Improved Parameter Estimation and Simple Trading Algorithm for Sparse, Mean-Reverting Portfolios

Annales Univ. Sci. Budapest., Sect. Comp. 37 (2012) 121–144

24 Pages Posted: 31 Jul 2017

See all articles by Norbert Fogarasi

Norbert Fogarasi

Budapest University of Technology and Economics

János Levendovszky

Budapest University of Technology and Economics

Date Written: May 27, 2012

Abstract

We examine the problem of finding sparse, mean reverting portfolios based on multivariate historical time series. After mapping optimal portfolio selection into a generalized eigenvalue problem, two different heuristic algorithms are referenced for finding the solution in a subspace which satisfies the cardinality constraint. Having identified the optimal portfolio, we outline the known methods for finding the long-term mean and introduce a novel approach based on pattern matching. Furthermore, we present a simple convergence trading algorithm with a decision theoretic approach, which can be used to compare the economic viability of the different methods and test the effectiveness of our end-to-end process by extensive simulations on generated and historical real market data.

Keywords: Mean reversion, sparse estimation, convergence trading, parameter estimation, VAR(1) model, covariance selection, financial time series

JEL Classification: G11

Suggested Citation

Fogarasi, Norbert and Levendovszky, János, Improved Parameter Estimation and Simple Trading Algorithm for Sparse, Mean-Reverting Portfolios (May 27, 2012). Annales Univ. Sci. Budapest., Sect. Comp. 37 (2012) 121–144 . Available at SSRN: https://ssrn.com/abstract=3009796

Norbert Fogarasi (Contact Author)

Budapest University of Technology and Economics ( email )

Budafoki ut 8.
Budapest, 1111
Hungary

János Levendovszky

Budapest University of Technology and Economics ( email )

Budafoki ut 8.
Budapest, 1111
Hungary

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