us-market-bubble-detector

Assess market bubble risk objectively by collecting quantitative metrics like Put/Call ratios, VIX, margin debt, breadth, and IPO data, then applying a mechanical scoring framework to classify market phases and generate actionable investment decisions.

The Minsky model framework for market bubble evaluation is a data-driven, two-phase process that mandates quantitative data collection first, followed by strictly limited qualitative adjustments to prevent confirmation bias during risk assessment.

Identify the current market bubble phase by evaluating technical indicators against strict criteria, classifying conditions into Normal, Caution, Elevated Risk, Euphoria, or Critical phases to establish corresponding risk budgets for investment decisions.

Yes, you can use yfinance and pytrends for market bubble technical analysis. These dependencies support data retrieval for evaluating valuation metrics and technical indicators required by the quantitative risk assessment framework.

The limitation of qualitative adjustments in bubble risk assessment is that they are strictly limited by the framework to prevent confirmation bias, ensuring that objective metrics like margin debt and breadth drive the mechanical scoring.

Yes, the us-market-bubble-detector skill supports VIX and margin debt evaluation. It prioritizes these objective metrics alongside Put/Call ratios, breadth, and IPO data to calculate phased risk assessments and actionable recommendations.