Research notes on portfolio intelligence, risk models, and the future of AI-assisted investing
The process and math behind ItoFlow's in-house risk model for global stocks, ETFs, style tilts, mixed-asset covariance, and single-stock shocks.
Hooks can't scale. Sub-agents block. We built asynchronous critique agents that use spaced repetition to course-correct long-running AI trading strategies without ever stalling the main execution.
When AI agents decide to rebalance at 10 PM, naive systems execute at stale prices. Here's how we built async execution that queues trades and waits for each exchange to open.
The patterns that made Claude Code successful don't transfer to investing. Here's why the challenges are fundamentally different, and harder in ways that aren't immediately obvious.
Real analysis of AAPL, MSFT, GOOGL, NVDA, and META reveals why Google returned 44% while Apple limped to 6.5%. Discover how combining fundamental and quantitative analysis delivers +4.99% better returns.
How AI agents are revolutionizing financial analysis and democratizing institutional-grade quantitative research capabilities.