This blog post demonstrates an event-study workflow using stock prices and adverse-event signals. We identify days with elevated adverse event reports and measure stock returns in surrounding windows, validating the asymmetric reaction pattern documented in academic literature. This notebook is intended as a methodology framework for data ingestion and event-study analysis. It is not a reproduction of the specific results found in the academic papers, nor is it financial advice. It demonstrates how to fuse disparate data sources (yfinance, openFDA) in a single analytical view.
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This notebook is configured for JAZZ (Jazz Pharmaceuticals) and XYREM. The markdown explanations, literature references, and results are specific to this ticker/drug combination. If you run this with a different ticker or drug, the outputs will change but the explanatory text won't automatically update. Treat this as a methodology template rather than a one-click report generator. Defaults used to build this notebook: ticker JAZZ, PRICE_FROM_INPUT 2005-01-01, PRICE_TO_INPUT 2025-12-31, drug XYREM, START_DATE_INPUT 2005-01-01, END_DATE_INPUT 2025-12-31.
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FAERS Distribution
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Days exceeding the red threshold line are classified as high-FAERS events.
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DIY: Compare ABBV (large-cap) with a smaller* biotech like SRPT, etc. Narrow the date range to periods around known drug safety controversies