Optimal trading strategies - a time series approach
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
Cite
@article{arxiv.1509.07953,
title = {Optimal trading strategies - a time series approach},
author = {Peter A. Bebbington and Reimer Kuehn},
journal= {arXiv preprint arXiv:1509.07953},
year = {2016}
}