Among recent approaches for the adjustment of correlation matrices, the most efficient methods are currently based on SDP formulations of the calibration problem. In this paper, we have a closer look at the pros and cons of two particular approaches: a very flexible primal SDP approach which is recommended for low dimensional problems, and a less flexible dual SDP approach which has much better performance and can thus be used to solve high dimensional problems. Afterwards, we introduce an instance of the general calibration problem with additional structural constraints. These constraints stem from popular factor models in finance and allow for valuable insights into the structure of the financial market. We will show that these instances should not be cast as SDPs any more, but may be solved as standard non-linear programs.     «

Among recent approaches for the adjustment of correlation matrices, the most efficient methods are currently based on SDP formulations of the calibration problem. In this paper, we have a closer look at the pros and cons of two particular approaches: a very flexible primal SDP approach which is recommended for low dimensional problems, and a less flexible dual SDP approach which has much better performance and can thus be used to solve high dimensional problems. Afterwards, we introduce an insta...     »