2025年
Ryuji Hashimoto, Kiyoshi Izumi, Interpretable Market Simulations via Optimal Transport: Power Law Decomposition and Implications for Market Design, 6th ACM International Conference on AI in Finance (ICAIF'25), Singapore, November, 2025.
Ryuji Hashimoto, Yuki Tanaka, Takehiro Takayanagi, Zhe Piao, Kiyoshi Izumi, Norm Salvaged Embedding: Improving Condition Alignment of Synthetic Time Series Generation in Finance, 6th ACM International Conference on AI in Finance (ICAIF'25), Singapore, November, 2025.
Yuki Tanaka, Ryuji Hashimoto, Takehiro Takayanagi, Zhe Piao, Yuri Murayama, and Kiyoshi Izumi, CoFinDiff: Controllable Financial Diffusion Model for Time Series Generation, International Joint Conferences on Artificial Intelligence (IJCAI), Montreal, Canada, August, 2025.
Takehiro Takayanagi, Kiyoshi Izumi, Javier Sanz-Cruzado, Richard McCreadie, Iadh Ounis, Are Generative AI Agents Effective Personalized Financial Advisors?, Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, July, 2025.
Takehiro Takayanagi, Masahiro Suzuki, Kiyoshi Izumi, Javier Sanz-Cruzado, Richard McCreadie, Iadh Ounis, FinPersona: An LLM-Driven Conversational Agent for Personalized Financial Advising, European Conference on Information Retrieval, April, 2025.
Takehiro Takayanagi, Hiroya Takamura, Kiyoshi Izumi, Chung-Chi Chen, Can GPT-4 Sway Experts’ Investment Decisions?, Findings of the Association for Computational Linguistics: NAACL 2025, April, 2025.
2024年
Takehiro Takayanagi, Masahiro Suzuki, Ryotaro Kobayashi, Hiroki Sakaji, Kiyoshi Izumi, Is ChatGPT the future of causal text mining? A comprehensive evaluation and analysis, 2024 IEEE International Conference on Big Data (BigData), 2024.
Meiyun Wang, Kiyoshi Izumi, Hiroki Sakaji, LLMFactor: Extracting Profitable Factors through Prompts for Explainable Stock Movement Prediction, Findings of the Association for Computational Linguistics: ACL 2024, in publication
2023年
Takehiro Takayanagi, Kiyoshi Izumi, Harnessing Behavioral Traits to Enhance Financial Stock Recommender Systems: Tackling the User Cold Start Problem, 2023 IEEE International Conference on Big Data (Big Data), Sorrento, Italy, 2023, December
Ryotaro Kobayashi, Yuri Murayama, Kiyoshi Izumi, Impact Analysis of Social Events on Industries through Narrative Causal Search, The 5th Financial Narrative Processing Workshop (FNP2023), Sorrento, Italy, December, 2023.
Tsubasa Ueda, Takehide Hirose, Kiyoshi Izumi, Export Nowcasting with AIS and Foot Traffic Data, 13th International Conference on Smart Computing and Artificial Intelligence (SCAI 2023) in 14th IIAI International Congress on Advanced Applied Informatics (IIAI AAI 2023), 2023. Koriyama, Japan, July 2023
Masanori HIRANO, Kiyoshi IZUMI, Quantitative Evaluation of Multi-agent Simulation using Generative Adversarial Network, 9th International Conference on Computational Social Science (IC2S2), Copenhagen, Denmark, July 20th, 2023.
Masanori HIRANO, Hiroki SAKAJI, Kiyoshi IZUMI,, Policy Gradient Stock GAN for Realistic Discrete Order Data Generation in Financial Markets, 13th International Conference on Smart Computing and Artificial Intelligence (SCAI 2023) in 14th IIAI International Congress on Advanced Applied Informatics (IIAI AAI 2023), Koriyama, Japan, July 9th, 2023.
Note: Accept rate (Full paper): 86 / 251 = 34%, Competitive paper award
Ryotaro Kobayashi, Yuri Murayama, Kiyoshi Izumi, Economic Causal Chain Presentation System Considering Output Diversity to Search Economic Ripple Effects, The 4th Workshop on Knowledge Discovery from Unstructured Data in Financial Services (KDF2023), 2023
Hiroki Sakaji, Ryotaro Kobayashi, Kiyoshi Izumi, Hiroyuki Mitsugi, Wataru Kuramoto, Summarization of Investment Reports Using Pre-trained Model, 13th International Conference on Smart Computing and Artificial Intelligence (SCAI 2023) in 14th IIAI International Congress on Advanced Applied Informatics (IIAI AAI 2023), pp. 554-559,Koriyama, Japan, July 2023
Takehiro Takayanagi, Chung-Chi Chen, and Kiyoshi Izumi , Personalized Dynamic Recommender System for Investors, International ACM SIGIR Conference on Research and Development in Information Retrieval , 2023
Takehiro Takayanagi, Kiyoshi Izumi, Atsuo Kato, Naoyuki Tsunedomi, Yukina Abe, Personalized Stock Recommendation with Investors’ Attention and Contextual Information, 2023 International ACM SIGIR Conference on Research and Development in Information Retrieval , 2023
2022年
Meiyun Wang, Hiroki Sakaji, Higashitani Hiroaki, Iwadare Mitsuhiro, Kiyoshi Izumi, A New Approach to Assessing Corporate R&D Capabilities: Exploring Patent Value Based on Machine Learning, 3rd Workshop on Women in AI and Finance, 3rd ACM International Conference on AI in Finance, 2022, Nov 2nd, 2022, New York, USA, 2022 November
Takehiro Takayanagi, Hiroki Sakaji, Kiyoshi Izumi, SETN: Stock Embedding Enhanced with Textual and Network Information, 2022 IEEE International Conference on Big Data (IEEE BigData 2022), 2022
Hiroki Sakaji, Masahiro Suzuki, Kiyoshi Izumi, Hiroyuki Mitsugi, Gradual Further Pre-training Architecture for Economics/Finance Domain Adaptation of Language Model, 2022 IEEE International Conference on Big Data (IEEE BigData 2022), pp. 2342-2345, 2022, Osaka, Japan, December
Rei Taguchi, Hiroki Sakaji, Kiyoshi Izumi, SSAAM: Sentiment Signal-based Asset Allocation Method with Causality Information, 2022 IEEE International Conference on Big Data (IEEE BigData 2022), pp.2363-2366, 2022, Osaka, Japan, December, 2022 Note:https://researchmap.jp/reitaguchi/published_papers/40693368
Masanori HIRANO, Ryo WAKASUGI, Kiyoshi IZUMI,, Analysis of Demand Response Scenarios by Industrial Consumers Using Artificial Electric Power Market Simulations, 7th International Conference on Business Management of Technology (BMOT 2022) in 12th IIAI International Congress on Advanced Applied Informatics (IIAI AAI 2022), pp. 547-554, 2022, DOI: doi.org/10.1109/IIAIAAI55812.2022.00111 Kanazawa, Japan, July 2022.
Masanori HIRANO, Kiyoshi IZUMI, Hiroki SAKAJI,, Data-driven Agent Design for Artificial Market Simulation, The 36th Annual Conference of the Japanese Society for Artificial Intelligence (JSAI2022), 2022, DOI: doi.org/10.11517/pjsai.JSAI2022.0_2S4IS2b01 pp. 2S4IS2b0, Kyoto, Japan, Jun,2022
■ Best paper award
Masanori HIRANO, Kiyoshi IZUMI,, Parameter Tuning Method for Multi-agent Simulation using Reinforcement Learning, The 9th International Conference on Behavioral and Social Computing (BESC 2022), pp. 1-7, 2022, DOI: doi.org/10.1109/BESC57393.2022.9995509 Matsuyama, Ehime, Japan, Oct. 2022.
Student best paper
Masanori HIRANO, Ryo WAKASUGI, Kiyoshi IZUMI,, Analysis of Carbon Neutrality Scenarios of Industrial Consumers Using Electric Power Market Simulations, The 24th International Conference on Principles and Practice of Multi-Agent Systems (PRIMA 2022), 2022, pp. 90-105, DOI: doi.org/10.1007/978-3-031-21203-1_6, Valencia, Spain, Nov. 2022.
Masanori HIRANO, Kiyoshi IZUMI,, Does Order Simultaneity Affect the Data Mining Task in Financial Markets? -- Effect Analysis of Order Simultaneity using Artificial Market, The 24th International Conference on Principles and Practice of Multi-Agent Systems (PRIMA 2022), 2022, pp. 297-313, DOI: doi.org/10.1007/978-3-031-21203-1_18, Valencia, Spain, Nov. 2022.
Masanori HIRANO, Kiyoshi IZUMI, Quantitative Tuning of Artificial Market Simulation using Generative Adversarial Network, The 6th IEEE International Conference on Agents (ICA 2022), pp. 12-17, 2022, DOI: doi.org/10.1109/ICA55837.2022.00009
Competitive Paper Award
Masanori HIRANO, Kiyoshi IZUMI,, Efficient Parameter Tuning for Multi-agent Simulation Using Deep Reinforcement Learning, 12th International Conference on Smart Computing and Artificial Intelligence (SCAI 2022-Winter) in 13th IIAI International Congress on Advanced Applied Informatics (IIAI AAI 2022 winter), 2022, Phuket, Thailand, Dec. 2022.
Naoto Minakawa, Kiyoshi Izumi, and Hiroki Sakaji, Bilateral Trade Flow Prediction by Gravity-informed Graph Auto-encoder, IEEE BigData 2022, 2022, Osaka, Japan, 2022 December
Takehiro Takayanagi, Information Retrieval in Financial Documents , AKBC 2022 Workshop, Knowledge Graphs in Finance and Economics, 2022, London, UK, 2022 Novemnber
Yuya Takada, Kiyoshi Izumi, Implementation of Biased Big Data to the Japanese Official Labor Statistics Using Supervised Learning under Covariate Shift, 2022 IEEE International Conference on Big Data, 2022, pp. 2052-2061, Osaka, Japan, 2022 December
Rei Taguchi, Hikaru Watanabe, Hiroki Sakajii, Kiyoshi Izumii, Kenji Hiramatsu, Proposal for Turning Point Detection Method using Financial Text and Transformer , The 36th Annual Conference of the Japanese Society for Artificial Intelligence, 2022, DOI: https://doi.org/10.11517/pjsai.JSAI2022.0_2S4IS2b02 Kyoto, Japan, 2022, June
Yoshiyuki Suimon, Hiroto Tanabe, Kiyoshi Izumi, The relationship between Twitter sentiment and mobility during the COVID-19 pandemic, 2022 IEEE International Conference on Big Data (IEEE BigData), 2022
Yoshito Noritake, Takanobu Mizuta, Ryuta Hemmi;,Shota Nagumo, Kiyoshi Izumi, Investigation on effect of excess buy orders using agent-based model, 2022 9th International Conference on Behavioural and Social Computing (BESC), Ehime, Japan, 2022 October, DOI:https://doi.org/10.1109/BESC57393.2022.9994930
Masanori HIRANO, Hiroki SAKAJI, Kiyoshi IZUMI,, Concept and Practice of Artificial Market Data Mining Platform,, 2022 IEEE Symposium on Computational Intelligence for Financial Engineering and Economics (CIFEr), 2022, DOI: doi.org/10.1109/CIFEr52523.2022.9776095 Vol. , No. , pp. 1-10, Online, May 2022.
Masanori Hirano, Hiroki Sakaji, Kiyoshi Izumi, Implementation of Actual Data for Artificial Market Simulation, The 21st International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2022) Note: Top Conference, pp. 1624-1626, DOI: doi.org/10.5555/3535850.3536056 online, May, 2022,
Naoto Minakawa, Kiyoshi Izumi, Hiroki Sakaji, Hitomi Sano, "Graph Representation Learning of Banking Transaction Network with Edge Weight-Enhanced Attention and Textual Information," The 2nd Workshop on Financial Technology on the Web (Fin-Web 2022), April, 2022. (Best Paper Award)
2021年
Hiroki Sakaji, Teruaki Hayashi, Yoshiaki Fukami, Takumi Shimizu, Hiroyasu Matsushima, Kiyoshi Izumi, "Retrieving of Data Similarity using Metadata on a Data Analysis Competition Platform," The 4th International Workshop on Cross-disciplinary Data Exchange and Collaboration In conjunction with 2021 IEEE International Conference on Big Data (CDEC2021), December, 2021.
Rei Taguchi, Hikaru Watanabe, Masanori Hirano, Masahiro Suzuki, Hiroki Sakaji, Kiyoshi Izumi, Kenji Hiramatsu, "Market Trend Analysis Using Polarity Index Generated from Analyst Reports," The 4th International Workshop on Cross-disciplinary Data Exchange and Collaboration In conjunction with 2021 IEEE International Conference on Big Data (CDEC2021), December, 2021.
Kiyoshi Izumi, Hitomi Sano, Hiroki Sakaji, Economic Causal-Chain Search and Economic Indicator Prediction using Textual Data, The 3rd Financial Narrative Processing Workshop (FNP 2021), September, 2021
Masanori Hirano, Kiyoshi Izumi, Hiroki Sakaji, STBM+: Advanced Stochastic Trading Behavior Model for Financial Markets based on Residual Blocks or Transformers, The 35th Annual Conference of the Japanese Society for Artificial Intelligence (JSAI), June, 2021
2020年
Hiroki Sakaji, Teruaki Hayashi, Kiyoshi Izumi, Yukio Ohsawa, Verification of Data Similarity using Metadata on a Data Exchange Platform, 2020 IEEE International Conference on Big Data (IEEE BigData 2020), December,2020, pp. 4467-4474
Masanori Hirano, Hiroyasu Matsushima, Kiyoshi Izumi, Hiroki Sakaji, STBM: Stochastic Trading Behavior Model for Financial Markets, Selected Papers from the Annual Conference of Japanese Society of Artificial Intelligence (JSAI 2020), Advances in Artificial Intelligence, Vol. 1357, pp. 157-165, Springer, July, 2021.
Masanori Hirano, Hiroyasu Matsushima, Kiyoshi Izumi, Implementation of Real Data for Financial Market Simulation using Clustering, Deep Learning, and Artificial Financial Market, The 23rd International Conference on Principles and Practice of Multi-Agent Systems (PRIMA 2020), November, 2020
Masanori Hirano, Hiroyasu Matsushima, Kiyoshi Izumi, Taisei Mukai, Simulation of Unintentional Collusion Caused by Auto Pricing in Supply Chain Markets, The 23rd International Conference on Principles and Practice of Multi-Agent Systems (PRIMA 2020), November, 2020
Yoshiyuki Suimon, Kiyoshi Izumi, Takashi Shimada, Hiroki Sakaji, Hiroyasu Matsushima, Estimating Manufacturing Activity via Machine Learning Analysis of High-frequency Electricity Demand Patterns, 5th International Conference on Business Management of Technology (BMOT), September, 2020
Tomoki Ito, Kota Tsubouchi, Hiroki Sakaji, Tatsuo Yamashita and Kiyoshi Izumi, SSNN: Sentiment Shift Neural Network, SIAM International Conference on Data Mining (SDM), Ohio, USA, May, 2020. (to appear) (acceptance rate = 24.0% (75/312))
Iwao Maeda, Hiroyasu Matsushima, Hiroki Sakaji, Kiyoshi Izumi, David Degraw, Hirokazu Tomioka, Atsuo Kato and Michiharu Kitano, "Learning Uncertainty in Market Trend Forecast Using Bayesian Neural Networks", The International Conference on Decision Economics (DECON 2019), pp.210-218, Feb. 2020.
Yono Kyoto, Kiyoshi Izumi, Hiroki Sakaji, Takashi Shimada and Hiroyasu Matsushima, "Measuring Macro Economic Uncertainty from News Text by Supervised LDA for Investor’s Decision Making", The International Conference on Decision Economics (DECON 2019), pp.125-133, Feb. 2020.
Kiyoshi Izumi, Shintaro Suda and Hiroki Sakaji, Economic News Impact Analysis Using Causal-Chain Search from Textural Data, The AAAI-20 Workshop on Knowledge Discovery from Unstructured Data in Financial Services, New York, USA, February, 2020.
Tomoki Ito, Kota Tsubouchi, Hiroki Sakaji, Tatsuo Yamashita and Kiyoshi Izumi, Word-level Contextual Sentiment Analysis with Interpretability, the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20), February 7-12, 2020, New York, US. (20.6% acceptance rate)
2019年
Masahiro Suzuki, Toshiya Katagi, Hiroki Sakaji, Kiyoshi Izumi, and Yasushi Ishikawa,Stock Price Analysis Using Combination of Analyst Reports and Several Documents, the 2nd International Workshop on Cross-disciplinary Data Exchange and Collaboration (CDEC 2019), November 8th, 2019 in conjunction with IEEE ICDM 2019, Beijing, China
Yuta Niki, Hiroki Sakaji, Kiyoshi Izumi, and Hiroyasu Matsushima, Causal Sentence Extraction from Multilingual Texts Using End-to-End LSTM Models, the 2nd International Workshop on Cross-disciplinary Data Exchange and Collaboration (CDEC 2019), November 8th, 2019 in conjunction with IEEE ICDM 2019, Beijing, China
Hiroki Sakaji, Yasutomo Kimura, Izumi Kiyoshi, and Hiroyasu Matsushima, Extraction of Volitional Utterances from Japanese Local Political Corpus, the 2nd International Workshop on Cross-disciplinary Data Exchange and Collaboration (CDEC 2019), November 8th, 2019 in conjunction with IEEE ICDM 2019, Beijing, China
Masanori Hirano, Kiyoshi Izumi, Hiroyasu Matshushima and Hiroki Sakaji, Comparison of Behaviors of Actual and Simulated HFT Traders for Agent Design, the 22nd International Conference on Principles and Practice of Multi-Agent Systems (PRIMA 2019), Torino, Italy, October 28th-31st, 2019 (26% acceptance rate of full paper)
Tomoki Ito, Kota Tsubouchi, Hiroki Sakaji, Kiyoshi Izumi, and Tatsuo Yamashita, CSNN: Contextual Sentiment Neural Network, IEEE International Conference on Data Mining (ICDM 2019), November 8-11, 2019, Beijing.(18.5% acceptance rate.)
Ryo Hamawaki, Jun'ichi Ozaki, Izumi Kiyoshi, Takashi Shimada, Hiroki Sakaji, Hiroyasu Matsushima, Chain Bankruptcy Simulation Considering Investment Banks to Companies, 2019 IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC 2019), pp.3764-3770, 06-09 October 2019, Bari, Italy
Masanori Hirano, Hiroki Sakaji, Kiyoshi Izumi, Hiroyasu Matsushima, "mhirano at the FinSBD Task: Pointwise Prediction Based on Multi-layer Perceptron for Sentence Boundary Detection", The First Workshop on Financial Technology and Natural Language Processing (FinNLP) IJCAI-Workshop, pp.102-107, Aug.2019.
Hiroki Sakaji, Ryota Kuramoto, Hiroyasu Matsushima, Kiyoshi Izumi, Takashi Shimada, Keita Sunakawa, "Financial Text Data Analytics Framework for Business Confidence Indices and Inter-Industry Relations", The First Workshop on Financial Technology and Natural Language Processing (FinNLP) IJCAI-Workshop, pp.40-46, Aug.2019.
Kiyoshi Izumi, Hiroki Sakaji, "Economic Causal-Chain Search using Text Mining Technology", The First Workshop on Financial Technology and Natural Language Processing (FinNLP) IJCAI-Workshop, pp.61-65, Aug.2019. (Best Paper Award at FinNLP 2019)
Ryo Hamawaki, Junichi Ozaki, Kiyoshi Izumi, Takashi Shimada, Hiroyasu Matsushima and Hiroki Sakaji, "Analysis of Investment Effect using Multiplex Network Simulation of Banks and Firms", 5th International Conference on Computational Social Science, Jul.2019.
Yoshinori Tanaka, Syunya Kodera, Fumihito Sato, Hiroki Sakaji and Kiyoshi Izumi,"The Extraction of Future-Oriented Sentences from Annual Reports", 7th International Conference on Smart Computing and Artificial Intelligence (SCAI 2019), pp.679-684, Jul.2019.
Iwao Maeda, Hiroyasu Matsushima, Hiroki Sakaji, Kiyoshi Izumi, David Degraw, Atsuo Kato and Michiharu Kitano,"Effectiveness of Uncertainty Consideration in Neural-Network-Based Financial Forecasting", 7th International Conference on Smart Computing and Artificial Intelligence (SCAI 2019), pp.673-678, Jul.2019.
[国際会議] Kyoto Yono, Kiyoshi Izumi, Hiroki Sakaji, Takashi Shimada and Hiroyasu Matsushima, "Analysis of Macro Economic Uncertainty from News Text with financial market", 7th International Conference on Smart Computing and Artificial Intelligence (SCAI 2019), pp.661-666, Jul.2019.
Kei Nakagawa, Shingo Sashida, Hiroki Sakaji and Kiyoshi Izumi,"Economic Causal Chain and Predictable Stock Returns", 7th International Conference on Smart Computing and Artificial Intelligence (SCAI 2019), pp.655-660, Jul.2019.
Yoshiyuki Suimon, Hiroki Sakaji, Kiyoshi Izumi, Takashi Shimada and Hiroyasu Matsushima, "Extraction of relationship between Japanese and US interest rates using machine learning methods", 7th International Conference on Smart Computing and Artificial Intelligence (SCAI 2019), pp.649-654, Jul.2019.
Tomoki Ito, Kota Tsubouchi, Hiroki Sakaji, Tatsuo Yamashita, Kiyoshi Izumi, "Word-level Sentiment Visualizer for Financial Documents", IEEE Computational Intelligence for Financial Engineering & Economics (CIFEr) 2019, pp.27-33, May 2019.
Yoshiyuki Suimon, Hiroki Sakaji, Kiyoshi Izumi, Takashi Shimada, Hiroyasu Matsushima, "Japanese long-term interest rate forecast considering the connection between the Japanese and US yield curve", IEEE Computational Intelligence for Financial Engineering & Economics (CIFEr) 2019, pp.34-40, May 2019.
Atsuki Nakayama, Kiyoshi Izumi, Hiroki Sakaji, Hiroyasu Matsushima, Takashi Shimada, Kenta Yamada, "Short-term Stock Price Prediction by Analysis of Order Pattern Images", IEEE Computational Intelligence for Financial Engineering & Economics (CIFEr) 2019, pp.84-89, May 2019.
Kyoto Yono, Kiyoshi Izumi, Hiroki Sakaji, Hiroyasu Matsushima, Takashi Shimada, "Extraction of Focused Topic and Sentiment of Financial Market by using Supervised Topic Model for Price Movement Prediction", IEEE Computational Intelligence for Financial Engineering & Economics (CIFEr) 2019, pp.149-155, May 2019.
Hiroki Sakaji, Akio Kobayashi, Masaki Kohana, Yasunao Takano and Kiyoshi Izumi, Estimation of Tags using Various Data for Online Videos, The 33-rd International Conference on Advanced Information Networking and Applications (AINA-2019), pp.301-312, Matsue, March 2019.
Hirofumi Yamamoto, Hiroki Sakaji, Hiroyasu Matsushima, Yuki Yamashita, Kyohei Osawa, Kiyoshi Izumi and Takashi Shimada, Forecasting Crypto-Asset Price using Influencer Tweets, The 33-rd International Conference on Advanced Information Networking and Applications (AINA-2019), pp.940-951 , Matsue, March 2019.
Tomoki Ito, Hiroki Sakaji, Kiyoshi Izumi, Kota Tsubiuchi and Tatsuo Yamashita, "Concept Crowd-based Sentiment Visualization for Financial Reviews", The International Conference on Decision Economics (DECON 2019), pp.183-191, Feb. 2019.
Kei Nakagawa, Tomoki Ito, Masaya Abe, Kiyoshi Izumi, Deep Recurrent Factor Model: Interpretable Non-Linear and Time-Varying Multi-Factor Model, AAAI-19 workshop on Network Interpretability for Deep Learning, Hawaii, US, January 2019
2018年
Masanori Hirano , Hiroki Sakaji, Shoko Kimura, Kiyoshi Izumi, Hiroyasu Matsushima, Shintaro Nagao, Atsuo Kato, "Selection of Related Stocks using Financial Text Mining", The 1st International Workshop on Cross-disciplinary Data Exchange and Collaboration (CDEC) in 18th IEEE International Conference on Data Mining Workshops (ICDMW2018), pp.191-198, Singapore, Nov. 2018.
Shin Nishioka, Kiyoshi Izumi, Wataru Matsumoto, Takashi Shimada, Hiroki Sakaji, Hiroyasu Matsushima, "Impact on Financial Markets of Dark Pools, Large Investor, and HFT", International Workshop on Artificial Market 2018 (IWAM2018) in conjunction with The 21st International Conference on Principles and Practice of Multi-Agent Systems (PRIMA2018), pp.4-16, Tokyo, Oct. 2018.
Masahiro Hirano, Kiyoshi Izumi, Hiroki Sakaji, Takashi Shimada, Hiroyasu Matsushima, "Impact Assessments of the CAR Regulation using Artificial Markets", International Workshop on Artificial Market 2018 (IWAM2018) in conjunction with The 21st International Conference on Principles and Practice of Multi-Agent Systems (PRIMA2018), pp.43-58, Tokyo, Oct. 2018.
Ryo Hamawaki, Kiyoshi Izumi, Hiroki Sakaji, Takashi Shimada, Hiroyasu Matsushima, "Chain Bankruptcy Size in Inter-bank Networks: the Effects of Asset Price Volatility and the Network Structure", International Workshop on Social Simulations and Supercomputers in conjunction with The 21st International Conference on Principles and Practice of Multi-Agent Systems (PRIMA2018), Tokyo, Oct. 2018.
2017年
Hiroki Sakaji, Risa Murono, Hiroyuki Sakai, Jason Bennett, Kiyoshi Izumi, Discovery of Rare Causal Knowledge from Financial Statement Summaries, The 2017 IEEE Symposium on Computational Intelligence for Financial Engineering and Economics (CIFEr), pp.602-608, Hawaii, USA, November, 2017.
Tomoki Ito, Hiroki Sakaji, Kiyoshi Izumi, Kota Tsubouchi, Tatsuo Yamashita, Development of Sentiment Indicators Using both Unlabeled and Labeled Posts, The 2017 IEEE Symposium on Computational Intelligence for Financial Engineering and Economics (CIFEr), pp.314-321, Hawaii, USA, November, 2017.
Tomoki Ito, Hiroki Sakaji, Kiyoshi Izumi, Kota Tsubouchi, Tatsuo Yamashita, Development of an Interpretable Neural Network Model for Creation of Polarity Concept Dictionaries, The 2017 IEEE International Conference on Data Mining Workshops, pp.1122-1131, New Orleans, USA, November, 2017.
Hiroki Sakaji, Atsuya Miyazaki, Hiroyuki Sakai, Kiyoshi Izumi, Extracting Laboratory Front Pages from University Websites, The 6th International Workshop on Web Services and Social Media In conjunction with The 20th International Conference on Network-Based Information Systems (NBiS-2017), pp.1117-1125, Toronto, Canada, August, 2017.
2016年
Takanobu Mizuta, Yoshito Noritake, Satoshi Hayakawa, Kiyoshi Izumi, Affecting Market Efficiency by Increasing Speed of Order Matching Systems on Financial Exchanges -- Investigation using Agent Based Model, IEEE Symposium Series on Computational Intelligence, Computational Intelligence for Financial Engineering and Economics (CIFEr), December 6-9, 2016, Athens
[会議論文] Tomoki Ito, Kiyoshi Izumi, Kota Tsubouchi and Tatsuo Yamashita, Polarity propagation of financial terms for market trend analyses using news articles, IEEE WCCI 2016, 2016年７月24-29日、カナダ.
Takuma Torii, Tomio Kamada, Kiyoshi Izumi, Kenta Yamada, Platform Design for Large-Scale Artificial Market Simulation and Preliminary Evaluation on the K computer, AROB 22nd 2017 (Jan. 19-21, 2017. B-Con PLAZA, Beppu. JAPAN) symposium
2015年
Takuma Torii, Kiyoshi Izumi, Kenta Yamada, Shock transfer by arbitrage trading and the role of circuit breakers, The 21st International Conference on Computing in Economics and Finance 2015 (CEF2015), Taipei, Taiwan, June 20--22, 2015.
2014年
Kiyoshi Izumi, Whole Tokyo Stock Exchange Market Simulation Project: Design of Financial Market Regulations using Agent-based Simulation, JST/CREST International Symposium on Post Petascale System Software,2014年12月3日.
Takuma Torii, Kiyoshi Izumi, Kenta Yamada. ``Whole Tokyo Stock Exchange Market Simulation Project: Design of Financial Market Regulations using Agent-based Simulation''. JST/CREST International Symposium on Post Petascale System Software (ISP2S2), IRC of Kobe University and RIKEN AICS, Kobe, Japan, December 2-4, 2014.
Naoki Matsumura, Kiyoshi Izumi, Kenta Yamada, A Marketing Simulation of a Retail Store with the Consumer Reactions to Stock-outs, Social Modeling and Simulations + Econophysics Colloquium 2014, Kobe,2014年11月5日.
Yuki Kusada, Tkanohbu Mizuta, S. Hakawa,Kiyoshi Izumi, Impacts of Position-Based Market Makers on Markets' Shares of Trading Volumes - An Artificial Market Approach, Social Modeling and Simulations + Econophysics Colloquium 2014,Kobe,2014年11月5日.
Takuma Torii, Kiyoshi Izumi, Kenta Yamada, Multi-Asset Artificial Market Simulation:Test of Market-wide Circuit Breaker Regulation, Social Modeling and Simulations + Econophysics Colloquium 2014,Kobe,2014年11月5日.
Takanobu Mizuta, Kiyoshi Izumi, Isao Yagi and Shinobu Yoshimura，” Regulations' Effectiveness for Market Turbulence by Large Mistaken Orders using Multi-Agent Simulation”, IEEE Computational Intelligence for Financial Engineering and Economics 2014, London, 2014年3月27日.
2014年3月27日, Takanobu Mizuta, Shintaro Kosugi, Takuya Kusumoto, Wataru Matsumoto and Kiyoshi Izumi, Do Dark Pools Stabilize Markets and Reduce Market Impacts? -- Investigations using Multi-Agent Simulations --, IEEE Computational Intelligence for Financial Engineering and Economics (CIFEr2014), March 27-18, 2014, London,UK.
3rd Best Paper Award
2013年
2013年9月13日 Takanobu Mizuta, Satoshi Hayakawa, Kiyoshi Izumi and Shinobu Yoshimura:Simulation Study on Effects of Tick Size Difference in Stock Markets Competition, Proceedings of The 8th International Workshop on Agent-based Approach in Economic and Social Complex Systems (AESCS2013), pp.235-246, Shibaura Institute of Technology, Tokyo, JAPAN, (2013.9.11-13).
Takanobu MIZUTA, Kiyoshi IZUMI, Shinobu YOSHIMURA, Price Variation Limits and Financial Market Bubbles: Artificial Market Simulations with Agents’ Learning Process, 2013 IEEE Symposium Series on Computational Intelligence (SSCI), CD-ROM, Singapore, (2013.4.16-19)
2012年
Chi WANG, Kiyoshi IZUMI, Takanobu MIZUTA, and Shinobu YOSHIMURA, Investigating the Impact of Trading Frequencies of Market Makers: a Multi-agent Simulation Approach, 4th World Congress on Social Simulation, Taiwan, Sep. 4-7, 2012.
2011年
Kiyoshi Izumi, Space Design by Agent Simulation based on Real Trajectory Data, SICE2011, Tokyo, Sep. 14, 2011.
Tohgoroh Matsui, Takashi Goto, Kiyoshi Izumi, Yu Chen, Compound Reinforcement Learning: Theory and An Application to Finance, The 9th European Workshop on Reinforcement Learning,, Greece, Sept 2011.
F. Toriumi, I. Okada, H. Yamamoto, H. Suwa, K. Izumi and Y. Hashimoto, Classification of Social Network Sites based on Network Indexes and Communication Patterns, International Workshop on Social Web Mining, 18 July 2011, Spain.
2010年
Kiyoshi Izumi, Takashi Goto, Tohgoroh Matsui, Trading Tests of Long-Term Market Forecast by Text Mining, Proceedings of 2010 IEEE International Conference on Data Mining Workshops, pp. 935-942, 2010.
Atsushi Nara, Kiyoshi Izumi, Hiroshi Iseki, Takashi Suzuki, Kyojiro Nambu, Yasuo Sakurai, Surgical Workflow Monitoring based on Trajectory Data Mining, Proceedings of International Workshop on Innovating Service Systems (ISS2010), 2010.
2009年
F. Toriumi, K. Izumi, and H. Matsui, Market Participant Estimation by using Artificial Market, The 1st Workshop on Multi-Agent Simulation in Finance and Economics, 2009.
I. Yagi, T. Mizuta, and K. Izumi, A study on the market impact of short-selling regulation using artificial markets, The 1st Workshop on Multi-Agent Simulation in Finance and Economics, 2009.
A. Nara, K. Izumi, H. Iseki, et.al., Trajectory Data Mining for Surgical Workflow Analysis, Geocomputing, 2009.
A. Nara, K. Izumi, H. Iseki, et.al., Surgical Workflow Analysis based on Staff’s Trajectory Patterns, The 1st Workshop on Modeling and Monitoring of Computer Assisted Interventions, 2009.
I. Yagi, T. Mizuta and K. Izumi, A study on the effectiveness of short-selling regulation using artificial markets, The 9th Asia-Pacific Complex Systems Conference, 2009.
2008年
K. Izumi, T. Goto, T. Matsui: Long-Term Market Analysis using Text Mining, The 7th International Conference on Computational Intelligence in Economics and Finance, 2008.
2007年
K. Izumi, H. Matsui, and Y. Matsuo: Market Impact Analysis by Socially Embedded Multi Agent Simulation, Eleventh International Conference on the Enhancement and Promotion of Computational Methods in Engineering and Science, 2007.
K. Izumi, F. Toriumi, and H. Matsui, Artificial Market 2.0: From Simulation to Service, The Fifth International Workshop on Agent-based Approaches in Economic and Social Complex Systems, 2007.
K. Izumi, H. Matsui, and Y. Matsuo: A Self-Impact Analysis by Artificial Market Simulation, Computational Intelligence and Data Mining, 2007.
K. Izumi, H. Matsui, and Y. Matsuo: Socially Embedded Multi Agent Based Simulation of Financial Market, Autonomous Agents and Multi-Agent Systems, 2007.
K. Izumi, H. Matsui, and Y. Matsuo: Integration of Artificial Market Simulation and Text Mining for Market Analysis, Hybrid Information Technology, 2007
2005年
H. Matsui, K. Izumi, and S. Tojo: Learning Foreign Exchange Intervention Policies with an Artificial Market, Proceedings of 8th Joint Conference on Information Science, pp. 841-844, 2005.
2004年
K. Izumi, T. Yamashita, and K. Kurumatani: Reward Mechanism of Agent Types in Minority Games, Proceedings of Second Conference of the European Social Simulation Association, ESSA 04, 2004.
K. Izumi, T. Yamashita, and K. Kurumatani: Analysis of Learning Types in an Artificial Market, Proceeding of Joint Workshop on Multi-Agent and Multi-Agent-Based Simulation, 2004.
K. Izumi, T. Yamashita, and K. Kurumatani: Control of Learning Types for Efficient Resource Allocation, Proceedings of North American Association for Computational Social and Organizational Science, 2004.
K. Izumi, T. Yamashita, and K. Kurumatani: Analysis of Efficiency and Accuracy of Learning in Minority Games, Proceedings of THE THIRD INTERNATIONAL JOINT CONFERENCE ON AUTONOMOUS AGENTS AND MULTI-AGENT SYSTEMS, 2004.
K. Izumi, T. Yamashita, and K. Kurumatani, Analysis of Complexity and Time Restriction in Resouces Alllocation Problems, Proceedings of the 9th Workshop on Economics and Heterogeneous Interacting Agents (WEHIA2004), 2004.
2002年
K. Izumi, Does Learnig by Market Participants Make Financial Markets Complicated?, AAAI Workshop Multi-Agent Modeling and Simulation of Economic Systems, 2002.
K. Izumi, Micro-macro relation in artificial market models, Proceedings of the 6th International Conference on Complex Systems 2002, pp. 36-43, 2002.
K. Izumi, S. Nakamura, K. Ueda, Identification of Agents’ Strategy Making Process by an Experimental Market, Proceedings of the 6th Joint Conference on Artificial Intelligence, pp. 1081-1084, 2002.
K. Izumi, Analysis of the Relation between Complexity of Agents and Complexity of Markets in an Artificial Market, Proceedings of Fourth International Conference on Computational Intelligence and Multimedia Applications (ICCIMA 2001), pp. 29-33, 2002.
2001年
K. Izumi, Complexity of Agents and Complexity of Markets, in Proceedings of JSAI 2001 International Workshop on Agent-based Approaches in Economic and Social Complex Systems (AESCS 2001).
2000年
K. Izumi and K. Ueda, Phase Transition in a Foreign Exchange Market: Analysis Based on an Artificial Market Approach, in Proceedings of Symposium on Empirical Science of Financial Fluctuations, pp 33-34, 2000.
K. Izumi and K. Ueda, Analysis of Thought Processes of Virtual Dealers in an Artificial Market, in P.P. Wang (eds.), Proceedings of the Fifth Joint Conference on Artificial Intelligence, vol. 2, pp 891-894, 2000.
1999年
K. Izumi and K. Ueda, Analysis of Exchange Rate Scenarios Using an Artificial Market Approach, in A. Amin, C.-H. Chen, et al. (eds.), Proceedings of the International Conference on Artificial Intelligence, pp 360-366, CSREA Press, 1999.
1998年
K. Izumi and K. Ueda, Emergent Phenomena in a Foreign Exchange Market: Analysis based on an Artificial Market Approach, in C. Adami et al. (eds.), "Artificial Life VI", pp398-402, MIT Press, 1998.
K. Izumi and K. Ueda, A Multiagent Model of a Foreign Exchange Market, in Preprints of IFAC/SCE/IFIP/IFORS/Society for Computational Economics Symposium on Computation in Economics, Finance and Engineering: Economic Systems, pp146-151, 1998.
1996年
K. Izumi and T. Okatsu, An Artificial Market Analysis of Exchange Rate Dynamics, in L.J. Fogel et.al (eds.), "Evolutionary Programming V", pp27-36, MIT Press, 1996.