most citedPolicy Gradient Stock GAN for Realistic Discrete Order Data Generation in Financial Markets

1 citations · 1 across the 2 of their papers we have counts for

collaborators

2 papers

cs.LG2022★ 1 cited

Policy Gradient Stock GAN for Realistic Discrete Order Data Generation in Financial Markets

Masanori Hirano, Hiroki Sakaji, Kiyoshi Izumi

This study proposes a new generative adversarial network (GAN) for generating realistic orders in financial markets. In some previous works, GANs for financial markets generated fa…

cs.CY2020

Data Combination for Problem-solving: A Case of an Open Data Exchange Platform

Teruaki Hayashi, Hiroki Sakaji, Hiroyasu Matsushima +3

In recent years, rather than enclosing data within a single organization, exchanging and combining data from different domains has become an emerging practice. Many studies have di…