An overview of research themes, analytical notes, teaching cases, and conceptual frameworks examining how financial theory, market data, artificial intelligence, and human judgment interact in digital-asset markets.
Examines how liquidity conditions, market microstructure, and derivatives data shape risk assessment in cryptocurrency markets.
Explores machine-learning methods for market-event detection, regime classification, and analytical decision support.
Develops principles for human oversight, accountability, and risk responsibility in AI-assisted financial decision-making.
Analyzes how liquidity shifts and deleveraging episodes influence volatility and liquidation cascades.
Presents a framework for identifying and characterizing market regimes in digital-asset markets.
Explores the interactions among open interest, funding rates, and liquidation risk.
A classroom case on integrating AI analysis with human judgment in contract trading.
A case study on position sizing, stop management, and scenario-based risk control.
A practical framework that combines human expertise with AI tools for market analysis.
Contract trading involves substantial risk and is not suitable for every investor.
Educational content does not constitute investment advice.