Market Reactions to Material Cybersecurity Incidents

Battle Count: 71

The paper identifies a statistically significant negative market reaction (-3.07% average) to cybersecurity disclosures, with a particularly strong effect for small-cap companies (-7.49% vs +0.43% for larger firms). This suggests potential for event-driven trading strategies (short-selling small-cap stocks post-disclosure). However, the paper does not evaluate actual trading profitability, transaction costs, or whether the effect is already priced in. The sample size is small, and the 7-day window is short. The findings are more relevant as a risk signal for portfolio managers than as a directly implementable trading strategy.

The methodology is straightforward: scraping SEC EDGAR for Item 1.05 filings, retrieving stock prices via Yahoo Finance API, computing percentage returns over a fixed window, and running standard t-tests. All tools are publicly available Python libraries. No complex modeling, optimization, or ML training is required. The main effort is in data collection and cleaning.

All data sources are publicly accessible (SEC EDGAR database, Yahoo Finance API via yfinance). Python libraries (sec-api, yfinance) are specified with URLs. The methodology uses standard statistical tests (t-tests) with clearly defined hypotheses. However, no code repository is provided, and the exact filtering criteria for data cleaning are described only in prose. The small sample size (54 events) and specific date cutoff (Nov 12, 2025) mean results may not be exactly reproducible over time as new filings accumulate.