us-market-bubble-detector

You can detect a market bubble by quantitatively analyzing financial indicators such as the Put/Call Ratio, VIX, margin debt, and IPO data. The skill applies strict qualitative criteria to this data to prevent confirmation bias and generate a total risk score.

Detecting a stock market bubble requires quantitative data collection including Put/Call Ratio, VIX, margin debt, market breadth, and IPO data. The skill uses these specific financial indicators to evaluate current market bubble risk and assign a granular risk phase.

To prevent confirmation bias during market bubble evaluation, a two-phase process applies strict qualitative adjustments to quantitative scoring. This ensures risk phases—ranging from Normal to Critical—are determined objectively rather than by selective data interpretation.

Yes, you can use Python with pandas and numpy for data-driven bubble detection. The skill requires these libraries to collect, process, and evaluate market data, applying strict criteria to output risk phases and a detailed action matrix for investors.

For different market bubble stages, you should follow a detailed action matrix that outlines risk budget, entry points, profit-taking, stops, and short-selling considerations. The matrix provides specific strategies based on the total score's risk phase, from Normal to Critical.