FlashFolio: A GPU-Accelerated Solver for Portfolio Optimization
This work addresses the computational bottleneck of large-scale portfolio optimization for quantitative finance practitioners, enabling faster and more robust solutions.
FlashFolio, a GPU-accelerated solver for portfolio optimization, achieves speedups of up to 12.9x for single-period and 48x for multi-period problems compared to MOSEK, while also showing stronger robustness on challenging instances.
We present FlashFolio, a GPU-accelerated solver for single-period and multi-period portfolio optimization with factor-based risk modeling, bid-offer spread costs, and nonlinear market impact. These models are widely used in portfolio construction and optimal execution, but become computationally challenging at large scale, especially in the multi-period setting. We benchmark FlashFolio against MOSEK on instances constructed from realistic market inputs. FlashFolio delivers consistent runtime improvements, achieving speedups of up to 12.9x in the single-period setting and 48x in the multi-period setting, while also exhibiting stronger robustness on challenging multi-period instances. Our results show that GPU-based optimization can help improve the practicality of large-scale portfolio optimization.