Optimal Trading Strategies — A Time Series Approach

14 Pages Posted: 8 Dec 2016

See all articles by Peter Bebbington

Peter Bebbington

University College London, Department of Physics and Astronomy, Students

Reimer Kühn

King's College London

Date Written: March 28, 2016

Abstract

Motivated by recent advances in the spectral theory of auto-covariance matrices, we are led to revisit a reformulation of Markowitz’ mean-variance portfolio optimization approach in the time domain. In its simplest incarnation it applies to a single traded asset and allows to find an optimal trading strategy which — for a given return — is minimally exposed to market price fluctuations. The model is initially investigated for a range of synthetic price processes, taken to be either second order stationary, or to exhibit second order stationary increments. Attention is paid to consequences of estimating auto-covariance matrices from small finite samples, and auto-covariance matrix cleaning strategies to mitigate against these are investigated. Finally we apply our framework to real world data.

Keywords: Portfolio, Time Series, Optimisation

Suggested Citation

Bebbington, Peter and Kühn, Reimer, Optimal Trading Strategies — A Time Series Approach (March 28, 2016). Available at SSRN: https://ssrn.com/abstract=2881986 or http://dx.doi.org/10.2139/ssrn.2881986

Peter Bebbington (Contact Author)

University College London, Department of Physics and Astronomy, Students ( email )

Gower Street
London
United Kingdom

Reimer Kühn

King's College London ( email )

Strand
London, England WC2R 2LS
United Kingdom

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
81
Abstract Views
643
Rank
590,585
PlumX Metrics