FlashFolio: A GPU-Accelerated Solver for Portfolio Optimization
Yilun Jiang, Haihao Lu, Zedong Peng, Jinwen Yang

TL;DR
FlashFolio is a GPU-accelerated solver that significantly speeds up large-scale portfolio optimization, making complex multi-period models more practical.
Contribution
It introduces a GPU-based solver that outperforms traditional solvers like MOSEK in speed and robustness for portfolio optimization tasks.
Findings
Achieves up to 12.9x speedup in single-period optimization.
Achieves up to 48x speedup in multi-period optimization.
Demonstrates improved robustness on challenging instances.
Abstract
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.
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