Arthur Hayes, Former Ethereum Skeptic, on Why the Merge Makes Him Bullish on ETH - Ep. 393
Arthur Hayes, cofounder of BitMex, discusses how he’s trading the Merge, the impact of macroeconomic policy in the markets, his career as a writer, and much more.
Show highlights:
- how crypto is reconfiguring how humans do finance over the internet
- why Arthur initially thought Ethereum was worthless
- how NFTs allow users to trade human culture and will unlock trillions of dollars of value
- why Ethereum doesn’t even need to be deflationary
- whether other layer 1s can take some market cap from Ethereum
- why Arthur thinks that a successful Merge is understated and why this is a valid reason for hedging
- why he thinks an Ethereum proof of work chain won’t succeed and how Arthur will trade ETHPoW
- why LDO, Lido’s token, is a riskier bet but has more potential gains
- how he believes the Shanghai upgrade will impact ETH’s price
- whether the Merge affects BTC’s narrative as digital gold and whether the inflation hedge theory of Bitcoin still holds
- why Bitcoin is a measure of USD liquidity and why the Fed rates don’t matter as much as everyone thinks
- whether hedge funds and institutional investors would want to invest in crypto given the high correlation with traditional markets
- what Arthur believes the impact of a potential US recession would be on the crypto markets
- why he believes the real economy is not relevant to the financial markets
- whether algorithmic stablecoins are doomed to fail
- how the credit cycle works and how it repeats again and again
- Arthur’s method for identifying good projects to invest in
- how Arthur became such a good writer
- whether BTC is money and the religious aspect of the Bitcoin culture
Arthur:
Episode Links
Previous Coverage on Unchained:
- With the Merge, Will Ethereum Take Over Bitcoin’s Title as Digital Gold?
- Why Kevin Zhou Believes Ethereum Will Have 3 Forks After the Merge
- Post-Merge, If Lido Becomes Dominant, What Does That Mean for Ethereum?
Arthur’s posts discussed during the show:
- Eth-Flexive
- Ether, a double digit shitcoin
- Teach me Daddy (on USD liquidity and Macroeconomics)
Macroeconomics:
- Adam Cochran on the Fed’s QT
- Pantera Capital’s newsletter
ETH Trade:
- Whether Ethereum’s Merge is priced in
- Gauntlet’s view on the Merge
- BTC correlation with stocks
ETH Post-Merge Dynamics:
- Cumberland on the Ethereum dynamics after the merge
- Miles Suter on the implications of the Merge
- The triple point asset
Learn more about your ad choices. Visit megaphone.fm/adchoices
Available Results
Generated results are saved to your library for reuse and search.
Choose Template
Pick the result you want. You can review provider and model before generating.
A concise first-pass summary for understanding the episode quickly.
A comprehensive, source-grounded extraction of the reusable knowledge in an episode.
A comprehensive extraction focused on opportunities, strategy, markets, and company building.
Explicit actions, next steps, habits, recommendations, and things to avoid.
Repeatable methods, frameworks, mental models, processes, and systems.
A dedicated inventory of concrete resources named in the episode.
A concise first-pass summary for understanding the episode quickly.
A detailed readable summary organized by chapter or topic.
A navigable map of subjects, topic flow, and suggested chapters.
A comprehensive, source-grounded extraction of the reusable knowledge in an episode.
Reusable atomic knowledge units extracted from the episode.
A comprehensive extraction focused on health practices, protocols, claims, and safety caveats.
A comprehensive extraction focused on opportunities, strategy, markets, and company building.
Explicit actions, next steps, habits, recommendations, and things to avoid.
A dedicated inventory of concrete resources named in the episode.
A dedicated analysis of warnings, limitations, trade-offs, weak evidence, and uncertainty.
A concise first-pass summary for understanding the episode quickly.
A detailed readable summary organized by chapter or topic.
A navigable map of subjects, topic flow, and suggested chapters.
A comprehensive, source-grounded extraction of the reusable knowledge in an episode.
Reusable atomic knowledge units extracted from the episode.
A comprehensive extraction focused on health practices, protocols, claims, and safety caveats.
A comprehensive extraction focused on opportunities, strategy, markets, and company building.
Scientific findings, mechanisms, studies, hypotheses, and the limits of the evidence discussed.
Technologies, AI models, technical methods, capabilities, limitations, and adoption implications.
Investment theses, assets, catalysts, valuation reasoning, time horizons, and risks.
Chronologies, actors, causes, consequences, turning points, and competing historical interpretations.
Policies, proposals, stakeholders, arguments, implementation constraints, and predicted effects.
Career paths, skills, hiring signals, workplace decisions, transitions, and limitations of the advice.
Behavioral mechanisms, biases, motivation, habits, emotions, interventions, and evidence limitations.
Economic mechanisms, incentives, indicators, market structure, forecasts, and uncertainty.
Leadership principles, team systems, organizational design, culture, feedback, and failure modes.
Audience, positioning, messaging, acquisition, retention, experiments, metrics, and failed approaches.
Teaching methods, learning strategies, practice, feedback, assessment, and effectiveness evidence.
Theses, premises, arguments, objections, values, thought experiments, and unresolved questions.
Communication patterns, conflict, boundaries, expectations, repair methods, and contextual limitations.
Books, papers, authors, courses, and other learning resources mentioned in the episode.
Repeatable methods, frameworks, mental models, processes, and systems.
Explicit actions, next steps, habits, recommendations, and things to avoid.
Memorable statements and important claims with attribution and source context.
A dedicated inventory of concrete resources named in the episode.
A dedicated analysis of warnings, limitations, trade-offs, weak evidence, and uncertainty.