The First Crypto President: Presidential Power and Cryptocurrency Markets During Trump's Second Term (2025-2029)

Battle Count: 60

The paper provides valuable context on market microstructure failures (oracle desynchronization, exchange freezes, order book fragmentation, absence of circuit breakers), leverage dynamics (10x-25x positions), and cascading liquidation mechanics ($19B in 24 hours). However, it does not propose specific trading strategies, quantitative models, or algorithmic approaches. Its relevance is primarily in understanding risk factors, event-driven market dynamics, and the asymmetric risk distribution that affects different participant types. Useful for risk management frameworks and understanding regime shifts in politically-linked assets, but not directly implementable as a trading system.

This is a descriptive-analytical paper rather than a model implementation paper. There are no algorithms to implement, no models to train, and no code to reproduce. The 'implementation' would involve replicating the data collection from multiple sources (Bloomberg, CoinGlass, Etherscan, SEC filings) and performing basic time-series analysis and on-chain transaction tracking. The qualitative institutional assessment component is inherently non-reproducible in a computational sense.

The paper uses publicly available data sources (CoinGlass, CoinMarketCap, Etherscan, Bloomberg Billionaires Index) and SEC filings, but the analysis is largely qualitative and interpretive. No code or specific computational pipeline is provided. The mixed-methods approach combining quantitative data with qualitative institutional assessment makes full reproduction difficult. Some data sources (Bloomberg Terminal) require paid subscriptions. The paper acknowledges limitations from pseudonymous blockchain data and politically contested narratives.