AI 中文总结
该研究基于2015-2026年美国股票期权面板数据，发现期权隐含可预测性具阶段依赖性，经典微笑-收益关系减弱，提升树模型仅在AI与大盘股阶段收益预测优于线性模型，崩盘预测AUC随阶段变化。
AI 中文摘要
我们使用包含10026种标的资产、共1236万条美国股票公司-日观测值的2015-2026年统一面板数据，重新估计经典的期权隐含可预测性证据。我们将样本分为三个阶段：后危机后期低波动阶段（2015-2019）、高波动过渡阶段（2020-2022）、AI与大盘股集中阶段（2023-2026）。Xing等人（2010）的“微笑-收益”关系持续减弱：下月单变量微笑系数从2015-2019年的-0.023（t=-5.5）降至2023-2026年的不显著值-0.006（t=-1.5），且在三个月期限转为正（+0.016，t=+2.1）。在包含全部六个经典信号的联合模型中，微笑在全阶段均不显著，且在最新阶段再次改变符号。相比之下，Cremers-Weinbaum隐含波动率（IV）利差和Bakshi等人（2003）风格的风险中性偏度测度在各阶段及模型中均保持显著。使用IV曲面、交易活动、希腊字母（Greeks）和流动性特征的提升树基准模型，仅在AI与大盘股集中阶段的下月收益预测中优于线性模型，其样本外R²（R²_OOS）为+1.29%，而线性模型仅为+0.07%。置换重要性识别出不同阶段的领先预测因子，且无经典手工工程信号进入前五名。在公司层面五天崩盘分类任务中，AUC在平静市场最高（0.706，XGBoost），在高波动过渡阶段最低（0.561）。总体而言，期权隐含可预测性是真实存在的，但具有阶段依赖性，2023年后的AI与大盘股时期与建立经典结果的新冠前环境存在显著差异。
英文摘要
We re-estimate canonical option-implied predictability evidence using a unified 2015--2026 panel of 12.36 million U.S. equity firm-day observations across 10,026 underlyings. We split the sample into three regimes: late-post-crisis low volatility (2015--2019), high-volatility transition (2020--2022), and AI/mega-cap concentration (2023--2026). The Xing et al. (2010) smirk--return relationship weakens steadily: the next-month univariate smirk coefficient falls from $-0.023$ $(t=-5.5)$ in 2015--2019 to an insignificant $-0.006$ $(t=-1.5)$ in 2023--2026, and turns positive at the three-month horizon $(+0.016,\ t=+2.1)$. In joint specifications with all six canonical signals, the smirk is insignificant throughout and again changes sign in the latest regime. By contrast, the Cremers--Weinbaum IV spread and a Bakshi et al. (2003)-style risk-neutral skewness measure remain significant across regimes and specifications. A boosted-tree benchmark using IV-surface, trading-activity, Greeks, and liquidity features outperforms linear models for next-month return prediction only in the AI/mega-cap regime, with $R^2_{\mathrm{OOS}}=+1.29%$ versus $+0.07%$. Permutation importance identifies different leading predictors by regime, and no canonical hand-engineered signal enters the top five. For firm-level five-day crash classification, AUC is highest in calm markets $(0.706,\ \text{XGBoost})$ and lowest during the high-volatility transition $(0.561)$. Overall, option-implied predictability is real but regime-dependent, and the post-2023 AI/mega-cap period differs sharply from the pre-COVID setting in which the canonical results were established.
