The Maximum Entropy Distribution of an Asset Inferred from Option Prices
应用最大熵原理，从期权价格数据中推断标的资产的概率分布，该分布对未知信息保持中立，并可通过最小交叉熵原理融入先验知识。模拟表明，该方法能准确拟合已知密度。
This paper describes the application ofthe Principle of Maximum Entropy to the estimation of the distribution of an underlying asset from a set of option prices. The resulting distri? bution is least committal with respect to unknown or missing information and is, hence, the least prejudiced. The maximum entropy distribution is the only information about the asset that can be inferred from the price data alone. An extension to the Principle of Mini? mum Cross-Entropy allows the inclusion of prior knowledge of the asset distribution. We show that the maximum entropy distribution is able to accurately fit a known density, given simulated option prices at different strikes.