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An Open-Source Implementation of the Critical-Line Algorithm for Portfolio Optimization

Author(s): David H. Bailey | Marcos López de Prado

Journal: Algorithms
ISSN 1999-4893

Volume: 6;
Issue: 1;
Start page: 169;
Date: 2013;
Original page

Keywords: portfolio selection | quadratic programming | portfolio optimization | constrained efficient frontier | turning point | Kuhn-Tucker conditions | risk aversion

Portfolio optimization is one of the problems most frequently encountered by financial practitioners. The main goal of this paper is to fill a gap in the literature by providing a well-documented, step-by-step open-source implementation of Critical Line Algorithm (CLA) in scientific language. The code is implemented as a Python class object, which allows it to be imported like any other Python module, and integrated seamlessly with pre-existing code. We discuss the logic behind CLA following the algorithm’s decision flow. In addition, we developed several utilities that support finding answers to recurrent practical problems. We believe this publication will offer a better alternative to financial practitioners, many of whom are currently relying on generic-purpose optimizers which often deliver suboptimal solutions. The source code discussed in this paper can be downloaded at the authors’ websites (see Appendix).
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