4 citations · 6 across the 7 of their papers we have counts for
4 papers · 1 filter
Efficient differentiable quadratic programming layers: an ADMM approach
Andrew Butler, Roy Kwon
Recent advances in neural-network architecture allow for seamless integration of convex optimization problems as differentiable layers in an end-to-end trainable neural network. In…
Data-driven integration of norm-penalized mean-variance portfolios
Andrew Butler, Roy H. Kwon
Mean-variance optimization (MVO) is known to be sensitive to estimation error in its inputs. Norm penalization of MVO programs is a regularization technique that can mitigate the a…
Data-driven distributionally robust risk parity portfolio optimization
Giorgio Costa, Roy H. Kwon
We propose a distributionally robust formulation of the traditional risk parity portfolio optimization problem. Distributional robustness is introduced by targeting the discrete pr…
Integrating prediction in mean-variance portfolio optimization
Andrew Butler, Roy H. Kwon
Prediction models are traditionally optimized independently from their use in the asset allocation decision-making process. We address this shortcoming and present a framework for…