How Long Will This Bear Market Last? | EP 72

This episode explores a critical divergence between crypto-native and traditional finance sentiments, highlighting key economic indicators and emerging tech trends that suggest a continued bull market, despite widespread bearish predictions.

Market Sentiment Divergence

• The hosts open by reflecting on their previous warnings about a potential market top, acknowledging they were premature in calling the cycle's peak. They now believe the market is mid-cycle, with potentially 6-18 months remaining, viewing the recent downturn as a healthy correction.
• The hosts discuss the prevailing bearish sentiment among prominent crypto traders and analysts.
• Anom, a notable figure, is cited as predicting a bear market based on on-chain metrics and macro factors like tariffs and AI's impact.
• CryptoQuant's Ke Yong-Ju also signals a Bitcoin bull cycle end, citing drying liquidity and whale selling.
• "Every on-chain metric signals the bare market with fresh liquidity drying up," Ke Yong-Ju stated, highlighting the data-driven pessimism.

Counter-Arguments: Bullish Indicators

• Despite the bearish outlook, the hosts present a strong case for continued market optimism, focusing on robust economic indicators and institutional interest.
• The overall US economy is performing well, with rising corporate earnings forecasts and historically low high-yield spreads.
• Inflation is down in the short term, contrary to expectations from tariff discussions.
• Unemployment remains near historic lows, indicating economic strength.
• One host mentions, "The economy looks good... inflation is down... unemployment rate is also near the lows," directly contradicting bearish macro arguments.

Tariffs and Economic Impact

• The discussion delves into the potential impact of tariffs, emphasizing that while uncertainty is a risk, the actual economic effects are not yet visible.
• Auto manufacturers like BMW are taking steps to absorb costs, offering price protection to US consumers, at least in the short to medium term.
• The hosts note that the uncertainty surrounding tariffs is more damaging than the tariffs themselves.
• "The worst thing about tariffs is uncertainty," one host emphasizes, suggesting that clarity on tariff policies would be beneficial.

Crypto vs. TradFi Sentiment

• A significant divergence is highlighted between the bearish sentiment in the crypto-native community and the bullish outlook among traditional finance institutions.
• There's a notable discrepancy between crypto-native bearishness and institutional bullishness, a divergence not seen since the FTX collapse.
• Institutions are increasing their exposure to crypto, with a $50 billion increase in stablecoins and a near doubling of tokenized treasuries since Trump's election.
• "Since Trump's election, we've added $50 billion in stablecoin," one host notes, illustrating the growing institutional interest.
• Tokenized T-bills are preferred over stablecoins by institutions due to their secure off-ramp and reduced counterparty risk.

Layer-1 Developments: Athena and Ondo

• The conversation shifts to the strategic implications of Athena and Ondo launching their own Layer-1 blockchains, focusing on the potential impact on Ethereum.
• Athena and Ondo are launching Layer-1 chains with permissioned validators, primarily from traditional finance.
• This move is seen as potentially "unbundling" Ethereum's DeFi moat, with Standard Chartered noting that Base has already diverted significant value from Ethereum.
• "RWA will likely need its own chain," one host states, explaining the rationale for permissioned chains with known validators and greater control.
• The hosts debate the purpose and target audience of these permissioned chains, questioning whether they solve a real problem or are merely marketing initiatives.

Coinbase and Tokenization

• Coinbase's potential role in tokenizing stocks is discussed, highlighting its strong position due to distribution, regulatory experience, and existing infrastructure.
• Coinbase and Base are well-positioned to tokenize stocks, leveraging their distribution, regulatory compliance, and experience with traditional finance.
• They are already exploring tokenized stablecoins for various countries, indicating a broader push into tokenization.
• "Out of all the companies in the world, Coinbase and Base are probably best positioned... in terms of tokenizing stocks," one host asserts.

Robinhood's Crypto Ambitions

• Robinhood's increasing focus on crypto and tokenization is examined, including its partnership with Kalshi to offer prediction markets.
• Robinhood's manifesto highlights ambitions to tokenize stocks and real estate, aiming for one-click real estate transactions.
• The partnership with Kalshi, a CFTC-regulated entity, allows Robinhood to offer prediction markets to its users.
• The hosts express concern that large Web2 companies like Robinhood could "eat crypto startups alive," posing a threat to the crypto ecosystem.

AI Developments: China vs. US

• The discussion transitions to AI, exploring the competitive landscape between China and the US, and the implications for crypto.
• The hosts note that Chinese AI startups appear to be on par with, or even ahead of, their US counterparts, particularly in model efficiency.
• DeepSeek, Qwen (Alibaba's model), and other Chinese models are highlighted for their performance and smaller size, enabling local deployment.
• "China is at least on par with the US," one host concludes, based on the available data points.
• The US export restrictions on Nvidia chips have seemingly spurred China to innovate on model algorithms and software, potentially creating a long-term advantage.

Localized LLMs and Privacy

• The trend towards smaller, more efficient LLMs that can run locally is discussed, emphasizing the benefits for privacy and performance.
• Localized LLMs, enabled by smaller model sizes, offer improved privacy and responsiveness by running inference locally rather than in the cloud.
• This trend could be bullish for companies like Apple and Google, which prioritize user privacy.
• "Localized LLMs... enables the ability to run them locally on your machine or even on your mobile phone," one host explains.
• The hosts discuss potential applications, such as personalized health insights, that could benefit from local LLM processing.

Vibe Coding and its Implications

• The concept of "vibe coding" (AI-assisted coding) is explored, highlighting its potential to empower non-technical founders and democratize app development.
• Vibe coding platforms like Lovable and others are making it easier for non-technical individuals to create demos and MVPs.
• This trend could lead to a shift in the founder landscape, with less emphasis on technical skills and more on product-market fit.
• "There will be a point where... to get to product-market fit, you don't actually need an engineer," one host predicts.
• The hosts discuss the potential for vibe coding to empower individuals in emerging countries, enabling them to build localized solutions.

Tokenizing Early-Stage Ideas

• The potential for tokenizing early-stage ideas and startups is discussed, highlighting platforms like Terabase that facilitate this process.
• Tokenizing early-stage ideas offers a new approach to startup funding and growth, creating a "circular funding vehicle."
• This contrasts with the traditional approach of tokenizing existing company shares, which faces friction and limited demand.
• "Instead of bringing the secondary market on-chain, you bring the primary market on-chain," one host explains.

Electric Vehicles and Robotics

• The conversation briefly touches on advancements in electric vehicles (EVs) and robotics, highlighting China's growing influence in these sectors.
• BYD, China's largest EV manufacturer, is launching a 5-minute charging system, showcasing rapid innovation in the EV space.
• Robotics is identified as a significant growth area, with potential applications in factories, healthcare, and general-purpose humanoids.
• The hosts discuss Elon Musk's optimistic projections for the humanoid market, while acknowledging his tendency to exaggerate.

Crypto and Robotics Intersection

• The potential intersection of crypto and robotics is explored, with a focus on data and incentives.
• The hosts struggle to identify clear use cases for crypto in robotics beyond payments.
• One potential application is using crypto incentives to bootstrap data for training robotics, but the necessity of this approach is questioned.
• "If anything, it's data," one host suggests, referring to the potential for crypto to incentivize data collection for training.

Final Thoughts and Market Outlook

• The episode concludes with a reaffirmation of the bullish outlook, emphasizing the importance of distinguishing between sentiment and underlying economic realities.
• The hosts reiterate their belief that the market is mid-cycle, with potential for further growth.
• The recent correction is attributed to sentiment around tariffs, which provided an excuse for a pullback in overvalued stocks.
• "This breakdown was actually a good thing," one host states, suggesting it provides more breathing room for the market.
• Bitcoin is identified as the preferred asset, while Ethereum's fundamentals are questioned.

The discussion underscores a critical market phase: while crypto-native sentiment is bearish, strong economic indicators and institutional interest suggest continued growth. Investors should prioritize data-driven analysis over prevailing sentiment, focusing on emerging trends like localized LLMs and tokenization.