Simulating cointegrated time series

When one models dependence solely via correlations, portfolio allocation models can perform poorly. This motivates considering dependence measures other than correlation. Cointegration is one such measure that captures long-term dependence. In this paper we present a new method to simulate cointegrated sample paths using the vector auto-regressive-to-anything (VARTA) algorithm. Our approach relies on new properties of cointegrated time series of financial asset prices and allows for marginal distributions from the Johnson system. The method is illustrated on two data sets, one real and one artificial.