Robust Estimation of Superhedging Prices

Annals of Statistics, Forthcoming

52 Pages Posted: 30 Apr 2020

See all articles by Jan Obłój

Jan Obłój

University of Oxford - Mathematical Institute; University of Oxford - Oxford-Man Institute of Quantitative Finance; University of Oxford - Saint John's College

Johannes Wiesel

University of Oxford - Mathematical Institute; St. John's College

Date Written: April 6, 2020

Abstract

We consider statistical estimation of superhedging prices using historical stock returns in a frictionless market with d traded assets. We introduce a plugin estimator based on empirical measures and show it is consistent but lacks suitable robustness. To address this we propose novel estimators which use a larger set of martingale measures defined through a tradeoff between the radius of Wasserstein balls around the empirical measure and the allowed norm of martingale densities. We establish consistency and robustness of these estimators and argue that they offer a superior performance relative to the plugin estimator. We generalise the results by replacing the superhedging criterion with acceptance relative to a risk measure. We further extend our study, in part, to the case of markets with traded options, to a multiperiod setting and to settings with model uncertainty. We also study convergence rates of estimators and convergence of superhedging strategies.

Keywords: superhedging price, risk measures, statistical estimation, consistency, robustness, stock returns, Wasserstein metric, pricing-hedging duality, empirical measure

Suggested Citation

Obloj, Jan K. and Wiesel, Johannes, Robust Estimation of Superhedging Prices (April 6, 2020). Annals of Statistics, Forthcoming , Available at SSRN: https://ssrn.com/abstract=3569722

Jan K. Obloj

University of Oxford - Mathematical Institute ( email )

AWB, ROQ, Woodstock Rd
Oxford, OX2 6GG
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University of Oxford - Oxford-Man Institute of Quantitative Finance ( email )

Eagle House
Walton Well Road
Oxford, Oxfordshire OX2 6ED
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University of Oxford - Saint John's College ( email )

St Giles
Oxford, Oxon OX1 3JP
United Kingdom

Johannes Wiesel (Contact Author)

University of Oxford - Mathematical Institute ( email )

Andrew Wiles Building
Radcliffe Observatory Quarter (550)
Oxford, OX2 6GG
United Kingdom

St. John's College ( email )

St Giles
Oxford, Oxon OX1 3JP
United Kingdom

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