9 citations · 11 across the 3 of their papers we have counts for
3 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…
physics.soc-ph2020★ 1 cited
On the relation between active population and infection rate of COVID-19
Takashi Shimada, Yoshiyuki Suimon, Kiyoshi Izumi
The relation between the number of passengers in the main stations and the infection rate of COVID19 in Tokyo is empirically studied. Our analysis based on conventional compartment…
cs.LG2019★ 9 cited
Deep Recurrent Factor Model: Interpretable Non-Linear and Time-Varying Multi-Factor Model
Kei Nakagawa, Tomoki Ito, Masaya Abe +1
A linear multi-factor model is one of the most important tools in equity portfolio management. The linear multi-factor models are widely used because they can be easily interpreted…