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Durham University

Department of Mathematical Sciences

Academic Staff

Publication details for Tahani Coolen-Maturi

Chen, J., Coolen, F.P.A. & Coolen-Maturi, T. (2019). On nonparametric predictive inference for asset and European option trading in the binomial tree model. Journal of the Operational Research Society 70(10): 1678-1691.

Author(s) from Durham

Abstract

This paper introduces a novel method for asset and option trading in a binomial scenario.
This method uses nonparametric predictive inference (NPI), a statistical methodology within im-
precise probability theory. Instead of inducing a single probability distribution from the existing
observations, the imprecise method used here induces a set of probability distributions. Based
on the induced imprecise probability, one could form a set of conservative trading strategies for
assets and options. By integrating NPI imprecise probability and expectation with the classical
nancial binomial tree model, two rational decision routes for asset trading and for European
option trading are suggested. The performances of these trading routes are investigated by com-
puter simulations. The simulation results indicate that the NPI based trading routes presented
in this paper have good predictive properties.