TModel-free portfolio theory: a rough path approach
Abstract
Classical approaches to optimal portfolio selection problems are based
on probabilistic models for the asset returns or prices. However, by
now it is well observed that the performance of optimal portfolios are
highly sensitive to model misspecifications. To account for various
type of model risk, robust and model-free approaches have gained more
and more importance in portfolio theory. Based on a rough path
foundation, we develop a model-free approach to stochastic portfolio
theory and Cover's universal portfolio. The use of rough path theory
allows treating significantly more general portfolios in a model-free
setting, compared to previous model-free approaches. Without the
assumption of any underlying probabilistic model, we present pathwise
Master formulae analogously to the classical ones in stochastic
portfolio theory, describing the growth of wealth processes generated
by pathwise portfolios relative to the wealth process of the market
portfolio, and we show that the appropriately scaled asymptotic growth
rate of Cover's universal portfolio is equal to the one of the best
retrospectively chosen portfolio. The talk is based on joint work with
Andrew Allan, Christa Cuchiero and Chong Liu.