K. Izumi

发表

Analysis of Exchange Rate Scenarios Using an Artificial Market Approach

Kiyoshi Izumi, Kazuhiro Ueda, K. Izumi, 1999, IC-AI.

Analysis of Dealers' Processing Financial News Based on an Artificial Market Approach

K. Izumi, 1999 .

Emergent phenomena in a foreign exchange market (poster): analysis based on an artificial market approach

K. Izumi, K. Ueda, 1998 .

Design of Financial Market Regulations against Large Price Fluctuations Using by Artificial Market Simulations

S. Yoshimura, K. Izumi, T. Mizuta, 2013 .

Roadmap for Multiagent Social Simulation on HPC

Hiromitsu Hattori, Kiyoshi Izumi, Nobuyasu Ito, 2015, 2015 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT).

A System for Classifying Proposals and Estimating Start Pages Stated in Notice of Annual Meeting of Shareholders

K. Izumi, Kaito Takano, Hiroyuki Sakai, 2018 .

Construction of Macroeconomic Uncertainty Indices for Financial Market Analysis Using a Supervised Topic Model

T. Shimada, K. Izumi, Hiroki Sakaji, 2020 .

How expert dealers make profits and reduce the risk of loss in a foreign exchange market

K. Izumi, K. Ueda, Yu Uchida, 2004 .

Investigation of the Effect of Group Dynamics for Solving Social Dilemmas

K. Izumi, T. Yamashita, K. Kurumatani, 2004 .

Emergent Phenomena in a Foreign Exchange Market : Analysis based on an Artificial Market Approach

K. Izumi, K. Ueda, 1998 .

mhirano at the FinSBD Task: Pointwise Prediction Based on Multi-layer Perceptron for Sentence Boundary Detection

K. Izumi, Hiroki Sakaji, Masanori HIRANO, 2019 .

Can Forward Guidance Influence Market Expectations? - Text Mining Approach

K. Izumi, Shintaro Suda, Ryo Ito, 2017 .

Economic Causal-Chain Search and Economic Indicator Prediction using Textual Data

K. Izumi, H. Sano, Hiroki Sakaji, 2021, FNP.

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

K. Izumi, Hiroki Sakaji, Masanori Hirano, 2022, 2023 14th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI).

Economic News Impact Analysis Using Causal-Chain Search from Textual Data

K. Izumi, Hiroki Sakaji, Shintaro Suda, 2020 .

Implementation of Actual Data for Artificial Market Simulation

K. Izumi, Hiroki Sakaji, Masanori Hirano, 2022, AAMAS.

Impact on Financial Markets of Dark Pools , Large Investor , and HFT

T. Shimada, K. Izumi, Hiroki Sakaji, 2018 .

Impact Analysis of Financial Regulation on Multi-Asset Markets Using Artificial Market Simulations

T. Shimada, K. Izumi, Hiroki Sakaji, 2020, Journal of Risk and Financial Management.

Impact Assessments of the CAR Regulation using Artificial Markets

T. Shimada, K. Izumi, Hiroki Sakaji, 2018 .

Market Trend Analysis Using Polarity Index Generated from Analyst Reports

K. Izumi, Hiroki Sakaji, Masanori Hirano, 2021, 2021 IEEE International Conference on Big Data (Big Data).

Effect of Mutual Choice Metanorm in Group Dynamics for Solving Social Dilemmas

K. Izumi, T. Yamashita, K. Kurumatani, 2005 .

Constructing and analyzing domain-specific language model for financial text mining

K. Izumi, Hiroki Sakaji, Masanori Hirano, 2023, Inf. Process. Manag..

Analysis of Demand Response Scenarios by Industrial Consumers Using Artificial Electric Power Market Simulations

K. Izumi, Masanori Hirano, Ryo Wakasugi, 2022, 2022 12th International Congress on Advanced Applied Informatics (IIAI-AAI).

Development of an artificial market model based on a field study

Kiyoshi Izumi, Kazuhiro Ueda, Shigeo Nakamura, 2005, Inf. Sci..

Using an Artificial Market Approach to Analyze Exchange Rate Scenarios

Kiyoshi Izumi, Kazuhiro Ueda, K. Izumi, 2002 .

Latent Segmentation of Stock Trading Strategies Using Multi-Modal Imitation Learning

Atsuo Kato, Kiyoshi Izumi, Hiroki Sakaji, 2020, Journal of Risk and Financial Management.

SETN: Stock Embedding Enhanced with Textual and Network Information

K. Izumi, Hiroki Sakaji, Takehiro Takayanagi, 2022, 2022 IEEE International Conference on Big Data (Big Data).

An Investigation into the Use of Group Dynamics for Solving Social Dilemmas

Koichi Kurumatani, Kiyoshi Izumi, Tomohisa Yamashita, 2004, MABS.

Japanese Interest Rate Forecast Considering the Linkage of Global Markets Using Machine Learning Methods

T. Shimada, K. Izumi, Hiroki Sakaji, 2020, International Journal of Smart Computing and Artificial Intelligence.

Contextual Sentiment Neural Network for Document Sentiment Analysis

Tomoki Ito, Kota Tsubouchi, Tatsuo Yamashita, 2020, Data Science and Engineering.

Forecasting Stock Price Trends by Analyzing Economic Reports With Analyst Profiles

K. Izumi, Hiroki Sakaji, Masahiro Suzuki, 2022, Frontiers in Artificial Intelligence.

Forecasting Net Income Estimate and Stock Price Using Text Mining from Economic Reports

Hiroki Sakaji, Kiyoshi Izumi, Hiroyasu Matsushima, 2020, Inf..

GINN: gradient interpretable neural networks for visualizing financial texts

Kiyoshi Izumi, Tomoki Ito, Hiroki Sakaji, 2018, International Journal of Data Science and Analytics.

Text-Visualizing Neural Network Model: Understanding Online Financial Textual Data

Kiyoshi Izumi, Tomoki Ito, Hiroki Sakaji, 2018, PAKDD.

Discovery of rare causal knowledge from financial statement summaries

Hiroyuki Sakai, Kiyoshi Izumi, Hiroki Sakaji, 2017, 2017 IEEE Symposium Series on Computational Intelligence (SSCI).

Inferring Long-term User Properties Based on Users' Location History

Kôiti Hasida, Naoaki Okazaki, Yoshiyuki Nakamura, 2007, IJCAI.

Affecting market efficiency by increasing speed of order matching systems on financial exchanges - investigation using agent based model

Kiyoshi Izumi, Takanobu Mizuta, Satoshi Hayakawa, 2016, 2016 IEEE Symposium Series on Computational Intelligence (SSCI).

Autoencoder-Based Three-Factor Model for the Yield Curve of Japanese Government Bonds and a Trading Strategy

K. Izumi, Hiroki Sakaji, Hiroyasu Matsushima, 2020, Journal of Risk and Financial Management.

An Artificial Market Model of a Foreign Exchange Market

Kiyoshi Izumi, K. Izumi, 2001 .

An Artificial Market Analysis of Exchange Rate Dynamics

Kiyoshi Izumi, Takashi Okatsu, K. Izumi, 1996, Evolutionary Programming.

Lexicon Creation for Financial Sentiment Analysis Using Network Embedding

Hiroki Sakaji, Ryo Ito, Shintaro Suda, 2017 .

Short-term Stock Price Prediction by Analysis of Order Pattern Images

Hiroki Sakaji, Kiyoshi Izumi, Hiroyasu Matsushima, 2019, 2019 IEEE Conference on Computational Intelligence for Financial Engineering & Economics (CIFEr).

Phase transition in a foreign exchange market-analysis based on an artificial market approach

Kiyoshi Izumi, Kazuhiro Ueda, K. Izumi, 2001, IEEE Trans. Evol. Comput..

Encoding of high-frequency order information and prediction of short-term stock price by deep learning

Hiroki Sakaji, Kiyoshi Izumi, Hiroyasu Matsushima, 2019, Machine Learning and AI in Finance.

Development of an Evaluation Method for Artificial Market Settings Considering a Realistic Pricing Mechanism

Isao Yagi, Kiyoshi Izumi, Takanobu Mizuta, 2012 .

Development of sentiment indicators using both unlabeled and labeled posts

Kiyoshi Izumi, Tomoki Ito, Hiroki Sakaji, 2017, 2017 IEEE Symposium Series on Computational Intelligence (SSCI).

Trading Tests of Long-Term Market Forecast by Text Mining

Tohgoroh Matsui, Kiyoshi Izumi, Takashi Goto, 2010, 2010 IEEE International Conference on Data Mining Workshops.

Atsuo Kato, Kiyoshi Izumi, Hiroki Sakaji, 2019, Inf..

Concept and Practice of Artificial Market Data Mining Platform

K. Izumi, Hiroki Sakaji, Masanori Hirano, 2022, 2022 IEEE Symposium on Computational Intelligence for Financial Engineering and Economics (CIFEr).

Deep Reinforcement Learning in Agent Based Financial Market Simulation

Atsuo Kato, Kiyoshi Izumi, Hiroki Sakaji, 2020, Journal of Risk and Financial Management.

Transfer Entropy Analysis of Information Flow in a Stock Market

Kiyoshi Izumi, Fujio Toriumi, F. Toriumi, 2017 .

Price variation limits and financial market bubbles: Artificial market simulations with agents' learning process

Shinobu Yoshimura, Kiyoshi Izumi, Takanobu Mizuta, 2013, 2013 IEEE Conference on Computational Intelligence for Financial Engineering & Economics (CIFEr).

A Study on the Effectiveness of Short-selling Regulation using Artificial Markets

Isao Yagi, Kiyoshi Izumi, Takanobu Mizuta, 2010 .

A Study on the Effectiveness of Short-Selling Regulation in View of Regulation Period Using Artificial Markets

Isao Yagi, Kiyoshi Izumi, Takanobu Mizuta, 2010, 2010 IEEE/ACIS 9th International Conference on Computer and Information Science.

A Study on the Market Impact of Short-Selling Regulation Using Artificial Markets

Isao Yagi, Kiyoshi Izumi, Takanobu Mizuta, 2009, PRIMA Workshops.

Financial Text Data Analytics Framework for Business Confidence Indices and Inter-Industry Relations

T. Shimada, K. Izumi, K. Sunakawa, 2019 .

Contextual Sentiment Neural Network for Document Sentiment Analysis

K. Izumi, Hiroki Sakaji, K. Tsubouchi, 2020, Data Science and Engineering.

Word-Level Contextual Sentiment Analysis with Interpretability

Tomoki Ito, Hiroki Sakaji, Kota Tsubouchi, 2020, AAAI.

CSNN: Contextual Sentiment Neural Network

Tomoki Ito, Kota Tsubouchi, Hiroki Sakaji, 2019, 2019 IEEE International Conference on Data Mining (ICDM).

Extraction of Focused Topic and Sentiment of Financial Market by using Supervised Topic Model for Price Movement Prediction

Hiroki Sakaji, Kiyoshi Izumi, Hiroyasu Matsushima, 2019, 2019 IEEE Conference on Computational Intelligence for Financial Engineering & Economics (CIFEr).

Analysis of the Macroeconomic Uncertainty Based on the News-based Textual Data with Financial Market

Hiroki Sakaji, Kiyoshi Izumi, Hiroyasu Matsushima, 2019, 2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI).

Measuring the Macroeconomic Uncertainty Based on the News Text by Supervised LDA for Investor’s Decision Making

T. Shimada, K. Izumi, Hiroki Sakaji, 2019 .

Neural-network-based parameter tuning for multi-agent simulation using deep reinforcement learning

K. Izumi, Masanori Hirano, 2023, World Wide Web.

Effectiveness of Uncertainty Consideration in Neural-Network-Based Financial Forecasting

Hiroki Sakaji, Kiyoshi Izumi, Iwao Maeda, 2019, 2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI).

Platform design for large-scale artificial market simulation and preliminary evaluation on the K computer

K. Izumi, Tomio Kamada, T. Torii, 2017, Artificial Life and Robotics.

Shock transfer by arbitrage trading: analysis using multi-asset artificial market

Kiyoshi Izumi, Kenta Yamada, Takuma Torii, 2015, Evolutionary and Institutional Economics Review.

Effects of Price Regulations and Dark Pools on Financial Market Stability: An Investigation by Multiagent Simulations

Isao Yagi, Shinobu Yoshimura, Kiyoshi Izumi, 2016, Intell. Syst. Account. Finance Manag..

On the relation between active population and infection rate of COVID-19

T. Shimada, K. Izumi, Yoshiyuki Suimon, 2020, 2008.07791.

Bilateral Trade Flow Prediction by Gravity-informed Graph Auto-encoder

K. Izumi, Hiroki Sakaji, N. Minakawa, 2022, 2022 IEEE International Conference on Big Data (Big Data).

Economic Causal-Chain Search using Text Mining Technology

Hiroki Sakaji, Kiyoshi Izumi, K. Izumi, 2019, IJCAI.

Estimation of cross-lingual news similarities using text-mining methods

Kiyoshi Izumi, Hiroki Sakaji, Kota Tsubouchi, 2018 .

Retrieving of Data Similarity using Metadata on a Data Analysis Competition Platform

Teruaki Hayashi, K. Izumi, Hiroki Sakaji, 2021, 2021 IEEE International Conference on Big Data (Big Data).

Verification of Data Similarity using Metadata on a Data Exchange Platform

Y. Ohsawa, Teruaki Hayashi, K. Izumi, 2020, 2020 IEEE International Conference on Big Data (Big Data).

Efficient Parameter Tuning for Multi-agent Simulation Using Deep Reinforcement Learning

K. Izumi, Masanori Hirano, 2022, 2022 13th International Congress on Advanced Applied Informatics Winter (IIAI-AAI-Winter).

Parameter Tuning Method for Multi-agent Simulation using Reinforcement Learning

K. Izumi, Masanori Hirano, 2022, 2022 9th International Conference on Behavioural and Social Computing (BESC).

Shock transfer by arbitrage trading: analysis using multi-asset artificial market

K. Izumi, T. Torii, Kenta Yamada, 2015, Evolutionary and Institutional Economics Review.

Investigation of Price Variation Limits, Short Selling Regulation, and Uptick Rules and Their Optimal Design by Artificial Market Simulations

S. Yoshimura, K. Izumi, T. Mizuta, 2015 .

How Does High Frequency Risk Hedge Activity Have an Affect on Underlying Market?: Analysis by Artificial Market Model

Shinobu Yoshimura, Saki Kawakubo, Kiyoshi Izumi, 2014, J. Adv. Comput. Intell. Intell. Informatics.

Analysis of an Option Market Dynamics Based on a Heterogeneous Agent Model

Shinobu Yoshimura, Saki Kawakubo, Kiyoshi Izumi, 2014, Intell. Syst. Account. Finance Manag..

Regulations' effectiveness for market turbulence by large erroneous orders using multi agent simulation

Isao Yagi, Shinobu Yoshimura, Kiyoshi Izumi, 2014, 2014 IEEE Conference on Computational Intelligence for Financial Engineering & Economics (CIFEr).

Do dark pools stabilize markets and reduce market impacts? Investigations using multi-agent simulations

Shinobu Yoshimura, Kiyoshi Izumi, Wataru Matsumoto, 2014, 2014 IEEE Conference on Computational Intelligence for Financial Engineering & Economics (CIFEr).

Investigating the Impact of Trading Frequencies of Market Makers: A Multi-Agent Simulation Approach

Shinobu Yoshimura, Kiyoshi Izumi, Takanobu Mizuta, 2013 .

Analysis of the Interaction between Option Market and Its Underlying Market by Coupled Artificial Markets

Saki Kawakubo, Kiyoshi Izumi, K. Izumi, 2016 .

Impact of Position-Based Market Makers to Shares of Markets Volumes -- an Artificial Market Approach

Kiyoshi Izumi, Satoshi Hayakawa, Takanobu Mizuta, 2015 .

Disagreement Among FOMC Members and Asset Prices

K. Izumi, Shintaro Suda, Ryo Ito, 2018 .

A Self-Impact Analysis by Artificial Market Simulation

Kiyoshi Izumi, Yutaka Matsuo, Hiroki Matsui, 2007, 2007 IEEE Symposium on Computational Intelligence and Data Mining.

Implementation Tests of Financial Market Analysis by Text Mining

Tohgoroh Matsui, Kiyoshi Izumi, Takashi Goto, 2011 .

Constructing Equity Investment Strategies Using Analyst Reports and Regime Switching Models

K. Izumi, Hiroki Sakaji, Rei Taguchi, 2022, Frontiers in Artificial Intelligence.

Learning Uncertainty in Market Trend Forecast Using Bayesian Neural Networks

Atsuo Kato, Hiroki Sakaji, Iwao Maeda, 2019 .

Integrated Information Support System for Global House, EXPO 2005 AICHI JAPAN based on CONSORTS Architecture

Noriaki Izumi, Koichi Kurumatani, Kiyoshi Izumi, 2006 .

Deep Recurrent Factor Model: Interpretable Non-Linear and Time-Varying Multi-Factor Model pdf

Kiyoshi Izumi, Tomoki Ito, Kei Nakagawa, 2019, ArXiv.

Change Detection of Orders in Stock Markets using a Gaussian Mixture Model

Kiyoshi Izumi, Ryo Takahashi, Fujio Toriumi, 2014, Intell. Syst. Account. Finance Manag..

Stock Price Analysis Using Combination of Analyst Reports and Several Documents

Hiroki Sakaji, Kiyoshi Izumi, Yasushi Ishikawa, 2019, 2019 International Conference on Data Mining Workshops (ICDMW).