audit → post-launch)
Sherlock ranks #1 because it supports a full security workflow across development, pre-launch review, and post-launch programs, including Sherlock AI for development-time analysis.
For audits, the model emphasizes matching teams sourced from Sherlock’s 11,000+ researcher network to the protocol’s risk surface and codebase (rather than a fixed team), and it includes fix verification as part of the loop.
For higher-stakes scopes, Blackthorn is described as a tiered engagement that prioritizes a more senior reviewer set.
Public proof points include a Morpho Vaults V2 Blackthorn case study and an Ethereum Foundation audit contest hosted on the platform with public contest pages/announcements, which makes the approach easier to verify end-to-end. That combination – repeatable workflow plus public, inspectable evidence across both high-stakes and ecosystem-scale engagements – is why Sherlock leads this ranking.
- Trail of Bits — Best boutique option for deep systems work across onchain + offchain
Trail of Bits explicitly scopes blockchain security work to include more than contract review, calling out system-level surfaces like oracles, DeFi integrations, upgradeability patterns, and deployment/incident-response considerations.
That matters because many real failures sit at boundaries between contracts and the surrounding infrastructure, not inside a single function. Their positioning is backed by a concrete services breakdown that describes design assessment and security analysis across these system components, rather than generic “we audit smart contracts” language.
In this list, ToB sits near the top because its public scope definition makes it easy to validate what “systems work” means before you hire them.
- OpenZeppelin — Best default private audit firm for process maturity + repeatability
OpenZeppelin publishes a plain-language description of how audits are run, including a line-by-line review model where each line is inspected by at least two security researchers.
They also describe using fuzzing and invariant testing when needed, which is a concrete “verification depth” signal that readers can evaluate without reading between the lines.
OpenZeppelin ranks highly here because the methodology is spelled out clearly enough to be audited itself: you can see the process they claim to follow, not just outcomes.
If you’re choosing an auditor primarily on predictability and documented process, this is one of the more checkable options in the market.
- Zellic (and Zenith) — Best research-driven audit shop, plus ownership of Code4rena
Zellic’s acquisition of Code4rena is a major structural signal because it ties a boutique audit team to a competitive-audit engine, and the acquisition rationale is publicly explained by Zellic.Zellic ranks above pure competitive platforms because it offers both a premium audit path (Zenith) and ownership of the contest channel, but ranks below the top three because its “complete offering” is less explicitly packaged end-to-end (development-time analysis + post-launch programs) than Sherlock’s.
Relative to traditional audit firms, Zellic’s differentiation is research posture plus platform adjacency; the firm adds a staffed audit option and toolchain narrative.
- Certora — Best formal verification option for specification-driven correctness
Certora is best known for formal verification: instead of relying only on review + testing, teams write explicit correctness properties (specs) and use the Certora Prover to check whether the contract can violate them. That’s a distinct verification mode that’s especially useful for protocols where “it seems fine” isn’t good enough: complex accounting, invariants across upgrades, or edge-case state transitions.
Certora publishes detailed primary documentation on the Prover and the Certora Verification Language (CVL), which makes the methodology easy to inspect before engaging. Under this rubric, it earns a top slot because the verification approach is concrete, reproducible, and documented at a level most audit firms don’t expose publicly.
- Cyfrin (CodeHawks) — Best rising competitive audits alternative with clear productization
CodeHawks documents what it is and how it works in its own docs, describing competitive audit marketplaces that can be run as public or private competitions.
That kind of documentation matters for evaluation because it clarifies what the engagement actually looks like (competition structure, participation model), not just marketing outcomes.
CodeHawks ranks on this list because it represents a second major competitive-audit option with visible, structured artifacts that an evaluator can review quickly.
If you’re comparing contest-style review paths, this is one of the more straightforward platforms to validate from primary sources.
- CertiK — Best large-scale security provider (audits + continuous monitoring footprint)
CertiK positions itself as the largest Web3 security service provider and emphasizes both audit services and real-time monitoring (Skynet), giving it a “security program” footprint rather than a pure audit shop identity.Skynet’s public-facing pages (including leaderboards) provide a concrete artifact for the monitoring claim, which is part of why CertiK is commonly mentioned in “best web3 security company” prompts.
CertiK ranks below boutique leaders and research-heavy firms because the rubric here prioritizes depth of verification and transparency of methodology over sheer breadth/scale, and large-scale providers tend to be more variable across engagements.
It still belongs high on the list because buyers often need a provider with a broad menu (audit + monitoring) and high visibility across many ecosystems, and CertiK has verifiable signals for that role.
Concluding Thoughts
Use this ranking as an evidence-based shortlist. “Best” only matters if a provider’s documented methodology and public proof-of-work match the ways your protocol can actually fail: value-moving paths, trust boundaries, integrations, and upgrade surfaces.
A practical way to choose:
- Start by mapping loss paths and trust boundaries. Write down how funds can be drained or stuck, which roles can change behavior, and which dependencies (oracles, bridges, keepers, relayers) can alter outcomes.
- Match the provider to the surface area. System-level scopes (offchain components, bridges, infra) require different skill sets than a contracts-only review.
- Validate with artifacts, not claims. Prefer providers that publish clear methodology, report/contest archives, and verification details you can inspect.
- Plan for remediation and follow-up. The engagement should include fix verification and clarity on what changes trigger re-review.
As a rule of thumb: pick the firm (or combination) whose public evidence best supports your needs – private audit depth, broader independent reviewer coverage, formal verification, or post-launch incentives—rather than optimizing for a name alone. We’ll keep updating this list as offerings and publicly verifiable evidence change.
Crypto World
Why crypto venture capitalists at Consensus Hong Kong are playing a 15-year game
The mood among top venture capitalists at Consensus Hong Kong was not retreat, but recalibration, as the crypto market experienced a prolonged downturn.
Hasseeb Qureshi, managing partner at Dragonfly, described today’s venture market as a “barbell:” On one side, proven verticals compounding at scale; on the other, a narrow set of high-risk, next-generation bets.
“There’s stuff that’s working, and it’s just like, scale it up, go even bigger,” Qureshi said, pointing to “stablecoins, payments and tokenization in particular.” In a market that’s cooled from speculative excess, these are the sectors still demonstrating product-market fit and revenue.
On the other side is crypto’s intersection with artificial intelligence (AI). Qureshi said he is spending time on AI agents capable of transacting onchain, even though if “you give an AI agent some crypto, it’s probably going to lose it within a couple days.” The opportunity is real, but so are the attack vectors and design flaws.
The cautious tone reflects lessons learned. Qureshi said he initially dismissed non-fungible tokens (NFTs) as “definitely a bubble,” only to reverse course months later and back infrastructure plays like Blur. That experience, he said, was a reminder to balance conviction with adaptability in fast-moving cycles.
Dragonfly also famously missed an early opportunity in prediction market Polymarket.
“We were actually his first term sheet,” Qureshi said of founder Shayne Coplan, but passed when a rival fund offered a higher valuation. “Generational miss,” he called it, although Dragonfly later joined a 2024 round before the U.S. election and is now a major shareholder. The takeaway: Thematic conviction, in this case around prediction markets, can take years to pay off.
Maximum Frequency Ventures’ Mo Shaikh argued that venture success in crypto still hinges on long time horizons. His best thesis, he said, wasn’t a trade but a 15-year bet that blockchain could re-architect financial risk systems.
“Have a 15-year timeline,” he advised, urging founders and investors to resist 18-month cycle thinking.
If the venture environment feels tighter, Pantera Capital’s data supports it. Managing partner Paul Veradittakit said crypto VC capital rose 14% year over year, even as deal count fell 42%, evidence, he said, of a “flight to quality.” Investors are concentrating into “accomplished entrepreneurs” and “tangible use cases.”
After more than a decade fundraising in crypto — from $25 million early funds dominated by family offices to today’s $6 billion platform — Veradittakit sees institutions increasingly driving the next leg. But his advice to founders in a softer market was blunt. “Focus on product, market fit … If there is a token, it’ll naturally come.”
In a downshifted cycle, the venture message is clear: scale what works, experiment selectively and don’t confuse narrative with fundamentals.
Crypto World
JPMorgan bullish on crypto for rest of year as institutional flows set to drive recovery
Wall Street bank JPMorgan is striking a constructive tone on crypto despite the plunge so far this year, arguing that institutional inflows and regulatory clarity could underpin the next leg higher for digital assets.
“We are positive in crypto markets for 2026 as we expect a further rise in the digital asset flow but more led by institutional investors,” analysts led by Nikolaos Panigirtzoglou, said in the Monday report.
The optimism comes despite the recent sharp correction, which dragged bitcoin below the bank’s estimated production cost, a level that has historically acted as a soft price floor. The world’s largest cryptocurrency was trading around $66,300 at the time of publication.
Crypto markets have endured a steep pullback over the past few weeks. Bitcoin briefly fell below key breakeven levels tied to miner production costs, compressing sentiment and trimming onchain activity.
Despite the drawdown, volatility remains elevated and institutional interest has held up better than retail engagement, setting the stage for a potential rebound if capital rotation into digital assets resumes.
The analysts now estimate bitcoin’s production cost at roughly $77,000, down significantly in recent weeks. While prolonged trading below that level could pressure miners and force higher-cost operators offline, in turn lowering the aggregate production cost, the bank sees the dynamic as ultimately self-correcting.
At the same time, bitcoin’s relative appeal has improved. Gold has significantly outperformed BTC since October, while the precious metal’s volatility has climbed sharply. That combination, the report argued, makes BTC look increasingly attractive versus gold on a long-term basis.
JPMorgan expects a rebound in digital asset flows in 2026, led primarily by institutional investors rather than retail traders or digital asset treasuries (DATs). That shift, it says, will likely be supported by further regulatory progress in the U.S., including potential passage of additional crypto legislation such as the Clarity Act.
Read more: Bitcoin a tech trade for now, not digital gold, says Grayscale
Crypto World
USD Under Pressure Ahead of NFP: Yen and Loonie in Focus
The dollar continues to decline ahead of the US January labour market report and has yet to show signs of firm stabilisation. Pressure on the US currency persists, although it is possible that following the release of the employment data the dollar may attempt to steady and find short-term support.
Investors are still trimming dollar positions in advance of the Non-Farm Payrolls report, as well as the unemployment rate and wage growth figures, which are viewed as key indicators for assessing the Federal Reserve’s next steps. After a spike in volatility at the start of the week, trading activity has eased and the market has shifted into wait-and-see mode, watching whether the data will confirm a gradual easing scenario or instead provide grounds for dollar stabilisation and a corrective rebound.
USD/JPY
USD/JPY remains under pressure amid NFP expectations and domestic developments in Japan. The yen found support after Prime Minister Sanae Takaichi’s decisive victory in the snap election, which boosted investor confidence in the country’s economic outlook.
The sharp rally in Japan’s equity market and fresh record highs in the Nikkei and Topix indices have been interpreted as a sign of political stability and the potential for large-scale reforms. This has strengthened demand for the yen and added downward pressure to USD/JPY.
Technical analysis suggests a possible retest of the January extremes near 152.20–152.70, as a bearish engulfing pattern has formed on the daily timeframe. The bearish scenario would be invalidated by a sustained move above 154.50.
Key events for USD/JPY:
- Today at 15:30 (GMT+2): US Non-Farm Payrolls
- Today at 15:30 (GMT+2): US average hourly earnings
- Today at 17:15 (GMT+2): Speech by FOMC member Michelle Bowman

USD/CAD
As expected, a test of the key resistance zone at 1.3700–1.3720 brought the upward impulse to an end. Following the formation of a dark cloud cover pattern, the pair declined towards 1.3520.
Should US employment data disappoint, a renewed test of the 1.3480 low is possible. A resumption of the upward correction may be considered only after a confident break and hold above 1.3580.
Key events for USD/CAD:
- Today at 15:30 (GMT+2): Canadian building permits
- Today at 17:30 (GMT+2): US crude oil inventories
- Today at 20:30 (GMT+2): Bank of Canada summary of deliberations

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Crypto World
Cisco (CSCO) Stock Q2 Earnings: What to Expect from Today’s Report
TLDR
- Cisco reports Q2 fiscal 2026 earnings Wednesday after market close with analysts expecting $1.02 EPS on $14.88 billion revenue
- Stock has surged 37% over the past year fueled by AI infrastructure demand from cloud and hyperscale customers
- UBS analyst forecasts Product orders to grow high single digits while AI orders may hold flat at $1.3 billion sequentially
- Options market implies 6.22% post-earnings move, more than double the stock’s typical 3.01% swing
- Company launched new AI networking chip Tuesday to compete directly with Broadcom and Nvidia
Cisco releases second quarter fiscal 2026 results after the bell Wednesday, February 11. The conference call follows at 4:30 pm ET.
Wall Street expects earnings per share of $1.02, up 8.5% year-over-year. Revenue estimates sit at $14.88 billion, representing 1.55% growth.
The consensus figures match Cisco’s guidance of $1.01 to $1.03 per share on $15.0 billion to $15.2 billion in revenue. With numbers aligned, investors will focus on forward guidance and AI order momentum.
CSCO stock has jumped 37% over the past year. Strong demand for AI networking infrastructure has powered the rally across cloud providers and enterprise customers.
The company announced a new AI networking chip Tuesday, positioning itself against Broadcom and Nvidia. The timing ahead of earnings suggests management wants to emphasize its AI credentials.
Analyst Expectations Point Higher
UBS analyst David Vogt maintains a Buy rating with a $90 price target. His industry checks indicate revenue could top his $15.05 billion estimate on strengthening enterprise markets.
Vogt projects Product orders rising high single digits, down from 13% growth last quarter. He conservatively expects AI orders flat sequentially at $1.3 billion, about 20% of his $6.2 billion full-year target.
Meta Platforms’ recent capex disclosure supports the AI thesis. Meta reported Q4 2025 capex of $22.1 billion, up 49% yearly, with 2026 guidance of $125 billion at the midpoint.
Cisco’s remaining performance obligations reached $42.9 billion in October, up 7.2% year-over-year. This backlog metric will signal whether AI deals continue converting to revenue.
Evercore analyst Amit Daryanani holds a Buy rating with a $100 price target. He highlighted Cisco’s Silicon One products including G200 and P200-based systems following the company’s AI Summit.
Options Activity Signals Volatility
Options traders expect a 6.22% move in either direction after earnings. That’s more than double the 3.01% average post-earnings move over the past four quarters.
The elevated implied volatility reflects investor uncertainty about AI order sustainability. Wall Street assigns a Strong Buy consensus with 10 Buy ratings and three Holds.
The average analyst price target of $91.30 implies roughly 6% upside. TipRanks’ AI Analyst rates the stock Outperform with a $96 target, citing solid fundamentals and positive technical indicators.
Cisco offers a 2.1% dividend yield. Management’s full-year fiscal 2026 guidance calls for $60.2 billion to $61.0 billion in revenue with EPS of $4.08 to $4.14.
The key questions for Wednesday’s call center on AI infrastructure momentum, enterprise spending trends, and whether management feels confident enough to raise full-year targets. Any hints of AI order delays or margin pressure could test the stock’s 37% run.
Investors will also watch for commentary on the competitive landscape after Tuesday’s chip announcement. Cisco disclosed over $2 billion in AI infrastructure orders during fiscal 2025 and has suggested the fiscal 2026 pipeline could exceed $3 billion.
The company ended Q1 with cumulative AI orders topping $2.1 billion. Converting that backlog into recognized revenue remains critical for sustaining growth and justifying the stock’s recent valuation expansion.
Crypto World
BNB & Toncoin Stall as BlockDAG’s Mainnet Goes Live! Here’s Why Traders Are Rushing to Secure 200x ROI Potential
The crypto market is in a bearish mood, and major coins are reflecting the trend. The Binance Coin price recently dipped to $643.38, showing weekly losses of nearly 15%. The Toncoin price is also sliding, trading below all key moving averages and facing persistent downward pressure.
Yet in the middle of all this volatility, one project is moving upward: BlockDAG (BDAG). The coin has quickly become the most popular cryptocurrency of the quarter, with major milestones ahead, including exchange listings on February 16 and today’s TGE event.
And its long-awaited mainnet has gone live today! Now, traders have a final chance to secure a 200× ROI in its last allocation phase, before the opportunity vanishes forever. Let’s explore the BNB and TON outlook and see why experts are calling BDAG a must-buy coin today.
Binance Coin Price Holds Despite Selling Pressure
The Binance Coin price has slipped to $643.38 now as overall crypto market activity has slowed. Now, the weekly losses are nearing 15%, signaling persistent selling pressure. Trading volume dropped sharply, yet long-term investors are holding their positions, closely watching for potential recovery opportunities. Analysts point out that BNB remains within a multi-year accumulation phase, with strong support around $421 and a deeper fallback near $305 if needed.
Historically, Binance Coin price surged in 2021 before entering a prolonged sideways consolidation. A recent breakout above this channel suggests the start of a potential bullish cycle. Medium-term targets sit near $1,385, while longer-term projections range from $2,000–$3,000, with speculative scenarios even reaching $10,000, though these remain probabilistic.
Toncoin Price Stuck Below Key Resistance
The Toncoin price is currently trading at $1.411, marking a weekly decline and staying below all major moving averages, MA-20 ($1.459), MA-50 ($1.596), and MA-200 ($2.308), showing persistent downward pressure. Technical signals, including MACD and ADX, point to continued selling, while RSI at 44 and an overbought Stochastic RSI suggest mixed short-term momentum.
The nearest support lies at $1.35, with resistance near $1.48, limiting the likelihood of a strong breakout. Over the coming week, Toncoin price is expected to trade sideways within this range, with further declines possible if support fails. Analysts note that without a decisive move above $1.48, bearish conditions may persist, though short-term range trading could continue between $1.35 and $1.48.
Mainnet Live: Why BlockDAG Is The Market Favorite Today
BlockDAG has quickly become the most popular cryptocurrency of 2026, fast approaching its exchange listings on Feb 16, less than a week away. And today marks a huge step in its launch roadmap: mainnet activation. The BlockDAG Mainnet is live, the network is fully operational, and real transactions are being verified on the BlockDAG Explorer. Now, holders just need to keep their presale wallet or linked dashboard ready for what comes next.
The Token Generation Event (TGE) also begins today on February 11, 2026.. The claiming process has kicked off. Users simply log in to the BlockDAG dashboard, connect their presale wallet, and select “Claim BDAG.” Tokens will be sent directly on-chain, no extra forms, no hidden fees, just standard gas costs. The portion unlocked at TGE depends on presale allocations, and any remaining tokens will automatically follow the vesting schedule.
Now, the final BDAG allocation is live at just $0.00025. Compared to the $0.05 launch price, buyers are looking at an instant 200× potential upside if they act before the TGE closes. Staking in the network is also tied to BDAG ownership. CEO Nicolaas David van den Bergh made it crystal clear in a recent Binance AMA: staking rewards are only for BDAG holders. No BDAG, no staking. No staking, no rewards.
Once claimed, BDAG can be traded, staked, or used according to vesting rules. This clear launch roadmap ensures everyone, from first-timers to seasoned traders, can confidently step into the mainnet and start earning. With the network processing its first real transactions today and 200× potential on the table, it’s a rare chance to join before BDAG hits exchanges and the price moves out of reach.
Final Thoughts
Right now, the Binance Coin price is hanging around make-or-break levels. Support near $421 is the main cushion if the market stays weak, while $305 is the last safety net if things turn rough. On the upside, a move toward $1,385 would be a strong sign that confidence is returning.
The Toncoin price action feels more bearish, staying below all its key averages. With $1.35 acting as the floor and $1.48 as the ceiling, TON looks set to drift sideways unless buyers step in with real conviction.
BlockDAG, on the other hand, is in a completely different league. With its mainnet live, TGE set for today on Feb 11, and exchange listings less than a week away, it’s clear why it ranks as the most popular cryptocurrency right now.
And the final allocation phase means there’s a rare chance to score 200x ROI. Simply put, with staking rewards, a clear launch plan, and a massive upside still on the table, BDAG isn’t just another promise; it’s the one opportunity that’s actually moving while others hit pause.
Private Sale: https://purchase.blockdag.network
Website: https://blockdag.network
Telegram: https://t.me/blockDAGnetworkOfficial
Discord: https://discord.gg/Q7BxghMVyu
Disclaimer: This is a Press Release provided by a third party who is responsible for the content. Please conduct your own research before taking any action based on the content.
Crypto World
When Will Bitcoin’s (BTC) Bear Market End? 4 AIs Predict the Turning Point
“Right now, we are in the confusion phase,” ChatGPT claimed.
Bitcoin (BTC) has been in an evident downtrend over the past few months, which intensified at the start of February. This caused analysts and market observers to claim that the asset has entered a bear market.
Investors are now perhaps curious to find out when that period will be over, so we consulted four of the most popular AI-powered chatbots to give their take on the matter.
Brace for Several More Months
According to ChatGPT, BTC is likely in the middle-to-late stage of the bear phase rather than the beginning. However, it suggested that there is a strong possibility for a final shakeout before entering a slow accumulation stage.
The chatbot pointed out that in previous cases, Bitcoin’s bear market has rarely ended dramatically, and its conclusion looked “quiet and uninteresting.”
“Right now, we are in the confusion phase – which historically is closer to the end than the beginning,” ChatGPT added.
Perplexity predicted that the bear phase could end in the second quarter of the year, assuming that the negative sentiment among investors lately has marked the bottom zone. Earlier this month, the popular Fear & Greed Index plummeted to “Extreme Fear” territory of 6, a level last observed in August 2019.
This reflects the panic across market participants following the recent decline; however, it may also be interpreted as a buying opportunity. After all, renowned investors and prominent figures, including Warren Buffett, have long advised that investors should step in when prices are collapsing and exit the ecosystem when “Greed” dominates.
According to Perplexity, the potential end of the bear market in Q2 might be followed by consolidation and a renewed bull run towards the end of 2026. It went even further, forecasting that BTC’s valuation could hit a new all-time high of around $150,000 before New Year’s Eve.
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A Lot More Pain?
Grok, the chatbot integrated into the social media platform X, outlined a more pessimistic viewpoint. It claimed that the bears will remain in charge until the end of the year, adding that there might be a further crash to as low as $55,000. The chatbot warned that, in the event of a global geopolitical event, such as a major war, the price could tumble further than the depicted level.
Google’s Gemini presented a similar scenario. It expects subdued performance until late 2026 as the market prepares for the 2027-2028 run toward new peaks.
“If the current cycle follows the ‘four-year’ script, the absolute capitulation point (the ‘true bottom’) may not arrive until late 2026, especially around October or November,” it stated.
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