An Empirical Implementation of the Ross Recovery Theorem as a Prediction Device
An Empirical Implementation of the Ross Recovery Theorem as a Prediction Device
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罗斯恢复定理作为预测装置的实证实现
DOI：
10.1093/jjfinec/nbz002
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发表时间：
2019
影响因子：
2.5
通讯作者：
Markus Ludwig
中科院分区：
文献类型：
--
作者：
F. Audrino;Robert Huitema;Markus Ludwig
基于Ludwig(2015)从期权价格的快照构造稳健状态价格密度面的方法，我们基于Ross(2015)的恢复定理发展了一种非参数估计策略。然后，我们使用S指数的期权，调查复苏是否产生了超出风险中性密度所能收集到的预测性信息。在2000年至2012年的13年 期间，我们发现基于恢复时刻的市场择时策略的表现优于基于风险中性时刻的市场择时策略。
Building on the method of Ludwig (2015) to construct robust state price density surfaces from snapshots of option prices, we develop a nonparametric estimation strategy based on the recovery theorem of Ross (2015). Using options on the S&P 500, we then investigate whether or not recovery yields predictive information beyond what can be gleaned from risk-neutral densities. Over the 13 year period from 2000 to 2012, we find that market timing strategies based on recovered moments outperform those based on risk-neutral moments.