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This study evaluates the practical usefulness of continuous-time arbitragestrategies designed to exploit serial correlation in fractional financialmarkets. Specifically, we revisit the strategies of \cite{Shiryaev1998} and\cite{Salopek1998} and transfer them to a real-world setting by distretizingtheir dynamics and introducing transaction costs. In Monte Carlo simulationswith various market and trading parameter settings, we show that both arehighly promising with respect to terminal portfolio values and lossprobabilities. These features and complementary sparsity make them valuableadditions to the toolkit of quantitative investors.

Discretization of continuous-time arbitrage strategies in financial markets with fractional Brownian motion