驯服期权因子动物园：高维分析
Taming the Option Factor Zoo: A High-Dimensional Analysis
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中文总结 AI 辅助
本研究通过高维分析发现，期权隐含因子虽大部分被股票因子覆盖，但少数跳跃尾部、峰度及隐含波动率凸性因子具有定价相关性，表明期权仅补充少量定价维度而非构成新因子动物园。
中文摘要 AI 辅助
期权隐含因子在很大程度上（但并非完全）由股票因子动物园所覆盖。我们构建了2004年至2023年间美国可交易股票的137个期权隐含特征，筛选出20个代表性的多空因子，并使用Feng、Giglio和Xiu（2020）的双重选择LASSO方法，将每个因子与160个股票因子进行检验。在样本内，股票因子解释了期权因子约91%的方差，且加入期权因子并未显著提高最大夏普比率。然而，单独来看，20个期权因子中有8个（主要是跳跃尾部、峰度和隐含波动率凸性的度量）在控制股票因子动物园后具有非零的SDF载荷，其中4个在Bonferroni校正后仍然显著。因此，期权增加了少数几个与定价相关的维度，而非一个新的因子动物园。
英文摘要
Option-implied factors are largely, but not entirely, spanned by the equity factor zoo. We construct 137 option-implied characteristics for optionable U.S. stocks from 2004 to 2023, screen them to 20 representative long-short factors, and test each against 160 equity factors with the double-selection LASSO of Feng, Giglio, and Xiu (2020). In-sample, the equity factors account for about 91% of the option factors' variance, and adding the option factors does not significantly raise the maximum Sharpe ratio. Individually, however, 8 of the 20 option factors, mainly measures of jump tails, kurtosis, and implied-volatility convexity, have non-zero SDF loadings after controlling for the equity zoo, and 4 remain significant after a Bonferroni correction. Options thus add a few pricing-relevant dimensions rather than a new factor zoo.
