Exogenous shocks generate heterogeneous behavioral responses across firms, yet event studies typically report only sector-level averages. This paper develops a multi-method approach combining causal identification (difference-in-differences with cluster-robust inference), unsupervised behavioral discovery (K-means trajectory clustering, Gaussian hidden Markov models), and cross-sectional resilience prediction (logistic regression with bootstrap inference) to decompose firm-level response heterogeneity from noisy market signals. We demonstrate the approach on 246 Chinese A-share IT firms (216 with complete data for all analyses) during the COVID-19 shock (January 2020), using 252 non-IT CSI 300 firms as controls. The return decline was market-wide, not IT-specific (DID p = 0.59); the IT-specific effect was elevated volatility (DID \b{eta} = 0.043, cluster-robust p < 0.001), with the effect surviving Benjamini-Hochberg correction across alternative specifications. Unsupervised clustering produced three categories of trajectories: fast recovery (36 companies, +29.7%), resilient/moderate (67 companies), and persistent drag (113 companies, -6.9%). Prior-to-crisis financial fundamentals did not predict resilience well (AUC = 0.64, 95% CI: 0.57-0.71), in line with efficient markets' incorporation of public information into stock prices. The combination of causal analysis, unsupervised learning, and prediction represents a reproducible framework which can be applied to crises in other market periods.

翻译：外生冲击会在企业间引发异质性行为响应，然而事件研究通常仅报告行业层面的平均结果。本文开发了一种多方法结合的研究路径，整合因果识别（双重差分法结合聚类稳健推断）、无监督行为发现（K-means轨迹聚类、高斯隐马尔可夫模型）以及横截面韧性预测（基于自助法推断的Logistic回归），以从噪声市场信号中分解企业层面的响应异质性。我们以2020年1月COVID-19冲击期间的246家中国A股IT企业（其中216家具有完整数据可进行所有分析）为样本，并以252家非IT沪深300企业作为对照组验证该方法。收益率下降是市场整体性的，而非IT行业特有（双重差分法p值=0.59）；IT行业的特有影响表现为波动率上升（双重差分法β系数=0.043，聚类稳健p值<0.001），且该效应在替代规范下经Benjamini-Hochberg校正后依然稳健。无监督聚类产生了三类轨迹：快速恢复型（36家企业，+29.7%）、韧性/中等型（67家企业）及持续拖累型（113家企业，-6.9%）。危机前的财务基本面未能良好预测韧性（AUC=0.64，95%置信区间：0.57-0.71），这与有效市场假说中“公开信息已融入股价”的预期相符。因果分析、无监督学习与预测的结合构成了一个可复现的分析框架，适用于其他市场时期的危机研究。