Polytopes associated with lattices of subsets and maximising expectation of random variables

The present paper originated from a problem in Financial Mathematics concerned with calculating the value of a European call option based on multiple assets each following the binomial model. The model led to an interesting family of polytopes $P(b)$ associated with the power-set $\mathcal{L} = \wp\{1,\dots,m\}$ and parameterized by $b \in \mathbb{R}^m$, each of which is a collection of probability density function on $\mathcal{L}$. For each non-empty $P(b)$ there results a family of probability measures on $\mathcal{L}^n$ and, given a function $F \colon \mathcal{L}^n \to \mathbb{R}$, our goal is to find among these probability measures one which maximises (resp. minimises) the expectation of $F$. In this paper we identify a family of such functions $F$, all of whose expectations are maximised (resp. minimised under some conditions) by the same {\em product} probability measure defined by a distinguished vertex of $P(b)$ called the supervertex (resp. the subvertex). The pay-offs of European call options belong to this family of functions.