Flood

Robust demand for share sales, institutional discipline, and a wall of worry suggest the equity market is healthy and not overextended. The S&P 500 selloff on Friday is a buying opportunity, and the market has a clear path to 8000 and beyond this year. Positioning remains neutral, leaving room for further upside.

Short ETH as a hedge against broad crypto exposure; speaker frames ETH shorts as an obvious hedge vehicle, implying relative underperformance or vulnerability versus the broader crypto basket.

Flood states, "I am still bullish Bitcoin... good time to rewrite, but definitely still long-term bullish." He notes that if the thesis (monetary debasement) is unchanged, lower prices are better entries. He argues that fiscal deficits and debt structuring make currency debasement inevitable. While the "nation-state adoption" thesis hasn't played out yet, the macro backdrop for a store of value remains intact. LONG. He views current apathy and price drawdowns as an accumulation opportunity. Quantum computing risks (mentioned as a specific idiosyncratic risk to BTC).

Flood says, "If you had to weight long societal unrest, political unrest... you should do that." Avi Felman clarifies, "that's probably the gold trade," and Flood agrees. Political volatility is increasing globally. In times of "societal unrest," capital flees to non-sovereign stores of value. While BTC is the digital version, Gold is the traditional beneficiary of this specific type of fear. LONG. A hedge against political instability and election cycles. High real rates typically hurt gold; easing of geopolitical tensions.

Flood states, "I wouldn't fade AI this year, candidly... the potential upside for AI is infinite." Even for a crypto trader, the capital flows into AI are undeniable. The narrative of "infinite returns" (AGI/Digital God) overrides valuation concerns. If capital must go somewhere, it flows to the sector promising the biggest technological leap. LONG. Momentum trade based on capital flows and narrative dominance. Valuation bubbles; regulatory scrutiny on big tech; diminishing returns on LLM scaling.

Flood explicitly says, "We've been adding recently [to Robinhood]." He notes HOOD serves the "average everyday American retail." The "App Thesis": Value accrues to the interface that owns the customer. As US regulations potentially open up for perps/crypto derivatives, Robinhood is best positioned to capture that volume because they already own the user base. LONG. A bet on the "super app" aggregation of trading (crypto + stocks + perps). Regulatory delays in allowing perps in the US; competition from DeFi if UX improves.

Flood discusses his firm's massive bet on Hyperliquid (HYPE), noting they were a significant amount of the "hour one, day one volume." He believes the market fundamentally misprices the revenue potential of perp DEXs compared to centralized exchanges (Binance makes ~$20B/year; market priced HYPE as if the sector makes $1B). HYPE captures the "on-chain, tech-native" trader, complementing the HOOD bet. LONG. High conviction bet on decentralized perpetuals gaining market share. Smart contract risk; regulatory crackdowns on DeFi.

Flood states, "I wouldn't fade AI this year, candidly... the potential upside for AI is infinite." Even for a crypto trader, the capital flows into AI are undeniable. The narrative of "infinite returns" (AGI/Digital God) overrides valuation concerns. If capital must go somewhere, it flows to the sector promising the biggest technological leap. LONG. Momentum trade based on capital flows and narrative dominance. Valuation bubbles; regulatory scrutiny on big tech; diminishing returns on LLM scaling.

Flood states, "I wouldn't fade AI this year, candidly... the potential upside for AI is infinite." Even for a crypto trader, the capital flows into AI are undeniable. The narrative of "infinite returns" (AGI/Digital God) overrides valuation concerns. If capital must go somewhere, it flows to the sector promising the biggest technological leap. LONG. Momentum trade based on capital flows and narrative dominance. Valuation bubbles; regulatory scrutiny on big tech; diminishing returns on LLM scaling.