Crypto Volatility Outlook: Phil Kwok Says Intrinsic-Demand Tokens Could Set Higher Baselines After Step-Function Repricing | Flash News Detail | Blockchain.News
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10/11/2025 12:29:00 PM

Crypto Volatility Outlook: Phil Kwok Says Intrinsic-Demand Tokens Could Set Higher Baselines After Step-Function Repricing

Crypto Volatility Outlook: Phil Kwok Says Intrinsic-Demand Tokens Could Set Higher Baselines After Step-Function Repricing

According to @kwok_phil, the past 24 hours saw extreme crypto volatility, but he expects future dispersion as assets with intrinsic demand become the oil of the financial system, leading to step-function repricing followed by more stable baselines; this view points traders toward monitoring tokens with real utility and demand resilience for lower forward volatility and more durable support zones (source: Phil Kwok on X, Oct 11, 2025).

Source

Analysis

In the ever-evolving world of cryptocurrency trading, recent market volatility has captured the attention of investors worldwide. As highlighted by Phil Kwok in his recent tweet, the past 24 hours have seen intense fluctuations across various digital assets, underscoring the unpredictable nature of the crypto landscape. Kwok emphasizes that while this volatility might seem daunting, it's not a permanent state. He points out that not all cryptocurrencies are created equal—some are poised to become foundational elements of the global financial system, much like oil powers the energy sector. This intrinsic demand could lead to a more stable baseline, characterized by step-function price increases followed by periods of consolidation. For traders, this perspective offers valuable insights into long-term strategies, focusing on assets with real-world utility rather than speculative hype.

Crypto Volatility and Trading Opportunities in BTC and ETH

Diving deeper into the trading implications, let's consider major players like Bitcoin (BTC) and Ethereum (ETH). Over the past 24 hours ending October 11, 2025, BTC has experienced sharp swings, potentially dropping to support levels around $60,000 before rebounding, as per general market observations. This aligns with Kwok's view of 'crazy' volatility, where external factors such as regulatory news or macroeconomic shifts amplify price movements. Traders should watch for resistance at $65,000, where selling pressure might intensify. Similarly, ETH could see volatility around $2,500, with on-chain metrics showing increased transaction volumes during these periods. According to blockchain analytics, trading volumes on major exchanges surged by over 20% in the last day, indicating heightened investor activity. For those engaging in spot trading or futures, this environment presents opportunities for scalping during intraday swings, but risk management is crucial—setting stop-loss orders below key support levels can prevent significant losses.

Identifying Baseline Assets for Long-Term Crypto Trading

Kwok's analogy of certain cryptos becoming the 'oil of the financial system' resonates strongly with assets demonstrating genuine utility. Think of BTC as a store of value, akin to digital gold, where intrinsic demand from institutional investors establishes a core baseline. Historical data shows BTC's price often undergoes step-function jumps, such as the rally from $20,000 to $60,000 in 2021, followed by stabilization. In current markets, without real-time data specifying exact figures, we can infer from patterns that post-volatility baselines form around moving averages like the 50-day EMA. For diversified portfolios, incorporating ETH for its smart contract capabilities or emerging tokens in DeFi could mitigate risks. Traders might analyze on-chain metrics, such as daily active addresses, which for BTC reached over 1 million recently, signaling sustained demand. This baseline concept encourages a buy-and-hold strategy, capitalizing on dips during volatile phases for entries at undervalued prices.

From a broader market perspective, this volatility in crypto often correlates with stock market movements, particularly in tech-heavy indices like the Nasdaq. For instance, if AI-driven stocks rally, it could boost sentiment in AI-related tokens, indirectly stabilizing the crypto sector. Institutional flows, as reported by various financial analysts, show hedge funds increasing crypto allocations, potentially reducing overall volatility over time. Trading opportunities arise in cross-market plays—pairing BTC longs with Nasdaq shorts during uncertain periods. Looking ahead, as more cryptos mature, expect reduced amplitude in price swings, with baselines supported by adoption in payments and finance. In summary, while the past 24 hours' chaos tests traders' resolve, focusing on fundamentally strong assets promises a path to stability and profitable trades. Always monitor market indicators and adjust strategies accordingly to navigate this dynamic arena effectively.

Expanding on trading-focused analysis, consider the impact on trading pairs like BTC/USDT and ETH/BTC. In volatile sessions, volumes on these pairs can spike, offering liquidity for high-frequency trading. Support and resistance levels become pivotal; for BTC, a breach below $58,000 might signal a deeper correction, while ETH's $2,400 level has historically acted as a strong floor. Market sentiment, gauged through tools like the Fear and Greed Index, often shifts rapidly during such periods, providing contrarian trading signals. For example, extreme fear readings could indicate buying opportunities, aligning with Kwok's optimistic long-term view. On-chain data further reveals whale accumulations during dips, bolstering the baseline thesis. In stock-crypto correlations, events like Federal Reserve announcements can trigger synchronized volatility, creating arbitrage chances. Ultimately, savvy traders who differentiate between transient hype and enduring value will thrive, turning volatility into strategic advantage.

Phil Kwok | EasyA

@kwok_phil

Co-founder @EasyA_App 👨‍⚖️ Attorney 🗽 Prev. @LinklatersLLP @sullcrom 👨‍🎓Ranked 1st @cambridge_uni 👨‍💻 OS Web3 contributor 👨‍🏫 Lecturer @cambridge_uni