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JPMorgan Gives Bold Nvidia Price Prediction, But Is It Realistic?

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Initial Call For NVIDIA Stock

NVIDIA Stock just delivered a record-breaking Q4 with $68.1 billion in revenue, 73% year-over-year growth, and earnings per share of $1.62 that crushed estimates. JPMorgan, among others, wasted no time raising its price target from $250 to $265.

Yet on February 26, the stock fell nearly 7% from its session high of $197 to under $185. The results are undeniable. But the price action, the money flow, and the institutional behavior tell a very different story. At least, for now.

The Numbers Look Bulletproof, Until You Look Closer

NVIDIA’s Q4 numbers speak for themselves. Revenue hit $68.1 billion, up 73% year-over-year. The data center segment alone pulled in $62.3 billion, making up 91% of total revenue. EPS (Earnings Per Share) of $1.62 beat the $1.53 consensus by nearly 6%.

And the Q1 FY2027 guidance of $78 billion blew past Wall Street’s $72.8 billion estimate — a figure that notably excludes any revenue from China.

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JPMorgan analyst Harlan Sur responded by lifting the Nvidia price target from $250 to $265.

Initial Call For NVIDIA Stock
Initial Call For NVIDIA Stock: TipRanks

But here is what most analysts are not highlighting. NVIDIA’s quarter-over-quarter growth rate is quietly decelerating. Q3 grew 22% over Q2. Q4 grew 19.5% over Q3.

The Q1 guidance implies roughly 14.5% sequential growth. Revenue keeps hitting records, but the pace of acceleration is fading. For a stock priced on growth momentum, this distinction matters. Something big money might be watching.

There is also the question of who is actually driving this revenue. Deepwater Asset Management’s Gene Munster estimates that roughly 70% of Nvidia’s revenue comes from just 8 companies.

CFO Colette Kress confirmed that the top 5 hyperscalers (cloud computing providers) account for slightly over 50% of data center revenue. That level of customer concentration means that even a modest 10-15% reduction in AI capex from a few major buyers could translate into billions in lost quarterly revenue.

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It is also worth noting that JPMorgan’s asset management division is itself a significant institutional holder of Nvidia.

JPMorgan Holds
JPMorgan Holds: Fintel

This is standard on Wall Street, but it is a context that retail investors should be aware of when evaluating the bullishness behind a price target upgrade.

What Retail NVDA Investors See vs What Institutions Are Doing

On-Balance Volume (OBV), an indicator that tracks cumulative buying and selling pressure by adding volume on up days and subtracting it on down days, tells a positive story on the surface.

OBV has maintained higher highs throughout Nvidia’s 3-month consolidation, suggesting retail-driven buying pressure remains consistently positive. However, it still needs to break past its ascending trendline resistance to confirm genuine broad-based strength.

NVIDIA OBV
NVIDIA OBV: TradingView

The most recent 13F filings (quarterly reports large investors must file with the SEC revealing their positions) for Q4 2025 show a dramatic shift in institutional sentiment.

Net institutional money flow surged to approximately $149 billion in purchases against $36 billion in sales — a net inflow of roughly $113 billion. That is a massive improvement from Q3, where institutions bought $38 billion and sold $34 billion, leaving a net inflow of just $4 billion.

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Nvidia Q4 Institutional Flows
NVIDIA Q4 Institutional Flows: Market Beat

Yet despite this wall of institutional money entering NVDA in Q4, the stock barely moved — trading sideways for most of the period. That suggests institutions were accumulating, but supply from insiders and earlier holders absorbed the demand. NVIDIA director Mark Stevens sold approximately $40 million in shares in December.

Bank of America, while slightly increasing its equity stake, closed out both its call and put options positions entirely — neutralizing its directional bets.

Institutions are clearly positioned. But the hedging and the flat price despite massive inflows suggest they are bracing for something. The next section explores what that might be.

The Risk Hiding in the Charts

The Chaikin Money Flow (CMF), an indicator that measures whether money is flowing into or out of a stock based on where the price closes within its daily range weighted by volume, reveals what the earnings headline does not.

Since February 5, as the right shoulder of Nvidia’s inverse head and shoulders pattern formed, CMF climbed steadily alongside the price. It rose all the way into the February 25 earnings breakout when Nvidia briefly touched $197.

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Then on February 26, as the stock reversed sharply to $185, CMF plunged.

That sudden collapse suggests the money flowing in during the rally was speculative positioning — not committed institutional capital — and it evaporated the moment the breakout failed. And based on what we discussed earlier, revenue deceleration could be a reason.

The monthly VWAP (Volume Weighted Average Price, which approximates where institutions have built their positions) reinforces this. NVIDIA had been trading above its monthly VWAP since breaking out on February 17.

The last time Nvidia broke below the monthly VWAP was on January 30, which led to a correction of approximately 8.5% by early February.

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Key Institutional Chart
Key Institutional Chart: TradingView

As of February 26, the stock has once again fallen below this line. This means recent institutional buyers are now underwater, which historically triggers further selling as stop losses unwind.

The technical breakdown has context. Michael Burry flagged today that Nvidia’s supply commitments have ballooned to levels that mirror Cisco before the dot-com bust — a company that wrote down billions when demand didn’t meet expectations.

CFO Kress acknowledged Nvidia has locked in inventory “further out in time than usual.” Bulls like BofA’s Vivek Arya argue this secures Nvidia’s dominance. But CMF collapsing and VWAP breaking on the same day suggests the market isn’t waiting to find out who’s right.

The NVIDIA Stock Price Levels That Decide What Happens Next

The charts, the money flow, and the institutional positioning all point to the same conclusion — $195 is where conviction gets tested, a level highlighted later on the chart. But first, the risk.

On the daily chart, a hidden bearish divergence has formed between November 10 and February 25. During this period, the NVIDIA stock price made a lower high while the Relative Strength Index (RSI), a momentum indicator, made a higher high

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Bearish Divergence
Bearish Divergence: TradingView

It is a signal that upward momentum is quietly fading even as the stock appears to hold its range.

Since that November divergence started developing, Nvidia has been locked between $169 and $199. It couldn’t break out of this consolidation despite multiple attempts — including the inverse head-and-shoulders breakout on February 25, which failed within 24 hours.

NVDA Price Analysis
NVDA Price Analysis: TradingView

The Fibonacci extension levels from the pattern now frame what comes next. On the downside, $183 at the 0.5 level is the immediate support. Below that, $180 at the 0.382 level becomes critical — a break there exposes $170, the right shoulder low, and $169, the head. Those levels would invalidate the pattern entirely.

On the upside, the neckline at $195 remains the key resistance and the conviction tester. A clean daily close above it, which the NVIDIA stock failed to do yesterday, is needed to reactivate the pattern.

That could push it towards the projected target at $226, the full head-to-neckline measurement.

The next extension at $235 brings it closer to JPMorgan’s $265 target. The path exists on paper.

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But as the money flow, the hidden bearish divergence, and today’s 7% rejection all confirm, this is a market that’s not buying it yet.

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Crypto Card Fees Explained: Hidden Costs To Know

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Crypto Card Fees Explained: Hidden Costs To Know

A crypto card can look simple. You tap to pay, shop online, or withdraw cash, and it works much like a regular card.

Still, the total cost is not always obvious. Depending on the provider, users may pay blockchain fees, conversion costs, foreign exchange charges, ATM fees, or merchant markups. Some of those costs appear clearly. Others are built into the rate or show up only at checkout.

That is why the real cost of a crypto card is not one single fee. It is the total cost of moving funds, converting them, and spending them.

Network fees can start before you even spend

The first cost can appear when a user moves crypto into a wallet or account linked to the card. In that case, the blockchain may charge a network fee, often called a gas fee.

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That fee usually does not come from the card provider. Instead, it comes from the network that processes the transaction. As a result, the cost can change depending on which blockchain the user picks and how busy that network is.

So even before the card is used for a purchase, the funding step may already carry a cost.

The exchange rate can include a hidden conversion cost

Many crypto cards convert crypto into fiat at the moment of payment. In some cases, that conversion cost appears as a stated fee. In other cases, it sits inside the exchange rate itself.

That difference matters. A card may look cheap on paper, but the user may still pay more through the rate used to convert crypto into dollars, euros, or another currency.

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So when comparing cards, users should not look only at the fee page. They should also look at how the provider handles conversion.

Foreign purchases can trigger FX fees

When a card is used in a different currency, foreign exchange fees can apply. That is common when users travel, shop on foreign websites, or withdraw cash abroad.

In some cases, the card network sets one rate and the issuer adds its own FX fee on top. That means the final cost can rise even when the transaction goes through normally.

This is one reason why cross border spending often costs more than a domestic purchase.

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DCC is one of the clearest ways to overpay

Another common cost appears at the terminal. When a user pays abroad, the merchant or ATM may ask whether to charge the card in the users home currency instead of the local one. That is Dynamic Currency Conversion, or DCC.

It often looks convenient, but it usually costs more. BEUC, the European Consumer Organisation, said consumers are financially worse off in practically every single casewhen they accept DCC. The same paper cited research showing DCC was on average 7.6% more expensive in one study, while the highest markup reached 12.4%.

So the cleaner option is usually the local currency, not the home currency shown on the screen.

A simple DCC example

Option

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What happens

Typical result

Pay in your home currency through DCC The merchant or ATM converts the purchase Often a worse rate than letting the card network handle it
Pay in the local currency The card network and issuer handle the conversion Usually the more standard and lower cost route

That difference may look small on one purchase. Still, it adds up across repeated payments and withdrawals. BEUCs paper also found examples where payment markups in stores ranged from 2% to 5%, while ATM DCC increases ran from 2.6% to 12% in one dataset.

ATM withdrawals can stack several fees at once

Cash withdrawals are another area where costs can pile up fast. First, the ATM operator may charge its own fee. Then the card issuer may add a withdrawal fee. If the withdrawal is in a foreign currency, an FX fee may apply as well.

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So one ATM transaction can combine several charges in a single step. That is why withdrawing cash is often one of the more expensive ways to use a crypto card.

Users should check both the card providers fee schedule and the ATM screen before confirming the transaction.

Card holds are not fees, but they still affect spending

Not every unexpected charge is a fee. Hotels, fuel stations, car rentals, and some online merchants often place a temporary hold on the card before the final charge settles.

That hold reduces the available balance for a period of time. Later, the merchant posts the final amount and releases the unused part.

So while a hold is not a direct cost, it can still confuse users and make the card balance look lower than expected.

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Other small charges can still matter

Some crypto cards also charge for physical card shipping, replacement cards, premium plans, or inactivity. These costs are not the same across the market, so they should not be treated as universal.

That is why the fee page matters as much as the headline promise. A provider may advertise low spending fees while charging in other places.

In short, the total cost depends on the full structure, not one line in the marketing copy.

What cost can look like in practice

A user may pay one fee to move crypto onchain, another cost through the conversion rate, another fee on a foreign purchase, and another markup if DCC is accepted by mistake. Then, if the same user withdraws cash abroad, ATM and FX charges may come on top.

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KAST’s public fee page offers one example of how that structure can work. It says non-USD card purchases carry a foreign exchange fee of 0.5% to 1.75%, depending on the countries involved. It also says ATM withdrawals cost $3 plus 2% of the withdrawal amount, with the same 0.5% to 1.75% FX fee added for non-USD withdrawals.

That example does not make crypto cards unusually expensive. It simply shows that the total cost often comes from several layers, not one headline fee.

If you want to see how a real fee schedule is laid out before you travel or spend abroad, take a minute to explore KAST.

The main point on cost

Crypto cards are easier to understand when each cost is separated clearly. The main ones to watch are network fees, conversion costs, FX fees, DCC markups, ATM charges, and temporary holds.

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Among them, DCC remains one of the clearest traps because it can make a transaction more expensive without adding any real benefit for the cardholder. BEUCs findings underline that point.

So the simplest rule is this: check how the card handles conversion, read the fee page before using it abroad, and choose the local currency when a terminal gives you the choice.

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Enhanced Labs raises $1 million to widen on-chain options yield

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Virtuals Protocol brings AI agent commerce to Arbitrum in new integration

Enhanced Labs raised a $1 million pre-seed led by Maximum Frequency Ventures to expand options-based yield strategies across on-chain and tokenized real-world assets.

Summary

  • Enhanced Labs secures $1 million pre-seed round led by Maximum Frequency Ventures.
  • Backers include GSR, Selini, Flowdesk and several angel investors.
  • Funds will expand options-based yield strategies to more on-chain and tokenized real-world assets.

U.S.-based DeFi infrastructure startup Enhanced Labs has closed a $1 million pre-seed funding round to expand its options-based yield products across a wider range of on-chain assets, including tokenized real-world assets. The round was led by Maximum Frequency Ventures, with market-making and trading firms GSR, Selini and Flowdesk joining alongside a group of undisclosed angel investors. According to the company, the capital will be used to support product development, operations and go-to-market efforts.

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Enhanced Labs positions itself as a provider of “options-based yield strategies” designed to sit on top of existing DeFi and tokenization rails, rather than competing directly with spot lending or simple staking. By extending these structured strategies to tokenized real-world assets, the firm is effectively betting that on-chain treasuries, credit, commodities and other RWAs will need the same kind of yield engineering and risk-transfer mechanisms that already exist in traditional markets. The goal is to package those exposures in a way that can be deployed programmatically, but still remain accessible to institutions that need clearer risk parameters than typical DeFi products offer.

Backing from names like GSR, Selini and Flowdesk suggests Enhanced Labs is targeting the intersection of market-making, derivatives and on-chain liquidity rather than retail-facing savings products. For these investors, options-based yield on tokenized assets is not just a new narrative but a potential source of structured flow if RWAs continue to move on-chain. The pre-seed size is modest by bull-market standards, but at this stage the more important signal is that specialized trading firms are willing to seed infrastructure aimed at making RWAs behave more like fully featured, hedgeable collateral.

If Enhanced Labs executes, it could help close one of the gaps in today’s tokenization pitch: plenty of projects can put a bond or a real-estate claim on-chain, but far fewer can offer a robust menu of ways to hedge, lever or generate predictable income on top of those assets. Whether a $1 million war chest is enough to build those tools—while navigating the regulatory and risk constraints that come with engineering yield on real-world exposures—remains an open question.

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DOJ and CFTC Seek Halt to Arizona Action Against Kalshi

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DOJ and CFTC Seek Halt to Arizona Action Against Kalshi

The US Department of Justice (DOJ) and Commodities and Futures Trading Commission (CFTC) asked a federal court to block Arizona from enforcing state gambling law against Kalshi’s event contracts, arguing that they fall under the CFTC’s exclusive authority over swaps markets.

The Wednesday filing argues that event contracts listed on federally regulated platforms such as Kalshi are swaps under the Commodity Exchange Act and therefore fall within the CFTC’s exclusive jurisdiction.

The filing says Arizona’s enforcement effort unlawfully intrudes on the CFTC’s exclusive jurisdiction over federally regulated event-contract markets.

If granted, the order would block Arizona from applying its gambling laws to prediction markets that are listed as federally regulated event contracts. An arraignment in the criminal case against Kalshi is currently scheduled for Monday.

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Arizona Attorney General Kris Mayes announced charges against the companies behind Kalshi on March 17, accusing them of operating an “illegal gambling business in Arizona without a license” and offering illegal election wagering.

Kalshi co-founder and CEO, Tarek Mansour, claimed the charges were a “total overstep” and “not about gambling.”

Federal and state regulators clash over prediction markets

The dispute has become a major test of whether prediction market contracts belong under federal commodities law or state betting rules.

CFTC, DOJ court filing seeking a TRO against Arizona federal court in case against Kalshi, Case No: CV-26-01715-PHX-MTL. Source: Courtlistener

On April 2, the CFTC filed three separate lawsuits against the gaming regulators of Illinois, Connecticut and Arizona, claiming that the event contracts offered by the platforms violated state gambling laws and licensing requirements.

In those suits, the CFTC says it has exclusive jurisdiction over CFTC-registered designated contract markets that list lawful event contracts. Kalshi is the clearest example in the current litigation.

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Related: Kalshi, Polymarket face trading halt in Nevada after court rulings

Prediction markets are facing growing regulatory pressure in the US, where 11 states have pursued legal action against them.

Prediction market activity has been rising since the beginning of the US and Israeli military conflict with Iran, fueling renewed insider trading allegations, after six Polymarket traders netted $1 million by accurately betting when the US would strike Iran.

In response to insider trading concerns, Democratic Party Senator Adam Schiff has introduced legislation seeking to ban prediction markets on war, death and terrorism.

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Magazine: Train AI agents to make better predictions… for token rewards