Crypto World
Do prediction market odds equal probability? Not quite
A US exchange can list a new prediction market by filing a form saying the contract complies with the law, and start trading the next day. No approval required.
Summary
- Prediction market prices are well calibrated overall: studies of thousands of settled markets find outcomes occurring at close to their implied frequencies, with accuracy that beats individual experts and polls.
- The best-documented distortion is the favorite-longshot bias: cheap contracts win less often than their prices imply and expensive contracts win slightly more, so buyers of long shots earn systematically negative returns.
- Capital lock-up is the least discussed distortion: a contract paying $1 in six months is worth less than its probability today because the money is committed and earning nothing, which pushes long-dated prices below fair value.
- Calibration varies by domain and horizon, with political markets showing compression toward 50% at long horizons, attributed to opposing partisan bets cancelling instead of informing.
- Fees, spreads, and the maker-taker split move realized returns meaningfully on instruments priced in cents, and resolution risk sits underneath everything as the possibility that a correct forecast still fails to pay.
Behind that speed sits a trapdoor written into Dodd-Frank, three undefined words, and a rulemaking the CFTC opened this June to finally settle what they mean.
The most useful sentence ever written about prediction markets is that a contract trading at 70 cents implies a 70% probability, and the most useful next sentence is that this is an approximation with known, measurable errors. Both halves matter. The first is why journalists, analysts, and increasingly institutional data buyers treat these prices as forecasts: the mapping is real, and the empirical record supporting it is better than most critics assume. The second is why traders who read the price as literal truth lose money in patterned, predictable ways. Research covering hundreds of thousands of settled contracts across the largest venues now supports a precise account of where the mapping holds and where it bends, and the answer is not that markets are wrong but that a price is a market-clearing number produced by capital under constraints, not a probability produced by an oracle. This guide walks the evidence: the calibration record, then the five distortions, then how to read a price properly.
The mapping, and why it mostly works
Start with the good news, because it is stronger than the skeptical framing usually allows.
Calibration studies plot implied probabilities against realized frequencies: take every contract that traded at roughly 30 cents, check how often those events actually happened, and see whether the answer is close to 30%. Across large samples of settled markets, the resulting curve tracks the ideal diagonal closely. One analysis of thousands of markets on the largest regulated venue found overall accuracy above 90% across probability ranges, with the curve hugging the diagonal and no evidence of gross systematic error. Academic work examining more than 300,000 contracts reached a compatible conclusion: prices are informative, and they improve as markets approach settlement, which is exactly what an efficient information aggregator should do as uncertainty resolves.
Comparisons to alternatives are the second part of the case. Aggregated market prices have generally outperformed individual expert forecasts, single polls, and simple statistical models, because the mechanism rewards being right with money and punishes confident error, which is a stronger incentive structure than reputation. Market efficiency has also been improving as the sector grows: spreads on the leading venue compressed sharply as volume expanded, which mechanically improves price quality. For context, crypto.news has explained where the liquid markets live and why the venue structure matters for market quality.
So the base case is that these prices deserve to be taken seriously as probability estimates. The rest of this guide is about the five ways they deviate, each of which is measurable and each of which points the same direction: the deviations mostly hurt the participant who reads the price naively.
Distortion one: the favorite-longshot bias
The best-documented bias in the literature, imported from a century of horse-race betting research, is that markets overprice unlikely outcomes and underprice likely ones.
The evidence in prediction markets is now substantial. Studies of large Kalshi samples find that low-priced contracts win far less often than needed to break even, while high-priced contracts win slightly more often and deliver small positive returns. One analysis found that events priced above 80% occurred about 84% of the time, several points below what their prices implied, meaning even the favorites side of the bias produces a modest shortfall against expectations at that end of the range. The pattern shows up across politics, entertainment, and economic data releases, and across trade sizes and volumes, which argues against it being an artifact of one market type.
The explanations are behavioral and structural in combination: people systematically overestimate small probabilities, a finding that predates prediction markets by decades; cheap contracts offer lottery-like payoff profiles that attract optimistic buyers; and limited arbitrage capital means the mispricing is not fully competed away. For a participant, the practical implication is uncomfortable and simple: buying long shots at five or ten cents is, on the historical record, a systematically losing strategy, and the sellers of those contracts have been the ones collecting.
Distortion two: capital lock-up
The most underappreciated distortion has nothing to do with psychology. It is arithmetic about time.
Buying a contract at 70 cents commits 70 cents until settlement, earning nothing in the meantime. If settlement is a week away, the cost of that commitment is negligible. If settlement is a year away, the buyer has forgone a year of risk-free return on the capital, which at prevailing rates is a meaningful percentage of the stake. Rational participants therefore pay less than the true probability for long-dated contracts, and recent work formalizes this as settlement discounting: in collateralized markets where capital sits locked until resolution, the price-as-probability mapping is incomplete, because these venues are information aggregators embedded in capital markets, not frictionless probability oracles.
The practical consequences run in two directions. For a reader treating the price as a forecast, long-dated contracts systematically understate the true probability, and the effect compounds with the horizon. For a trader, the discount is not an anomaly to exploit but the market correctly pricing the cost of committed capital, which means an apparent edge on a distant contract may be entirely consumed by the opportunity cost of getting there. Any comparison between a prediction market price and a poll or model output should account for this, and almost none do.
Distortion three: liquidity and domain
Calibration is not uniform across markets, and the variation is systematic enough to have been decomposed.
Volume concentrates heavily: political and macroeconomic contracts have accounted for a majority of trading on the largest venues, which means those markets have the tight spreads, the professional participation, and the price quality that the calibration studies mostly measure. Thin markets on obscure questions inherit none of that, and a 40-cent price in a book with a fifteen-cent spread carries far less information than the same number on a Fed decision.
Domain matters beyond liquidity. Research examining calibration across knowledge domains, horizons, and trade sizes found that a handful of components accounted for the large majority of variation, with political markets showing pronounced underconfidence: prices compressed toward 50%, understating the probability of favored outcomes, at nearly every horizon and most strongly among the largest traders. The proposed mechanism is bilateral cancellation, in which opposing partisan bets pull prices toward the middle without adding information, and the same pattern replicated on a structurally different venue, which strengthens the finding.
There is also a category where calibration is close to meaningless: questions with no historical base rate. A market on whether an unprecedented technological milestone occurs by a distant date has nothing to anchor to, and its price reflects sentiment among a small self-selected group. Those markets are entertainment dressed as forecasting, and they should be read accordingly.
Distortion four: fees, spreads, and who you trade as
On instruments priced in cents, transaction costs are not a rounding error, and the research shows they fall unevenly.
Analyses of the maker and taker split find that participants providing liquidity earn better returns than those taking it, for two compounding reasons: makers obtain better prices by definition, and takers generally pay the fees. Layer the favorite-longshot bias on top and the worst realized outcomes concentrate among takers buying cheap contracts, which is also the most intuitive behaviour for a new participant. The gap is measurable in the return data across price deciles.
The spread deserves separate attention because it is the cost most often ignored. A two-cent spread on a 65-cent contract consumes roughly 3% of the position immediately on a round trip, which against an expected edge of a few percentage points can erase the trade’s entire rationale. Spread quality has improved substantially with volume, but it varies enormously by market, and checking it before sizing is the single highest-return habit available.
Distortion five: resolution risk
The last distortion is the one that turns a correct forecast into a loss, and it is structural, not statistical.
A contract pays according to its stated resolution criteria as adjudicated by its named source or process, and that adjudication can diverge from what an ordinary observer concludes happened. On regulated venues the source is typically a designated authority, which makes disputes rare but not impossible where wording is ambiguous. On blockchain-based venues, settlement runs through decentralized oracle processes with proposal, challenge, and token-holder voting stages that this publication examines in detail, and there the divergence risk is materially higher and has produced real disputed payouts. That is the risk underneath every price.
The correct way to hold this is as a haircut on every price. A contract at 90 cents is not a 90% chance of being paid; it is a roughly 90% chance the event occurs multiplied by the probability that the resolution process pays it as expected. In liquid markets with objective single-source criteria, that second factor is close to one. In ambiguously worded or contentious markets, it is meaningfully lower, and it is entirely absent from the headline number.
What the calibration research cannot tell you
Before assembling the method, one honest caveat about the evidence base, because the studies cited above have limits that their headline numbers conceal.
The samples are historical and venue-specific. The largest datasets cover a regulated exchange over a period running from 2021 through 2025, an era in which prediction markets were smaller, more concentrated among sophisticated participants, and dominated by categories with clean resolution sources. Calibration measured on that population may not describe a market that has since added tens of millions of retail accounts through brokerage distribution, expanded aggressively into sports, and grown volumes by an order of magnitude. More retail participation could improve calibration by adding diverse information or worsen it by adding correlated sentiment, and the honest answer is that nobody yet knows which dominates at current scale.
Selection also shapes what gets measured. Calibration studies necessarily examine markets that resolved, which excludes contracts delisted, withdrawn, or voided, and those are disproportionately the ambiguous or contested ones where the price-to-probability mapping would have performed worst. The measured record is therefore a record of the well-behaved subset, and the true error rate including resolution failures is worse than the curves show.
Regime change is the third limit. Calibration is a property of a market’s participant mix, incentive structure, and information environment, all of which are shifting fast: new venues, new distribution, institutional data buyers, leveraged product variants, and a legislative environment that could remove entire categories. Findings proven on one configuration do not automatically survive into the next, which is why the coming election cycle is the most informative calibration test the sector has faced, and why any confident claim about accuracy should be dated.
None of this undermines the base case. It sharpens it: prediction market prices have a good measured record on a specific historical population under specific conditions, and the correct posture is to use that record as evidence while treating the current, much larger, much more retail market as an ongoing experiment whose results are not yet in.
How to read a price properly
Assemble the five and a usable method falls out.
Treat the price as a strong prior, never a fact. Adjust upward for long-dated contracts to account for the capital lock-up discount. Discount extreme prices toward the middle, since long shots are overpriced and heavy favourites are slightly overpriced too. Weight the reading by liquidity, taking prices from deep, professionally traded markets seriously and thin ones as sentiment. Read the resolution criteria and apply a haircut where the wording admits argument. And when trading rather than reading, account for fees, the spread, and whether you are making or taking, because those costs land before any edge does.
None of this argues against the instruments. The calibration record is genuinely good, better than most alternatives, and improving with volume. It argues for reading them the way a professional reads any market-implied number, an inflation breakeven or an options-implied volatility: as information produced by capital under constraints, containing real signal and predictable distortions, and worth more to the person who knows which is which.
One last practical note, aimed at the readers who consume these prices without ever trading them, which is now most of the audience. Prediction market numbers increasingly appear in political commentary, market research, and media dashboards as substitutes for polls, and the substitution is usually presented without any of the qualifications above. A responsible citation of a market price does three things: it names the venue, since calibration differs by market structure and resolution architecture; it names the date and horizon, since the same question priced a year out and a week out carries different distortions; and it treats the number as one estimate among several, never the answer, because the research showing markets beat individual experts does not show them beating the combination of markets, models, and polls read together. Crypto.news has also covered who is buying these numbers as exchanges, sportsbooks, and data buyers fight over the value of market-implied probabilities.
The strongest version of the case for these instruments is that they add a real, financially disciplined signal to a forecaster’s toolkit. The weakest version, and unfortunately the most common in circulation, is that a number from a screen settles a question. The distance between those two readings is what this guide has been about, and it is entirely made of the five distortions above.
Frequently asked questions
Does a 70-cent contract mean a 70% probability?
Approximately. Calibration studies across thousands of settled markets find implied probabilities track realized frequencies closely, with overall accuracy above 90% across price ranges. The mapping is a good first approximation with documented deviations at the extremes, over long horizons, in thin markets, and after fees.
What is the favorite-longshot bias?
The tendency for cheap contracts to win less often than their prices imply and expensive ones to win slightly more. Research on large samples finds low-priced contracts deliver systematically negative returns while high-priced contracts yield small positive ones, with one analysis showing events priced above 80% occurring about 84% of the time. Buying long shots is, on the record, a losing strategy.
Why do long-dated contracts trade below their true probability?
Because capital is locked until settlement and earns nothing meanwhile. Committing money for a year to a contract paying $1 has a real opportunity cost, so rational buyers pay less than the fair probability, an effect recent research formalizes as settlement discounting. Any comparison of a long-dated market price to a poll or model should adjust for it.
Are prediction markets more accurate than polls or experts?
Generally yes, in the aggregate. Market prices have outperformed individual expert forecasts, single polls, and simple statistical models across many studies, because participants are financially rewarded for accuracy and penalized for confident error. The advantage is largest in liquid markets and smallest in thin ones with no historical base rate to anchor prices.
Which markets should be trusted least?
Thin ones, distant ones, and unprecedented ones. Wide spreads mean low information content; long horizons introduce the lock-up discount and, in political markets, documented compression toward 50%; and questions with no historical base rate, such as unprecedented technological milestones, have nothing anchoring their prices beyond the sentiment of a small self-selected group.
How much do fees and spreads matter?
Considerably, on contracts priced in cents. A two-cent spread on a 65-cent contract costs roughly 3% on a round trip, which can exceed a realistic edge. Research also finds liquidity providers earn better returns than takers, who both pay fees and receive worse prices, with the gap widest among buyers of cheap contracts.
What is resolution risk?
The possibility that a contract fails to pay as expected because of how it resolves rather than what happens in the world. Contracts settle against named sources and pre-written criteria, so ambiguity can produce outcomes that surprise participants, and on blockchain venues using decentralized oracle voting the risk is materially higher. Every price should be read with a haircut for it.
How should a careful reader use these prices?
As a strong prior rather than a fact: adjust long-dated prices upward for capital lock-up, discount extreme prices toward the middle, weight by liquidity, read the resolution criteria, and subtract transaction costs before assuming an edge. Treated that way, prediction market prices are among the most useful public forecasts available. This is educational information, not investment advice.
Disclaimer: This article is for information and educational purposes only and does not constitute financial or investment advice. Research findings cited reflect published studies of historical data and do not predict future accuracy, and trading event contracts carries risk of total loss of amounts invested. Always do your own research. Information is accurate as of July 27, 2026.
The IMF said Brazil’s stablecoin market has expanded rapidly since 2017, with cross-border crypto flows growing faster than traditional capital flows.
Perpetual futures tied to SK Hynix, a South Korean chipmaker whose American depositary receipts debuted on Nasdaq earlier this month, suffered a flash crash on Hyperliquid shortly before the underlying share price came under pressure in its home market.
Between 23:00 UTC and 23:01 UTC, the price of perpetuals tracking the Seoul-traded stock crashed 20% to $900, according to data from Hyperliquid. The price rebounded to over $1,000 the very next minute and was recently priced at $1,092. The contract is traded and denominated in dollar-pegged stablecoin USDC.
An hour later, the Korean stock market opened on a negative note, led by chipmakers. By the end of the day, SK Hynix shares had dropped by 15% to 1,550,000 won ($1,762). Other losers included Samsung Electronics and carmaker Hyundai Motor. The benchmark Kospi index fell 11%.
SK Hynix ADRs, 10 of which equal one share, fell 4.5% in pre-market trading to $136.51.
Hyperliquid, the leading perpetuals-focused decentralized exchange, has emerged as a hot favorite of traders looking to express their view on traditional assets, especially since the onset of the Iran war in late February. The exchange had not responded to a request for comment by publication time.
BitMEX is now facing legal action alleging it withheld trader collateral and engaged in insider trading. The new lawsuit accuses Hayes and fellow co-founders, Ben Delo and Samuel Reed, of designing a system to retain customers’ collateral and transfer the remaining bitcoin to the platform’s insurance fund.
“One lawsuit won’t move the market, but allegations involving 622 BTC (worth over $40.5 million) of withheld collateral reinforce the oldest doubt in crypto: your funds are safe until the day they aren’t,” said Samuel Videau, chief technology officer at Genius. “What’s ending is opacity,the model where you wire assets to a black box and take the operator’s word for it.”
The overall crypto derivatives market has barely flinched. The perpetual swap product BitMEX built now generates the bulk of trading activity on larger exchanges like Binance and OKX, alongside traditional platforms like the Chicago Mercantile Exchange (CME).
“The derivatives market is now much larger and more diversified,” said Edwin Cheung, executive director at crypto trading platform Gate. “Most displaced volume is likely to be absorbed by other established platforms.”
The shift suggests exchanges now need scale, regulatory compliance and broader services to survive, rather than relying on retail trading alone.
Although most of the cryptocurrency market has turned red today, some altcoins are taking the storm worse than others. This is typically true for Pi Network’s native token, and today is no exception.
The asset has plummeted by 9% in the past 24 hours and has come painfully close to breaking below $0.07, which would mean a fresh all-time low.
PI Crashes Again
Looking at PI’s price performance, you can easily quote one of the most recognizable songs of all time, which was immortalized from the TV show Friends. It just hasn’t been PI’s day, week, month, or even a year. Aside from a few impressive but very brief pumps, such as the one in March that sent the asset to $0.30 within days, the bears have been in total control, pushing it to a new low after a new low.
The last example came precisely two weeks ago. At the time, PI had broken below the crucial $0.10 support and went into price discovery territory (but on the wrong side). It kept plunging until it finally found some support at $0.07, but only after it had charted a new all-time low.
Although the bulls reemerged at this point and helped it recover some ground to $0.10 in the following 10 days or so, the overall bearish sentiment remained high, and the inevitable transpired. PI was rejected once again, plummeted to $0.08, and after a few days trading above that line, it broke below it in the past 24 hours.
Hours ago, the asset tanked below $0.074, coming about 5% away from its ATL. Although it has rebounded slightly to over $0.075 now, it remains deep in the red daily (-9%) and weekly (-19%).
Washed Out Sentiment
Even before PI’s nosedive to $0.074, popular analyst Ben (co-founder of BSCNew) commented that the sentiment around the asset remains “as washed out as I have seen it.” And all of that comes despite the continuous updates, redesigned apps, and protocol upgrades delivered by the Core Team.
As such, Ben commented that his position is still unchanged as he cares about “shipping cadence more than the weekly candle.” And, he concluded that “the cadence is accelerating.”
Other accounts dedicated to covering Pi Network news, such as Pi Town, are also supportive of what the team is doing, and seemingly remain unfazed by the overall price calamity of the native token.
The post Pi Network Price Nears Record Low: What ‘Washed Out’ Sentiment Means for PI Holders appeared first on CryptoPotato.
The Hyperliquid Policy Center and Multicoin Capital submitted a joint comment to the US Commodity Futures Trading Commission (CFTC) on July 27th.
They expressed support for the agency’s proposed prediction market framework but also pressed for two changes that could affect how on-chain event contracts are designed and approved.
The filing is a direct response to the CFTC’s “Prediction Markets; Public Interest Determinations” proposal published earlier in June. It aims to amend Regulation 40.11 and seeks to establish a 90-day process for reviewing event contracts that may involve gaming, war, terrorism, assassination, or other activities listed in the Commodity Exchange Act, among other things.
HPC and Multicoin called the plan a “clear and well-reasoned framework.” They argued that prediction markets belong under the CFTC’s exclusive federal jurisdiction.
The letter also states that regulating prediction markets on a state level, creating “fifty separate state regimes,” would fragment national derivatives markets.
Prediction markets topped $50 billion in trading volume last month, and the biggest names in traditional finance are moving in.
Today, with @multicoin, we filed a joint comment supporting the @CFTC ‘s proposed prediction markets framework.
These markets have grown up. The… https://t.co/pYG4mevmbT
— Hyperliquid Policy Center (@HyperliquidPC) July 27, 2026
Settlement: Key Regulatory Test
The first concern that the group outlines is related to the use of one word in the Commodity Exchange Act: “involve.” Under the statute’s rule, the CFTC can review contracts that involve certain listed activities and prohibit them when they are contrary to the public interest.
The letter supports an interpretation focused on settlement. Instead of treating trading itself as gaming, regulators would have to examine the event that determines the payout. A contract would fall within the special rule when settlement directly turns on illegal activity, not merely because buying it resembles placing a wager.
In addition, the group asked for more examples. Edge cases may include certain contracts with several potential paths to settlement or products that reference a sensitive activity only indirectly. Clear illustrations would help exchanges and developers assess regulatory exposure before having to commit resources to a launch.
Transparency Could Become a Competitive Requirement
The second recommendation concerns what happens after a review under Regulation 40.11. Under the current proposal, the CFTC would publish written findings when it blocks a contract and explain how that particular decision fits with earlier findings.
HPC and Multicoin argue that this could create an information gap: an approval, including by inaction, can reveal as much about the regulatory boundaries as a prohibition. Without any public reasoning, other platforms may repeat the same legal work, seek guidance, or avoid products that could have been permissible.
In any case, it’s interesting to follow developments surrounding the letter and whether the CFTC would adopt the two requested changes. This could be a signal that regulators are actively listening to industry experts and attempt to legislate in a way that’s both fair to anyone involved.
The post Hyperliquid and Multicoin Push CFTC Toward One Prediction Market Rulebook appeared first on CryptoPotato.
A federal judge blocked Minnesota’s prediction market ban on Monday, handing Kalshi, Polymarket US, and the Commodity Futures Trading Commission (CFTC) a preliminary injunction days before the law’s August 1 effective date.
US District Judge Katherine Menendez found the Commodity Exchange Act (CEA) likely preempts the statute. Her order bars enforcement against CFTC-registered designated contract markets (DCMs) until a final merits decision.
Why the Court Found Federal Law Likely Preempts Minnesota’s Statute
Menendez issued the order in 3 related cases against Minnesota, Attorney General Keith Ellison, Governor Tim Walz, and other state officials. Kalshi, Polymarket US, and the federal government each won their injunction motions.
Minnesota’s law, Minn. Stat. § 609.7615, makes operating or creating a prediction market a felony. It covers sports, elections, legal actions, pop culture, and statements by specific people. Advertising and providing data services also carry criminal penalties.
The CFTC filed its lawsuit in May, after Walz signed the legislation. Chairman Michael Selig argued the ban would criminalize weather contracts that Minnesota farmers use for hedging.
Menendez ruled that the CEA gives the CFTC exclusive jurisdiction over swaps traded on DCMs. She found many contracts on both platforms, including election and geopolitical markets, that likely qualify as swaps. Consequently, Minnesota likely cannot regulate them.
“Kalshi and Polymarket US are designated contract markets, so the CFTC has exclusive jurisdiction to regulate transactions involving those swaps,” the order read.
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Judge Signals Final Relief Could Be Narrower
However, Menendez stressed that not every event contract fits the swap definition. She pointed to Kalshi markets on Love Island USA winners and World Cup announcer mentions as likely failing the test.
Both sides briefed the case as all-or-nothing, she noted. That left the court little guidance for crafting a narrower remedy, so she froze the entire statute for now.
Irreparable harm weighed heavily in the decision. Kalshi reported over 90,000 verified Minnesota users as of May 26, with millions of dollars in open positions. Sovereign immunity would bar any recovery of damages if enforcement proceeded.
The court did not address the First Amendment claims raised by both exchanges. Those questions, along with the implied preemption issue, now await a full merits ruling.
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The post Court Sides With Kalshi and Polymarket Over Minnesota’s August 1 Ban appeared first on BeInCrypto.
In Washington, momentum can vanish as quickly as it arrives. The Clarity Act now sits on the shelf, while the Bitcoin price slips under renewed pressure after a sharp selloff across Asian markets.
Senate Majority Leader John Thune has shifted attention toward federal nominations and a Russia sanctions bill, delaying debate on crypto legislation. The Digital Asset Market Clarity Act, designed to define SEC and CFTC oversight, now faces an increasingly narrow window before Congress begins its August recess.
— Crypto Banter (@crypto_banter) July 28, 2026
SENATE SHELVES CLARITY ACT FOR NOW!
Majority Leader John Thune is prioritizing nominations and a Russia sanctions bill, pushing the crypto market structure legislation aside amid limited floor time, CoinDesk reports.
Clarity is unlikely to reach a vote before next week, the… pic.twitter.com/XKztbFL7cf
That delay arrives at a supposedly bullish moment. Risk appetite was at its top, and now, the delay leaves crypto exposed to fresh volatility.
Discover: The Best Token Presales
Clarity Act Delay Extends Regulatory Limbo
The Clarity Act is a reminder that politics don’t move in straight lines. Ethics concerns surrounding public officials’ digital asset holdings continue to complicate negotiations. Meanwhile, a proposed 2029 sunset clause remains another point of contention before lawmakers can reach consensus.
Outside Capitol Hill, opposition continues to build. New York Attorney General Letitia James argues the Clarity Act could weaken states’ ability to prosecute crypto fraud, potentially limiting local enforcement powers. Her criticism adds another obstacle as supporters race against the congressional calendar.
Not just in the States, regulatory pressure is also unfolding overseas. Thailand’s SEC has filed criminal complaints against Bitkub and two former executives over allegations they concealed a 2021 cyberattack worth about $50 million. Although customers were reimbursed, authorities allege the exchange submitted inaccurate reports, reviving concerns over transparency throughout the industry.
Elsewhere, prediction markets continue advancing despite federal uncertainty. A U.S. judge temporarily blocked Minnesota’s restrictions on platforms including Kalshi and Polymarket, citing potential conflicts with federal commodities law. As the CFTC seeks faster legal clarity, the Clarity Act remains trapped in Washington’s legislative queue.
Discover: The Best Crypto to Diversify Your Portfolio
Bitcoin Price Slides as Asian Markets Trigger Risk Aversion
The Bitcoin price weakened after Asian equity markets suffered a huge selloff, extending losses from the previous U.S. session. Bitcoin briefly fell below recent support before stabilizing. It’s not just crypto, but a wider retreat from risk assets as investors reduced exposure across multiple markets.
The butchering started with South Korea’s Kospi, which recorded one of its sharpest declines in months, led by heavy selling in major technology stocks. This could be the culprit, dragging the Bitcoin price lower alongside market sentiment.
Recent gains have also begun to lose momentum. Bitcoin price previously rebounded from July lows but struggled to reclaim higher resistance levels as buying pressure softened. Spot Bitcoin ETFs continued attracting inflows over recent weeks, although significant late-week withdrawals showed institutional demand remains sensitive to macroeconomic shifts.
Large holders have largely avoided aggressive accumulation during the latest decline. Strategy maintained its existing Bitcoin position without announcing any additional purchases, instead preserving billions in available cash. At the same time, miners may receive modest relief as network difficulty appears set for its first annual decline in nearly two decades.
Attention now shifts toward the Federal Reserve and Washington alike. Bitcoin price could remain trapped in a cautious range until investors receive clearer signals from policymakers and lawmakers. For now, delayed legislation and fragile market sentiment continue moving together, leaving the Clarity Act and crypto markets waiting for the next decisive chapter.
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The post Crypto News, July 28: CLARITY Act Shelved, Bitcoin Drops in Asian Market Rout appeared first on Cryptonews.
The rather impressive Monday rally didn’t last long, as the entire cryptocurrency market has turned red today, with the market cap losing over $80 billion from top to bottom.
Ripple’s native token is no exception. The asset has dropped from yesterday’s peak at $1.11 to $1.05. Here are some of the possible reasons behind this decline and what could be next.
XRP Dives and ETF Inflows Can’t Save It
Perhaps the most obvious reason behind XRP’s crash is that it’s not an isolated case; the entire market has turned red, led by bitcoin’s dive from $65,600 to $63,000. As such, the cross-border token cannot be simply ruled out, as it tends to follow the overall market trend.
It appears investors are reducing their exposure to risk-on assets like crypto ahead of the next Federal Reserve FOMC meeting. The US central bank will announce its interest rate decision tomorrow evening. According to some reports, there’s an actual chance of a rate hike despite easing inflation in June.
The rejection at $1.11 and the subsequent decline to $1.05 meant that XRP has actually lost a crucial support zone at $1.08-$1.10, which managed to halt its free falls for most of July. Aside from this technical side of things, the asset’s drop triggered a large wave of liquidations, which also created the snowball effect of a more profound decline.
The silver lining is that the ETF net flows remained in the green. However, it was a very modest number of under $600,000, which is evidently not sufficient to help XRP avoid such price losses.
So What’s Next?
The daily leg down hasn’t changed popular analysts’ opinion on XRP’s claimed bright future. Xaif Crypto acknowledged the rising leverage and XRP’s rather tight trading range. The market observer commented that “two-sided liquidations are getting hit on both longs and shorts,” which, aligned with neutral funding and drying up spot liquidity on Binance, will likely lead to a much bigger move soon.
Meanwhile, CasiTrades outlined once again that she expects the next XRP wave to be “violent.” The analyst noted that XRP has returned to macro support, which, if broken to the downside, will likely lead to a more painful decline to $0.87, her targeted bottom.
ripple:native’s Next Wave Could Be Violent!
Do you see how nicely we’re following the purple scenario?
During Friday’s livestream, I highlighted the importance of the $1.09 level we were testing at the time. I explained that it would likely provide a small reaction… pic.twitter.com/9pjn0EbOZS
— CasiTrades
(@CasiTrades) July 27, 2026
The post Why Is Ripple’s XRP Down by 4.5% Today (July 28)? appeared first on CryptoPotato.
All eyes are on July 30, when Amazon reports Q2 2026 earnings, with Wall Street increasingly convinced the bar has been set too low. Consensus sees EPS near $1.82-$2.26 on roughly $197 billion in revenue, but the real story is AWS: after posting its fastest growth in 15 quarters at 28% in Q1, several major banks—including Bank of America—now expect acceleration toward 32-33%, fueled by surging AI demand and Bedrock workloads tied to Anthropic and OpenAI.
That optimism comes with a catch. Amazon’s $200 billion AI capex plan has already squeezed free cash flow to just $1.2 billion, and investors will be watching closely for any further guidance hike, following similar moves from Alphabet. Options markets are pricing a 6.3% swing on earnings day, above the stock’s typical 5.4% post-earnings move, signaling traders expect this report to matter more than usual.
With shares up roughly 18% year-to-date and trading at a below-average forward multiple, the setup favors strength—but only if AWS growth and margin guidance clear an already demanding bar.
Technical Analysis of Amazon
As the chart shows, Amazon stock has pulled back from April’s highs near $280 within a broader ascending channel, with price now testing the confluence of the rising trendline and the 0.618 Fibonacci retracement near $225-$230—precisely where Thursday’s earnings could prove decisive.
Bullish Scenario
Should Amazon deliver on the AWS acceleration Wall Street is now pricing in, a strong earnings beat could fuel a bounce off this trendline-Fibonacci confluence. A confirmed reclaim of the 0.5 retracement near $240, followed by a push back above the 0.382 level around $248, would put the broader uptrend firmly back in play, opening the door toward a retest of the channel’s upper boundary and the April highs.
Bearish Scenario
Conversely, a disappointing report—particularly around capex guidance or AWS margins—could send price breaking below both the ascending trendline and the 0.618 retracement. That would expose the deeper 0.786 level near $215, with a more severe reaction potentially dragging price back toward the $200 psychological support that has held since April.
With earnings landing squarely on this technical crossroads, AMZN stock’s next move could be one of the most consequential of the summer—will AWS’s AI story be enough to reignite the rally, or does the chart already know something the numbers don’t?
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Lido, a liquid staking protocol that lets users earn Ethereum staking rewards through its stETH token, has launched an upgrade to its staking infrastructure that aims to improve validator efficiency and decentralization.
The upgrade introduces Curated Module v2, which adds support for Ethereum’s 0x02 withdrawal credentials. The change allows validators to increase their effective balance from 32 ETH to up to 2,048 ETH, according to a Lido update on Monday.
Lido said the migration could reduce Ethereum’s validator count from about 880,000 to roughly 628,000, a decrease of about one-third. The migration has not started yet, and the figures are based on Lido’s projections.
The change is expected to affect Ethereum’s consensus layer by reducing the number of validators and validator messages required to maintain the network, according to Lido. It is not designed to change execution-layer activity, which determines transaction fees and gas costs.
The update also introduces new accountability measures for Lido’s node operators, including bonding and penalty mechanisms. Lido said future stake distribution could place more weight on factors such as operator performance, fees and contributions to Ethereum’s ecosystem.
“Curated Module v2 is the next major step in that evolution,” Lido said, adding that the upgrade introduces new operator incentives, bond-based security mechanisms and governance improvements. Lido said no action is required from stakers because the upgrade will be handled at the protocol level.
Related: Ethereum nears market bottom against Bitcoin, though key signals remain unconfirmed: CryptoQuant
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