vcp-screener

Screen S&P 500 stocks for the Volatility Contraction Pattern (VCP) by running automated analysis scripts that detect tightening consolidations and identify Stage 2 uptrends. The skill fetches required historical price data from financial modeling APIs to generate potential breakout candidates.

A Stage 2 uptrend is a technical phase where a stock experiences significant price increases. VCP screening identifies it by applying trend analysis and pattern detection algorithms to historical data, scoring stocks based on the strength of their volatility contraction before a potential breakout.

You can use pandas and numpy for investment research and stock screening because the skill utilizes these dependencies alongside requests to fetch data from financial modeling APIs. This stack processes historical prices to detect VCP formations and score Stage 2 uptrends.

The best way to identify potential breakout candidates in the S&P 500 is using automated trend analysis and pattern detection. This approach scans for the Volatility Contraction Pattern and Stage 2 uptrends, outputting a scored list of stocks showing strong consolidation behaviors.

You need a financial modeling API to run VCP stock screening because the skill requires fetching historical market data for accurate pattern detection. External data retrieval is necessary to perform the internal trend analysis and calculate the Volatility Contraction Pattern scores.

VCP screening focuses on tightening consolidation because the Volatility Contraction Pattern indicates decreasing price volatility before a potential breakout. This Stage 2 uptrend behavior suggests that supply is being absorbed, making the stock a strong candidate for significant price increases.