Improved Fr\'echet$-$Hoeffding bounds on $d$-copulas and applications in model-free finance

TL;DR

This paper develops improved bounds on the dependence structure of multivariate distributions, enabling more accurate model-free pricing of multi-asset options by incorporating partial dependence information.

Contribution

It introduces enhanced Fréchet-Hoeffding bounds for copulas considering additional dependence information, and extends integral representations to quasi-copulas for better expectation bounds.

Findings

Improved bounds tighten the estimates of dependence structures.

Additional information significantly narrows option price bounds.

Bounds are applicable in multi-asset financial models with partial dependence data.

Abstract

We derive upper and lower bounds on the expectation of $f(\mathbf{S})$ under dependence uncertainty, i.e. when the marginal distributions of the random vector $\mathbf{S}=(S_1,\dots,S_d)$ are known but their dependence structure is partially unknown. We solve the problem by providing improved \FH bounds on the copula of $\mathbf{S}$ that account for additional information. In particular, we derive bounds when the values of the copula are given on a compact subset of $[0,1]^d$, the value of a functional of the copula is prescribed or different types of information are available on the lower dimensional marginals of the copula. We then show that, in contrast to the two-dimensional case, the bounds are quasi-copulas but fail to be copulas if $d>2$. Thus, in order to translate the improved \FH bounds into bounds on the expectation of $f(\mathbf{S})$, we develop an alternative representation of multivariate integrals with respect to copulas that admits also quasi-copulas as integrators. By means of this representation, we provide an integral characterization of orthant orders on the set of quasi-copulas which relates the improved \FH bounds to bounds on the expectation of $f(\mathbf{S})$. Finally, we apply these results to compute model-free bounds on the prices of multi-asset options that take partial information on the dependence structure into account, such as correlations or market prices of other traded derivatives. The numerical results show that the additional information leads to a significant improvement of the option price bounds compared to the situation where only the marginal distributions are known.