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Could a Hot Inflation Print Send Bitcoin and Ethereum Into Freefall?

Could a Hot Inflation Print Send Bitcoin and Ethereum Into Freefall?

The cryptocurrency market is going through a difficult stretch. In my view, this selloff is not a story about broken technology or failed projects. It is a story about how tightly digital assets now track the mood of traditional finance. Bitcoin has fallen 2.49% to $81,755.72 in 24 hours. That move underperforms a flat S&P 500. At the same time, Bitcoin’s 24-hour correlation with the S&P 500 sits at a strong 81%. That correlation tells me the current pressure comes mainly from macro forces rather than from crypto-native news. Ethereum has suffered even more. It dropped 4.34% to $2,434.26 in the same period, a decline that outpaced Bitcoin’s fall and underscores its role as a high-beta bet on the broader crypto market. When a major digital asset moves in lockstep with equities, traders should pay close attention to inflation data, bond yields, and central bank expectations. Those forces now matter as much as any blockchain upgrade or adoption headline.

The first major force behind this retreat is institutional selling. U.S. spot Bitcoin ETFs recorded roughly $681 million in net outflows for the week ending October 9. That reversal ended a 3-week inflow streak. This shift matters because these funds had become a reliable source of demand. Large investors are now showing caution as Treasury yields rise and inflation worries persist. A steady buyer has become a seller, and that shift weakens the market’s foundation. I will be watching daily ETF flow data to see if this pressure continues or fades. If outflows persist, Bitcoin will struggle to build any durable bounce. If flows stabilize, the market can at least find a floor. The ETF channel is now one of the clearest windows into institutional sentiment, and it currently shows fear.

A second force is a leverage flush. The decline triggered forced selling across derivatives markets. In the past 24 hours, liquidations wiped out more than $406 million in leveraged long positions. That mechanical unwind creates a cascade. Forced selling generates more sell orders, which push prices lower. This pattern is common after a rally. Crowded-in bullish bets get wiped out, and the market cools off violently. The key signal to watch is funding rates and open interest. When those metrics stabilize, it suggests the market has cleared excess leverage. Until then, the risk of more sudden drops remains high. Traders who used too much borrowed capital have learned a painful lesson. The market rarely rewards one-sided positioning for long.

Ethereum faced an even sharper version of this derivatives-driven pain. A total of $115.19 million in ETH long positions were forced to close within 24 hours. That figure accounted for the largest share of a total crypto liquidation of $488.61 million. The forced selling from overextended longs turned a moderate pullback into a steep decline. High leverage acted as fuel. When stop-losses triggered, they accelerated the move lower. I will be watching the aggregate funding rate. A move deeper into negative territory would signal that long unwinding continues. That would keep Ethereum under pressure in the near term. For now, the derivatives market remains the main driver of ETH price action. Spot buyers have not stepped in with enough force to absorb the supply.

The broader backdrop adds another layer of anxiety. No clear Ethereum-specific catalyst appeared. The move was part of a sector-wide retreat. Major altcoins like Solana and XRP fell by similar amounts. Investors are cautious ahead of the U.S. CPI report on October 14. They are also reacting to roughly $681 million in net outflows from spot Bitcoin ETFs last week. Rising 10-year Treasury yields toward 5.3% add to the risk-off mood. Ethereum now trades as a high-beta risk asset. It responds strongly to shifts in market sentiment and macro liquidity. That reality means crypto traders cannot ignore traditional inflation data. A single CPI print can change the direction of the entire market within minutes.

The near-term outlook for Bitcoin hinges on the October 14 CPI report. A favorable reading could help Bitcoin hold the $81,300-$82,000 support band. That outcome could open a path toward reclaiming $84,300. A hotter print risks restarting ETF outflows and a deeper test of support near $79,000. Bitcoin is in a holding pattern. Its immediate trend will be driven by traditional macroeconomic data, not by crypto-specific developments. I will watch how the market reacts at $82,000 immediately after the CPI release. A strong bounce from that level would signal that buyers still see value. A clean break below it would confirm that sellers remain in control.

Ethereum’s technical picture is more fragile. The asset has broken below its 50-day moving average near $2,558 and key support at $2,500. The $2,360 to $2,420 zone is now critical daily demand. If ETH holds this area, a relief rally toward $2,560 is possible. Oversold conditions support that view. The 7-day RSI sits at 26.64, a reading that often precedes a short-term bounce when macro fears ease. A decisive break below $2,360 could trigger another wave of selling. The next major support cluster sits around the 100-day moving average near $2,240. A hot CPI print that breaks support risks a drop toward $2,220-$2,280. Ethereum needs a macro tailwind to reverse its current course. Without one, rallies will likely remain short-lived.

My overall view is bearish for the near term. Bitcoin is experiencing a withdrawal of institutional capital and a flush of overleveraged positions. Ethereum faces the same pressures, but with even greater intensity, due to its derivatives exposure. The macro environment remains tense. Sentiment is weak. At the same time, the market is testing important levels. Bitcoin must hold above $81,300 after the CPI data. Ethereum must reclaim and hold above $2,500. If those levels fail, another wave of defensive selling could follow. If they hold, a relief bounce is possible. The October 14 inflation report will decide which path the market takes. I will keep watching ETF flows, funding rates, and the reaction at those key price zones.

 

Source: https://e27.co/could-a-hot-inflation-print-send-bitcoin-and-ethereum-into-freefall-20261013/

Anndy Lian is an early blockchain adopter and experienced serial entrepreneur who is known for his work in the government sector. He is a best selling book author. The latest book is Web4: The Age of Autonomous Intelligence.

www.anndy.com
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Below $82,620 Bitcoin Could Test $81,154 Next

Below $82,620 Bitcoin Could Test $81,154 Next

The total crypto market cap rose 0.98% to $2.83T. A separate reading put the gain at 0.94%.

Bitcoin climbed 0.87% to $83,666.22. The move looked calm on the surface. The underlying mechanics told a different story. A derivatives-led short squeeze drove the advance. No clear coin-specific catalyst appeared in the data. No clear macro catalyst appeared either. The rally came from a mechanical clearing of leverage. It did not come from fresh fundamental demand.

Bitcoin liquidations surged 1,087% to $39.61M in 24 hours. Short positions accounted for $33.83M of that total over a 12-hour window. That forced bearish traders to cover. Their buying created rapid upward pressure. Total open interest rose 6.64%. That rise showed fresh leverage entering the market even as old positions closed. The combination produced a sharp move higher. It did not reflect new bullish conviction. It reflected a violent clearing of excessive bearish bets. This distinction matters for anyone judging the durability of the advance. A squeeze can lift prices quickly. A squeeze cannot create a lasting trend on its own.

Capital rotated into altcoins after the initial Bitcoin push. The Quantum-Resistant narrative rose 5%. Nervos Network CKB jumped 31.77%. Social sentiment net score stood at 5.82. The Altcoin Season Index sat at 64. These signals showed a risk-on mood. Traders used liquidity from the Bitcoin move to chase higher returns. That rotation broadened the rally. It also added speculative fuel. Trading volume across the sector fell 31.45%. A price rise on falling volume suggests low conviction. The sector also showed an 83% 7-day correlation with the Nasdaq-100 QQQ. That link points to a shared tech-driven move. The crypto advance did not occur in isolation. It tracked a broader risk-on current in technology shares. That correlation weakens the case for a crypto-native catalyst.

Near-term structure hinges on several levels. Bitcoin’s 7-day simple moving average sits near $83,633. Holding above that line could support a retest of the swing high at $87,363. The first support is the 38.2% Fibonacci retracement at $82,620. A break below that level could open a drop toward the 50% retracement at $81,154. The total market cap pivot stands at $2.83T. The 7-day exponential moving average also sits at $2.83T. The 23.6% Fibonacci resistance rests at $2.85T. A clean break above $2.85T could open a path toward $2.94T. Failure to hold $2.80T would suggest the squeeze-fueled bounce is fading. The 7-day RSI for the total market cap is 45.28. That reading leaves room for further upside. The MACD histogram remains negative. This shows underlying momentum is still recovering. The 50-day EMA is another downside reference. The sector is in a tentative rebound phase.

The most important gauge is U.S. spot Bitcoin ETF flow data. Consistent inflows would confirm institutional demand. Such demand would give the advance a stronger footing. Without positive flows, the rally remains hollow. Funding rates also matter. Sustained positive funding rates would show new longs entering. A return to negative rates would signal the squeeze is over. The current setup is neutral to bullish in the very short term. It depends on holding immediate support. The structure is not a clean trend reversal. It is a technical bounce within a low-volume environment. The Quantum-Resistant rotation and positive social sentiment provide a supportive layer. That layer is speculative. It can disappear quickly if Bitcoin loses $83,600 or if the total market cap slips below $2.80T.

My view is cautious. The 24-hour gain came from a short liquidation cascade. It did not come from a fundamental shift. The move was a leverage flush. It cleared out overextended bearish positions. It did not create a durable base of buyers. The altcoin rotation adds color. It does not change the core picture. The sector remains dependent on derivatives mechanics and a thin volume backdrop. A sustainable recovery requires more than a squeeze. It requires consistent spot demand and positive ETF flows. Until those appear, traders should treat this advance as a tactical bounce. The key question is whether Bitcoin can hold above $83,600 and whether the total market cap can reclaim $2.85T. A positive answer would improve the outlook. A negative answer would confirm that the squeeze has run its course.

For now, the market outlook is a cautious rebound. The advance lacks a solid foundation. The next few days will reveal whether this was a one-time leverage event or the start of a genuine trend reversal. The 0.87% Bitcoin gain and the 0.94% to 0.98% total market cap gain look modest. The 1,087% liquidation spike and the 31.45% drop in volume tell the real story. The 83% Nasdaq correlation and the 5.82 sentiment score add context. The $83,600 support and the $2.85T resistance define the near-term path. The $2.80T floor and the $2.94T target frame the risk and reward. Traders should watch ETF flows and funding rates. Those two inputs will show whether the market can move beyond a mechanical bounce. Until then, the rally remains a squeeze within a low-volume market. It is not a confirmed trend change.

The derivatives data deserves a closer look. A 1,087% surge in Bitcoin liquidations to $39.61M in 24 hours is not a normal reading. The concentration of $33.83M in short liquidations over 12 hours indicates bears were on the wrong side. Their forced buying pushed prices higher. Open interest rose 6.64% at the same time. That combination often marks a washout. It can create a sharp but short-lived move. When a market rises because shorts must cover, the buying ends when the shorts are gone. For a rally to continue, new buyers must step in. The 31.45% drop in volume suggests those new buyers have not arrived in size. That gap between price action and volume is the central risk.

The altcoin rotation offers a clue about trader behavior. The Quantum-Resistant category gained 5%. Nervos Network CKB gained 31.77%. The Altcoin Season Index at 64 indicates altcoins are in the lead. Social sentiment at 5.82 shows a bullish mood. These readings support a risk-on interpretation. They do not prove durable demand. A narrative-driven spike can reverse fast. If Bitcoin loses $83,600, the altcoin bid may vanish. If the total market cap loses $2.80T, the pullback could extend toward the 50-day EMA. The 7-day RSI at 45.28 and the negative MACD histogram show momentum is still healing. They do not confirm a new uptrend.

 

Source: https://e27.co/below-us82620-bitcoin-could-test-us81154-next-20261012/

Anndy Lian is an early blockchain adopter and experienced serial entrepreneur who is known for his work in the government sector. He is a best selling book author. The latest book is Web4: The Age of Autonomous Intelligence.

www.anndy.com
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Will artificial intelligence break your cryptocurrency wallet before quantum computers even exist?

Will artificial intelligence break your cryptocurrency wallet before quantum computers even exist?

Most people consider quantum computers the supreme danger to digital security today. We constantly hear stories about future supercomputers decoding the global internet. Cryptographers spend late nights worrying about the exact day a quantum machine boots up and breaks the elliptic curves protecting digital assets. A completely different risk creeps up on us right now. Advanced neural networks accelerate mathematical discovery at a breathtaking pace. This rapid advancement suggests smart software will likely solve the complex math protecting Bitcoin and Ethereum long before engineers build a functional decrypting machine.

To truly grasp this evolving timeline, we must examine the mechanics of the current quantum problem. Quantum computing relies heavily on Shor’s algorithm to break elliptic curve cryptography through brute-force computation. Security analysts classify this specific threat horizon as a long-term issue that remains years or decades away. Hardware engineers have demonstrated no physical machine capable of executing this theoretical attack against modern decentralized networks. The quantum narrative requires huge physical breakthroughs that stubbornly refuse to materialize on schedule. Software algorithms require no such hardware leaps to cause severe disruption.

The emerging software threat vector operates fundamentally differently. Machine learning exploits structured mathematical patterns and hidden shortcuts in curves and lattices. Instead of relying on sheer computational brawn, these programs find clever backdoors. The software identifies obscure relationships between numbers that human mathematicians miss completely. During an October 2026 discussion on the platform X, Ethereum researcher Justin Drake warned about this exact scenario. He stated that advanced software could weaken the Elliptic Curve Digital Signature Algorithm within months in a worst-case scenario. Bitcoin and Ethereum both rely heavily on this algorithm to secure user funds.

Ethereum co-founder Vitalik Buterin advanced this discussion further by highlighting a much deeper problem. Developers currently build next-generation defenses using lattice-based cryptography. They designed these frameworks specifically to resist future quantum attacks. Buterin noted that intelligent software could compress 50 years of human mathematical progress into just 2 years. This hyper-accelerated pace of research means algorithms might compromise these supposedly future-proof lattice frameworks before developers finish implementing them. Industry experts confirm this rapidly approaching reality by estimating the theoretical worst-case threat horizon for machine learning math at 2 years.

We must remember why developers chose the Elliptic Curve Digital Signature Algorithm in the first place. Satoshi Nakamoto selected the specific elliptic curve for Bitcoin back in 2009 because it offered strong security with relatively small key sizes. For over 15 years, this mathematical fortress successfully repelled every traditional hacking attempt. Mathematicians trust the discrete logarithm problem operating behind the scenes. They know conventional computers would need millions of years to guess a private key from a corresponding public key. Smart algorithms change this calculus entirely by teaching themselves novel ways to solve the discrete logarithm problem without brute-force guessing.

Despite these fascinating theoretical vulnerabilities, digital asset holders have no logical reason to panic today. Theoretical math puzzles differ vastly from practical exploits targeting live decentralized networks. Programmers have engineered no public machine learning attack that successfully cracks a properly generated Bitcoin or Ethereum private key at a practical cost. An artificial neural network identifying a mathematical shortcut in a research paper does not instantly translate into a rogue bot draining billions of $ from active cryptocurrency exchanges. Security researchers monitor these developments closely and continually test the limits of modern software against standard encryption. The defensive walls remain standing. They currently provide 100% protection against all publicly known machine learning attacks.

The most immediate danger to your digital wealth rarely comes from an advanced algorithm. Human error remains the greatest vulnerability in any security system. Reacting impulsively to theoretical software threats often leads to catastrophic financial losses. Vitalik Buterin explicitly advised users against scrambling to move funds immediately. He pointed out that users have historically lost far more money to poorly handled wallet migrations and malicious phishing tools than to actual network hacks. Malicious actors build fake migration tools that promise post-quantum security, only to steal users’ funds the moment a victim connects their wallet.

Instead of executing risky portfolio migrations, asset holders can manage their exposure through simple structural adjustments. The easiest defense is to change how you interact with the underlying blockchain. Cryptocurrency experts highly recommend keeping assets in addresses that have never sent an outbound transaction. When a user creates a new Bitcoin or Ethereum address and only receives funds, the network never exposes the underlying public key on the blockchain. This simple practice adds an incredibly strong layer of structural protection. Even a vastly intelligent learning model cannot attack a public key that remains completely invisible.

Users securing significant wealth should carefully evaluate their multi-signature wallet frameworks. Standard single-signature wallets represent a single point of failure. If an advanced program eventually breaks the underlying cryptography, a standard wallet offers 0 fallback protection. Savvy users opt for off-chain signature collection when designing multi-signature setups. If the primary algorithm fails under extreme computational pressure, a properly designed off-chain signature setup degrades safely to a single signer. This degradation prevents the entire smart contract from opening up to external exploitation. Smart contract architects prioritize this graceful failure mechanism.

The broader decentralized finance industry recognizes these looming challenges and is actively developing countermeasures. Industry roadmaps actively shift toward hash-based alternatives to secure the next generation of financial infrastructure. Developers steer both the Bitcoin and Ethereum networks toward hash-only designs. Technologists look closely at frameworks like SPHINCS and WOTS to provide the next layer of digital security. These hash-based systems lack the structured mathematical patterns that advanced algorithms find so easy to exploit. They offer a fundamentally different approach to protecting sensitive data.

My simple take is this. Understanding the fundamental difference between elliptic curves and hash functions explains why developers place so much faith in the latter. Elliptic curves rely on complex algebraic structures and predictable geometric relationships. A neural network excels at mapping these relationships and discovering hidden geometries. Hash functions operate more like chaotic blenders. You drop data into the hash function, and the underlying algorithm scrambles it into a fixed-length string of characters. No mathematical relationship exists between the input and the final output. Learning models struggle immensely with pure cryptographic chaos because chaos offers absolutely no predictable patterns to analyze.

The intersection of digital assets and smart algorithms promises a thrilling narrative over the next 10 years. The cryptocurrency community must remain vigilant as these learning models grow increasingly sophisticated. We must respect the potential for new technologies to rewrite the basic rules of mathematical impossibility. Preparing for these future risks represents an essential evolutionary step for decentralized finance. The developers maintaining Bitcoin and Ethereum possess the talent and the foresight to implement robust defensive upgrades long before theoretical threats become practical exploits. We simply need to exercise patience, practice good operational security, and let the brilliant cryptographers do their crucial work.

 

Source: https://www.benzinga.com/Opinion/26/10/62298011/will-ai-break-your-cryptocurrency-wallet-before-quantum-computers-even-exist

Anndy Lian is an early blockchain adopter and experienced serial entrepreneur who is known for his work in the government sector. He is a best selling book author. The latest book is Web4: The Age of Autonomous Intelligence.

www.anndy.com
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