In this work, we first investigate the characteristics of PSO for option pricing and propose improvements to PSO modeling, which reduces the number of PSO ...
For algorithm design, we have used nature inspired algorithm known as Particle swarm optimization (PSO) and for speed we have used state-of-the-art graphics ...
Heuristic approaches such as Particle swarm optimization (PSO) have been proposed for option pricing, which provide same or better results for simple options ...
In this work, we first investigate the characteristics of PSO for option pricing and propose improvements to PSO modeling, which reduces the number of PSO ...
A vanilla particle swarm optimizer (PSO) and cooperative swarm optimizer are implemented in Python and make use of the GPU.
In this article, the authors apply graphics processing unit (GPU) computation to an American option pricing problem via Monte Carlo (MC) simulations and ...
I used the particle swarm optimization (PSO) algorithm. Portfolio optimization works by forecasting the expected risk and return of each asset in the portfolio.
Missing: GPU. | Show results with:GPU.
Jul 4, 2021 · Particle swarm optimization (PSO) is an AI technique that can be used to find approximate solutions to extremely difficult or impossible numeric ...
Overview and Applications of Particle Swarm Optimization on GPGPU
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Particle Swarm Optimization is robust and effective method to solve optimization problems. Particle Swarm Optimization takes more time to find optimal ...
This paper proposes a Parallel Asynchronous PSO (PAPSO) framework based on thread pools utilizing multicore processors and adopts a cross-level approach to ...