  Portfolio optimisation is widely acknowledged for its significance in
investment decision-making. Yet, existing methodologies face several
limitations, among them converting optimal theoretical portfolios into real
investment is not always straightforward. Several classes of exogenous
(real-world) constraints have been proposed in literature with the intent of
reducing the gap between theory and practice, which have worked to an extent.
  In this paper, we propose an optimisation-based framework which attempts to
further reduce this gap. We have the explicit intention of producing portfolios
that can be immediately converted into financial holdings. Our proposed
framework is generic in the sense that it can be used in conjunction with any
portfolio selection model, and consists of splitting the portfolio selection
problem into two-stages. The main motivation behind this approach is in
enabling automated investing with minimal human intervention, and thus the
framework was built in such a way that real-world market features can be
incorporated with relative ease. Among the novel contributions of this paper,
this is the first work, to the best of our knowledge, to combine futures
contracts and equities in a single framework, and also the first to consider
borrowing costs in short positions.
  We present extensive computational results to illustrate the applicability of
our approach and to evaluate its overall quality. Among these experiments, we
observed that alternatives from literature are susceptible to numerical errors,
whereas our approach effectively mitigates this issue.
