23 citations · 47 across the 9 of their papers we have counts for
9 papers
Machine Learning for the Production of Official Statistics: Density Ratio Estimation using Biased Transaction Data for Japanese labor statistics
Yuya Takada, Kiyoshi Izumi
National statistical institutes are beginning to use non-traditional data sources to produce official statistics. These sources, originally collected for non-statistical purposes,…
SSAAM: Sentiment Signal-based Asset Allocation Method with Causality Information
Rei Taguchi, Hiroki Sakaji, Kiyoshi Izumi
This study demonstrates whether financial text is useful for tactical asset allocation using stocks by using natural language processing to create polarity indexes in financial new…
SETN: Stock Embedding Enhanced with Textual and Network Information
Takehiro Takayanagi, Hiroki Sakaji, Kiyoshi Izumi
Stock embedding is a method for vector representation of stocks. There is a growing demand for vector representations of stock, i.e., stock embedding, in wealth management sectors,…
Bilateral Trade Flow Prediction by Gravity-informed Graph Auto-encoder
Naoto Minakawa, Kiyoshi Izumi, Hiroki Sakaji
The gravity models has been studied to analyze interaction between two objects such as trade amount between a pair of countries, human migration between a pair of countries and tra…
Discovery of Rare Causal Knowledge from Financial Statement Summaries
Hiroki Sakaji, Jason Bennett, Risa Murono +2
What would happen if temperatures were subdued and result in a cool summer? One can easily imagine that air conditioner, ice cream or beer sales would be suppressed as a result of…
PAMS: Platform for Artificial Market Simulations
Masanori Hirano, Ryosuke Takata, Kiyoshi Izumi
This paper presents a new artificial market simulation platform, PAMS: Platform for Artificial Market Simulations. PAMS is developed as a Python-based simulator that is easily inte…
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…
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…
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…