In this paper we investigate trading with optimal mean reverting portfolios subject to cardinality constraints. First, we identify the parameters of the underlying VAR(1) model of asset prices and then the quantities of the corresponding Ornstein-Uhlenbeck (OU) process are estimated by pattern...

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...

In this paper, we study the problem of finding sparse, mean reverting portfolios in multivariate time series. This can be applied to developing profitable convergence trading strategies by identifying portfolios which can be traded advantageously when their prices differ from their identified...

The recent public adaptation of cryptocurrencies sparked a great interest in alternative uses of the blockchain technology. Private or permissioned blockchain-based systems are a promising technology, initiating novel applications in several important fields, such as financing, commerce, and...

We study the problem of finding sparse, mean reverting portfolios based on multivariate historical time series. After mapping the optimal portfolio selection problem into a generalized eigenvalue problem, we propose a new optimization approach based on the use of simulated annealing. This new...

Doctoral education is a wise societal investment with excellent pay-off in both the short- and long term. In Central- and South-East European countries numerous doctoral schools have the potential to become internationally recognized LEADERS in certain scientific areas. Public authorities pay...