BTC price faces 20% drop in weeks if Bitcoin avoids key level — analyst

CointelegraphPublicado em 2022-12-19Última atualização em 2022-12-19

Resumo

Bitcoin does not look good when it comes to sustained BTC price upside, traders warn, as GBTC reaches a fresh record discount.

Bitcoin stayed rigid below $17,000 at the Dec. 19 Wall Street open as skeptical traders feared more downside.

BTC/USD 1-hour candle chart (Bitstamp). Source: TradingView

BTC traders call time on upside potential

Data from Cointelegraph Markets Pro and TradingView showed BTC/USD lingering around the $16,700 mark, practically unmoved over the weekend.

The pair saw only fractional volatility at the open, as United States equities fell slightly. At the time of writing, the S&P 500 and Nasdaq Composite Index were down 0.5% and 1%, respectively.

For Bitcoin traders, there was little to celebrate, with consensus forming around the potential for testing lower levels next.

“Bearish as long as it stays below the $19k,” Crypto Poseidon summarized alongside a chart.

BTC/USD annotated chart. Source: Crypto Poseidon/ Twitter

Popular trader and analyst Rekt Capital highlighted $17,150 as an important level to reclaim to avoid further downside later on.

“If BTC continues to reject from the ~$17150 resistance... Then price could drop up to -20% to the downside in the coming weeks,” he predicted, uploading the 1-month BTC/USD chart.

Rekt Capital added that there was “still time for BTC to perform a Monthly Close above the ~$17150 level later this month,” but that “a Monthly Close below ~$17150 would confirm the beginnings of a breakdown from here.”

Michaël van de Poppe, founder and CEO of trading firm Eight, meanwhile offered a slightly more hopeful outlook.

With more U.S. economic data expected toward the end of the week, BTC/USD had the potential to break to the upside and target $17,300 to then offer “short opportunities.”

“No breakthrough, then looking for longs around $16.2K or $15.5K,” he countered.

BTC/USD annotated chart. Source: Michaël van de Poppe/ Twitter

Grayscale CEO: FTX was a "failure of people"

News that BinanceUS, the U.S. offshoot of largest crypto exchange Binance, had offered to acquire the assets of stricken lender Voyager, meanwhile had no tangible impact on market performance.

The latest development in the FTX saga, the announcement came as Binance itself continued to deal with what its CEO, Changpeng Zhao again called “FUD” over the weekend.

In a letter to investors, meanwhile, Michael Sonnenshein, CEO of investment firm Grayscale, sought to draw a clear distinction between FTX and crypto as a whole. Grayscale’s parent company, Digital Currency Group (DCG), had previously also become caught up in the FTX aftermath.

“FTX Was a Failure of People, Not a Failure of Crypto: Too many investors were harmed. From crypto to traditional finance, mainstream media, and D.C. – it seems few were spared from deception through false narratives and false documentation,” he wrote.

“We should not, however, conflate the actions of a few individuals and organizations with Bitcoin or Ethereum, the underlying blockchain technology, or smart contracts and decentralized finance applications.”

Grayscale’s flagship product, the Grayscale Bitcoin Trust (GBTC), traded at a 48.7% discount to the Bitcoin spot price as of Dec. 17 — its steepest discount ever, according to data from Coinglass.

GBTC premium vs. asset holdings vs. BTC/USD chart. Source: Coinglass

Leituras Relacionadas

Chip Stocks Lead U.S. Market Decline: Is AI Trading Being Hit by Both Interest Rates and Returns?

Chip stocks led a broad decline in US markets, with the Nasdaq dropping 2.2% and the S&P 500 falling 1.4%. This selloff reflects a dual challenge for the once-high-flying AI hardware trade: rising interest rate expectations and growing investor impatience for clear returns from massive AI capital expenditures. The pressure was most acute on hardware leaders. Nvidia fell about 4%, dipping below a $5 trillion market cap, while Micron plunged 13.2% ahead of its earnings report. Declines across memory, storage, AI, and mobile chips indicated a sector-wide retreat. The selloff spread globally, with South Korea's KOSPI index dropping nearly 10% as key suppliers SK Hynix and Samsung recorded double-digit losses. Investors appeared to be taking profits from the most crowded trades first. Macro headwinds intensified as market expectations shifted toward a more aggressive Federal Reserve. Forecasts for multiple rate hikes in 2026 pressured high-valuation tech stocks, which rely on long-term growth projections that become less attractive as discount rates rise. Concurrently, investors are scrutinizing the profit potential of the immense AI spending by cloud giants like Alphabet, Amazon, and Meta. While these expenditures drive demand for chips and hardware, the market is now questioning whether AI services will generate sufficient returns to justify the ongoing costs. This adjustment is not necessarily a bubble burst but a recalibration. AI demand fundamentals remain, but the narrative of endless growth can no longer fully offset concerns over higher interest rates and a longer path to profitability. Near-term direction may hinge on Micron's upcoming earnings guidance and incoming inflation data, which will influence both the AI demand outlook and the Fed's policy path. The market is transitioning from blindly buying growth to demanding clearer visibility on returns.

marsbitHá 1h

Chip Stocks Lead U.S. Market Decline: Is AI Trading Being Hit by Both Interest Rates and Returns?

marsbitHá 1h

OpenAI's New Paper: How to Train an AI that "Doesn't Deteriorate Under Pressure"?

OpenAI's new paper "Reinforcement Learning Towards Broadly and Persistently Beneficial Models" explores training AI to maintain safe, helpful, and honest behavior even under pressure, in unseen scenarios, or after being fine-tuned for harmful purposes. Moving beyond simple rule-based "don'ts," the research focuses on cultivating "beneficial traits" like honesty, risk-awareness, corrigibility, and transparency. It investigates if reinforcement learning (RL), often prone to "reward hacking" where models exploit loopholes, can instead be used to instill robust, generalized positive behaviors. Researchers created a multi-domain synthetic dialogue dataset covering areas like healthcare and law. They trained a model by replacing 5% of standard RL data with "beneficial trait" data. This model outperformed the baseline in 83% of 53 evaluations, showing average gains of 9.1% in alignment, safety, and helpfulness. Crucially, improvements generalized: a model trained only on healthcare "good behavior" data also performed better in 17 out of 19 non-healthcare alignment tests. The paper also tests "alignment persistence." When subjected to adversarial prompts or harmful fine-tuning, the beneficial trait model showed greater resilience, with smaller performance drops and less "spillover" of bad behavior to unrelated tasks. While not a complete solution, this work suggests a shift from post-hoc correction to proactively shaping robust, principled AI behavior, a critical step for deploying models in high-stakes, complex decision-making scenarios.

marsbitHá 1h

OpenAI's New Paper: How to Train an AI that "Doesn't Deteriorate Under Pressure"?

marsbitHá 1h

Goldman Sachs Revisits the State of the AI Boom: Strong Earnings Will Override Valuation Concerns Until the Investment Cycle Peaks, Volatility to Rise Further

Goldman Sachs discusses the current AI investment boom, arguing it is not a simple repeat of the 1999-2000 bubble. Unlike the dot-com era, current valuations are not wildly out of control because earnings expectations are rising in tandem with stock prices. The key issue is that market prices have already priced in substantial optimism, making them sensitive to any narrative shifts. The core risk has shifted from "valuation bubble" to "earnings bubble." While strong profits from companies in semiconductors, cloud infrastructure, and data centers currently outweigh valuation concerns, this is dependent on the ongoing capital expenditure cycle. The true test will be whether these robust earnings can be sustained after the investment cycle peaks. Current market prices imply optimistic assumptions, such as faster AI adoption, higher productivity gains, and a larger share of economic profits going to capital owners. The AI boom may also be masking relative weakness in the non-AI sectors of the economy. As a result, market volatility is expected to rise. Goldman recommends that investors consider maintaining exposure while adding downside protection, such as put options, to manage potential drawdowns.

marsbitHá 1h

Goldman Sachs Revisits the State of the AI Boom: Strong Earnings Will Override Valuation Concerns Until the Investment Cycle Peaks, Volatility to Rise Further

marsbitHá 1h

Zuckerberg Enters the Prediction Market

Mark Zuckerberg's Meta has entered the predictive markets arena with a new app called "Arena." Currently in an early experimental phase, Arena will initially operate as a standalone app using a points-based system where users can predict outcomes on politics, sports, and world events without real money. Meta plans to leverage its vast daily active user base for growth. The move comes as the predictive market industry sees explosive growth, with platforms like Polymarket and Kalshi handling hundreds of billions in volume. While a points system avoids initial regulatory hurdles, Meta hasn't ruled out introducing real-money betting later. The strategy aligns with Meta's pattern of adopting popular trends, though challenges remain, including regulatory scrutiny and the historically mixed success of its standalone apps.

Foresight NewsHá 1h

Zuckerberg Enters the Prediction Market

Foresight NewsHá 1h

Semiconductor Stock Rebound: Is the Technical Correction Over or a Trend Reversal?

The core of recent semiconductor stock volatility is not about daily price swings, but rather the market questioning whether AI-driven semiconductor pricing has entered a new phase. Following a sharp sell-off in Korean stocks on June 23rd, led by Samsung and SK Hynix, a subsequent rebound is seen more as a technical positioning adjustment rather than a confirmed trend reversal. The key variable is HBM (High Bandwidth Memory), essential for AI chips. Its supply-demand imbalance granted memory makers significant pricing power. The current market focus is on whether this dynamic remains strong enough to justify elevated valuations. All eyes are on Micron's upcoming earnings report. The critical factor is not whether results meet already high expectations, but whether the company's guidance confirms that AI memory pricing power, order visibility, and future margins are still expanding. Micron's outlook will serve as a crucial test for the broader AI semiconductor chain, including Samsung, SK Hynix, and other infrastructure players. The recent bounce appears to be a pre-earnings positioning repair. For it to evolve into a sustained uptrend, concrete evidence is needed that the AI infrastructure expansion cycle's fundamentals—particularly for high-end memory—remain robust and can continue to surpass elevated market expectations. The risk is that strong demand alone may not be sufficient if future guidance hints at peaking momentum or increasing supply-side pressures.

marsbitHá 1h

Semiconductor Stock Rebound: Is the Technical Correction Over or a Trend Reversal?

marsbitHá 1h

Trading

Spot
Futuros
活动图片

Categorias popularesright-arrow

Etiquetas Popularesright-arrow