In this paper we propose a coordinate descent algorithm for solving high dimensional risk parity problems. We show that this algorithm converges and is very fast even with large covariance matrices (n500). Comparison with existing algorithms also shows that it is one of the most efficient...

This article develops the theory of risk budgeting portfolios, when we would like to impose weight constraints. It appears that the mathematical problem is more complex than the traditional risk budgeting problem. The formulation of the optimization program is particularly critical in order to...

In this article, we consider a new framework to understand risk-based portfolios (GMV, EW, ERC and MDP). This framework is similar to the constrained minimum variance model of Jurczenko et al. (2013), but with another definition of the diversification constraint. The corresponding optimization...

The mean-variance optimization (MVO) theory of Markowitz (1952) for portfolio selection is one of the most important methods used in quantitative finance. This portfolio allocation needs two input parameters, the vector of expected returns and the covariance matrix of asset returns. This process...

This paper studies trend filtering methods. These methods are widely used in momentum strategies, which correspond to an investment style based only on the history of past prices. For example, the CTA strategy used by hedge funds is one of the best-known momentum strategies. In this paper, we...

In this paper we propose a cyclical coordinate descent (CCD) algorithm for solving high dimensional risk parity problems. We show that this algorithm converges and is very fast even with large covariance matrices (n 500). Comparison with existing algorithms also shows that it is one of the most...

In this paper we propose a cyclical coordinate descent (CCD) algorithm for solving high dimensional risk parity problems. We show that this algorithm converges and is very fast even with large covariance matrices (n 500). Comparison with existing algorithms also shows that it is one of the most...