RazorStack Trading

RazorStack Trading is an AI-assisted research and paper-trading workspace designed to make quantitative decision-making more explainable, measurable, and risk-aware. The platform combines AI research agents, a quantitative signal engine, portfolio analytics, backtesting, and a server-side risk gate into one integrated workflow. Users can discover market opportunities, inspect the evidence behind a signal, evaluate historical behavior, review data quality and portfolio implications, and submit only eligible proposals for risk review. At the center of RazorStack is a transparent quant engine that combines momentum, trend, volume confirmation, mean-reversion bias, and volatility quality into a structured BUY, SELL, or HOLD signal. Each output includes supporting indicators, market-regime context, drawdown measures, realized volatility, strategy rationale, and data-source metadata. The platform is intentionally designed around a clear safety boundary: quantitative and AI components may propose, but the risk service remains the sole approval authority. The browser cannot bypass risk controls or access broker credentials. HOLD signals cannot create orders, and every proposal is intended to move through an auditable lifecycle—from proposal and approval to adjustment, rejection, submission, or failure. RazorStack currently supports offline and mock-broker workflows for safe development and demos, with an architecture prepared for Alpaca paper trading, persisted strategy outcomes, richer data-quality tracking, correlation analysis, options metrics, and live paper-performance monitoring.