A Family of Maximum Entropy Densities Matching Call Option Prices

Probability Distributions of Assets Inferred from Option Prices via the Principle of Maximum Entropy

This article revisits the maximum entropy algorithm in the context of recovering the probability distribution of an asset from the prices of finitely many associated European call options via partially finite convex programming. We are able to provide an effective characterization of the constraint qualification under which the problem reduces to optimizing an explicit function in finitely many...

Moment matching approximation of Asian basket option prices

In this paper we propose some moment matching pricing methods for European-style discrete arithmetic Asian basket options in a Black & Scholes framework. We generalize the approach of [5] and of [8] in several ways. We create a framework that allows for a whole class of conditioning random variables which are normally distributed. We moment match not only with a lognormal random variable but al...

Calculation of maximum entropy densities with application to income distribution

The maximum entropy approach is a ,exible and powerful tool for density approximation. This paper proposes a sequential updating method to calculate the maximum entropy density subject to known moment constraints. Instead of imposing the moment constraints simultaneously, the sequential updating method incorporates the moment constraints into the calculation from lower to higher moments and upd...

An Efficient Algorithm To Compute Maximum Entropy Densities

Partially Adaptive Estimation via the Maximum Entropy Densities∗

We propose a partially adaptive estimator based on information theoretic maximum entropy estimates of the error distribution. The maximum entropy (maxent) densities have simple yet flexible functional forms to nest most of the mathematical distributions. Unlike the nonparametric fully adaptive estimators, our parametric estimators do not involve choosing a bandwidth or trimming, and only requir...