Abstract
In this paper we consider the impact of transaction costs on the periodic portfolio revision. We offer a statistical model for simulation of daily returns which can explain the empirical behavior of equity returns. The model is based on ARMA–GARCH processes, principal component analysis, classical tempered stable distribution, and skewed \(t\) copula. The main contribution of this paper is the application of a new approach for modelling transaction costs using daily returns by estimating an optimal portfolio with an arbitrary length for the holding period. Moreover, we compare the portfolio selection problem solved with and without transaction costs by applying different risk and performance measures on simulated returns, taking into account their Sharpe ratio and stable tail-adjusted return ratio. The experimental analysis suggests that the incorporation of transaction costs into an optimal portfolio framework leads to remarkable reduction of the transaction costs and stabilization of the optimal portfolio strategy. However, ignoring transaction costs does not always result in a less efficient portfolio.
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