Masanori HIRANO


平野 正徳

HIRANO, Masanori
Researcher,
Preferred Networks, Inc.

A Member of the Japanese Society for Artificial Intelligence, IEEE Member

Research Area: Social Simulation, Text Mining, Data Mining, Financial Market


Biography


Preferred Networks, Inc.

Oct. 2023 -

Researcher


The University of Tokyo

Apr. 2015 - Sep. 2023

Academic Experience

Oct. 2021 - Sep. 2023: Researcher (part-time), Preferred Networks, Inc.

Aug. 2019 - Sep. 2023: Technical Assistant, School of Engineering

Aug. 2021 - Sep. 2021: Research Intern, Preferred Networks, Inc.

Ph.D. program Ph.D. (Doctoral thesis: Fusion of Multi-agent Simulation and Data Mining for Financial Markets)

Apr. 2021 - Sep. 2023: Research Fellow (DC1), Japan Society for the Promotion of Science (JSPS)

Sep. 2020 - Sep. 2023: studied at Izumi Lab., Department of Systems Innovation, School of Engineering

Master's program (Early graduation) Master of Engineering (Master thesis: Implementation of Real Data for Financial Market Simulation)

Feb. 2020 - Mar. 2020: Visiting Research Student at Department of Computer Science, UCL (UK)

Apr. 2019 - Sep. 2023: World-leading Innovative Graduate Study Program Co-designing Future Society (WINGS-CFS)

Apr. 2019 - Sep. 2020 : studied at Izumi Lab., Department of Systems Innovation, School of Engineering

Undergraduate Bachelor of Engineering (Graduation thesis: Extraction of Related Stocks for Themed Mutual Funds using Text Mining)

Feb. 2019 - Mar. 2019 : studied as Visiting Student at Institut National des Sciences Appliquées de Lyon (France)

May 2017 - Mar. 2019 : researched at Izumi Lab., Faculty of Engineering

Jul. 2017 - Aug. 2017 : studied as Visiting Student at University of California, Berkeley (USA)

Apr. 2017 - Mar. 2019 : studied at Systems Design & Management Course, Department of Systems Innovation, Faculty of Engineering

Feb. 2017 : studied as Exchange Student at School of Global Policy and Strategy (GPS), University of California, San Diego (USA)

Apr. 2015 - Mar. 2017 : studied at Natural Sciences I, College of Arts and Sciences (Junior Division)


Junior & Senior High School at Komaba, University of Tsukuba

Apr. 2009 - Mar. 2015

Secondary Education

I spent 6 years studying at the Junior & Senior High School at Komaba, one of the top high school in Japan, as Secondary Education. This school played the role as an SSH (super science high school, it was assigned by MEXT.) So, I also joined some programs included the SSH programs.


Awards


  1. Dean’s Award AY2023, School of Engineering, The University of Tokyo (03/2024)
    University Press
  2. Best Paper Award (2023), The Japanese Institute of Electronics, Information and Communication Engineers (IEICE) Research Group on Language Understanding and Communication (NLC) (02/2024)Official HP
  3. AY2022 Student Best Paper Award, Special Interest Group on Financial Informatics of Japanese Society for Artificial Intelligence (10/2023)Official HP
  4. IEEE Computer Society Japan Chapter JAWS Young Researcher Award (09/2023) Official HP
  5. JAWS (Joint Agent Workshop & Symposium) Excellence Award (09/2023) Official HP
  6. Young Research Award, Special Interest Group on Natural Language Processing (SIG-NL) Information Processing Society of Japan (IPSJ) (09/2023) Official HP
  7. Honorable Mention Award, 18th Symposium of Young Researcher Association for NLP Studies (Yans) (08/2023) Official HP
  8. ELYZA Award (Sponsor Award), 18th Symposium of Young Researcher Association for NLP Studies (Yans) (08/2023) Official HP
  9. Competitive Paper Award in 14th IIAI International Congress on Advanced Applied Informatics (07/2023)
  10. Competitive Paper Award in 13th IIAI International Congress on Advanced Applied Informatics (12/2022)
  11. Best paper award in the 6th IEEE International Conference on Agents (IEEE ICA 2022) (11/2022)
  12. Student best paper award in the 9th International Conference on Behavioral and Social Computing (BESC 2022) (10/2022) Official HP
  13. Runner-up award in the 6th Symposium on Multi Agent Systems for Harmonization (SMASH22 Summer Symposium) (09/2022) Official HP
  14. Encouragement award in the 6th Symposium on Multi Agent Systems for Harmonization (SMASH22 Summer Symposium) (09/2022) Official HP
  15. Best Paper Award in 12th IIAI International Congress on Advanced Applied Informatics (07/2022)
    University Press / University Press 2
  16. The Japanese Society for Artificial Intelligence (JSAI) Incentive Award (AY 2021)
    Introduction (Japanese Only)
  17. The Japanese Society for Artificial Intelligence (JSAI) Annual Conference Excellence Award (2021)
    Introduction (Japanese Only) / University Press / University Press 2
  18. Dean’s Award AY2020, School of Engineering, The University of Tokyo (03/2021)
    University Press (Japanese Only) / University Press 2
  19. Nominated for student paper award in the 23rd International Conference on Principles and Practice of Multi-Agent Systems (PRIMA 2020) (11/19/2020) Official HP
  20. Nominated for best paper award in the 22nd International Conference on Principles and Practice of Multi-Agent Systems (PRIMA 2019) (10/30/2019) Official HP
  21. Winner (1st place) of Collusion Track in Supply Chain Management League (SCML) of the Tenth International Automated Negotiating Agents Competition (ANAC 2019) (08/15/2019) Official HP / University Press / University Press 2
  22. Winner (1st place) of Standard Track in Supply Chain Management League (SCML) of the Tenth International Automated Negotiating Agents Competition (ANAC 2019) (08/15/2019) Official HP / University Press / University Press 2
  23. Dean’s Award AY2018, Faculty of Engineering, The University of Tokyo (03/2019)
  24. The Japanese Society for Artificial Intelligence (JSAI) Annual Conference Student Incentive Award (2018)
    Introduction (Japanese Only) / University Press / University Press 2 (Japanese Only)

Publications (Refereed)


  1. Masanori HIRANO, Hiroki SAKAJI, Kiyoshi IZUMI,
    “PGSGAN: Policy Gradient Stock GAN,”
    International Journal of Smart Computing and Artificial Intelligence, vol.8, no.2, p.IJSCAI832, 2024.
    doi.org/10.52731/ijscai.v8.i2.832, detail
  2. Masahiro Suzuki, Hiroki Sakaji, Masanori Hirano, Kiyoshi Izumi,
    “FinDeBERTaV2: Word-Segmentation-Free Pre-trained Language Model for Finance,” [in Japanese]
    Transactions of the Japanese Society for Artificial Intelligence, vol.39, no.4, p.FIN23-G_1-14, 2024.
    doi.org/10.1527/tjsai.39-4_FIN23-G, detail
  3. Long CHENG, Masanori HIRANO, Kiyoshi IZUMI,
    “Analysis of Carbon Neutrality Strategies of Industrial Consumers Using Electric Power Market Simulations,” [in Japanese]
    Journal of Information Processing, vol.65, no.1, pp.46-60, 2024.
    doi.org/10.20729/00231730, detail
  4. Masanori HIRANO, Ryo WAKASUGI, Kiyoshi IZUMI,
    “Scenario Analysis of Demand Response Using Artificial Electric Power Market Simulations,”
    International Journal of Service and Knowledge Management, vol.7, no.2, p.IJSKM770, 2023.
    doi.org/10.52731/ijskm.v7.i2.770, detail
  5. Masanori HIRANO, Kiyoshi IZUMI,
    “Neural-network-based Parameter Tuning for Multi-agent Simulation using Deep Reinforcement Learning,”
    World Wide Web, vol.26, no.5, 2023.
    doi.org/10.1007/s11280-023-01197-5, detail
    Impact Factor: 3.7 (2022). Q1 Journal as of 2023.
  6. Masahiro SUZUKI, Hiroki SAKAJI, Masanori HIRANO, Kiyoshi IZUMI,
    “Constructing and Analyzing Domain-Specific Language Model for Financial Text Mining,”
    Information Processing & Management, vol.60, no.2, e103194, 2023.
    doi.org/10.1016/j.ipm.2022.103194, detail
    Impact Factor: 7.466, Q1 Journal as of 2022
  7. Masanori HIRANO, Kiyoshi IZUMI, Hiroki SAKAJI,
    “STBM+: Advanced Stochastic Trading Behavior Model for Financial Markets using Residual Blocks or Transformers,”
    New Generation Computing Optional, Springer, vol.40, no.1, pp.7-24, 2022.
    doi.org/10.1007/s00354-021-00145-z, detail
  8. Masanori HIRANO, Kiyoshi IZUMI, Hiroyasu MATSUSHIMA, Hiroki SAKAJI,
    “Comparing Actual and Simulated HFT Traders' Behavior for Agent Design,”
    Journal of Artificial Societies and Social Simulation, University of Surry, vol.23, no.6, e6, 2020.
    doi.org/10.18564/jasss.4304, detail
    (Q1 Journal as of 2020)
  9. Masanori HIRANO, Kiyoshi IZUMI, Takashi SHIMADA, Hiroyasu MATSUSHIMA, Hiroki SAKAJI,
    “Impact Analysis of Financial Regulation on Multi Assets Markets using Artificial Market Simulations,”
    Journal of Risk and Financial Management, MDPI, vol.13, no.4, e75, 2020.
    doi.org/10.3390/jrfm13040075, detail
  10. Masanori HIRANO, Hiroki SAKAJI, Shoko KIMURA, Kiyoshi IZUMI, Hiroyasu MATSUSHIMA, Shintaro NAGAO, Atsuo KATO,
    “Related Stocks Selection with Data Collaboration Using Text Mining,”
    Information (ISSN 2078-2489), MDPI, vol.10, no.3, e102, 2019.
    doi.org/10.3390/info10030102, detail

International Conferences (Refereed)


  1. Rawin Assabumrungrat, Kentaro Minami, Masanori Hirano,
    “Error Analysis of Option Pricing via Deep PDE Solvers: Empirical Study,”
    15th International Conference on Smart Computing and Artificial Intelligence (SCAI 2024) in 16th IIAI International Congress on Advanced Applied Informatics (IIAI AAI 2024), July 7th, 2024.
    detail
    arXiv:2311.07231 (doi.org/10.48550/arXiv.2311.07231), ssrn.com/abstract=4630864 (doi.org/10.2139/ssrn.4630864)
  2. Masanori Hirano, Kentaro Imajo,
    “Construction of Domain-specified Japanese Large Language Model for Finance through Continual Pre-training,”
    15th International Conference on Smart Computing and Artificial Intelligence (SCAI 2024) in 16th IIAI International Congress on Advanced Applied Informatics (IIAI AAI 2024), July 6th, 2024.
    detail
    arXiv:2404.10555 (doi.org/10.48550/arXiv.2404.10555), ssrn.com/abstract=4796245 (doi.org/10.2139/ssrn.4796245)
  3. Masanori Hirano,
    “Construction of a Japanese Financial Benchmark for Large Language Models,”
    Joint Workshop of the 7th Financial Technology and Natural Language Processing (FinNLP), the 5th Knowledge Discovery from Unstructured Data in Financial Services (KDF), and The 4th Workshop on Economics and Natural Language Processing (ECONLP) in conjunction with LREC-COLING-2024, pp.1-9, Torino, Italy, May 20th, 2024.
    aclanthology.org/2024.finnlp-1.1, detail
    arXiv:2403.15062 (doi.org/10.48550/arXiv.2403.15062), ssrn.com/abstract=4769124 (doi.org/10.2139/ssrn.4769124)
  4. Masahiro SUZUKI, Masanori HIRANO, Hiroki SAKAJI,
    “From Base to Conversational: Japanese Instruction Dataset and Tuning Large Language Models,”
    2023 IEEE International Conference on Big Data (IEEE BigData 2023), pp.5684-5693, Sorrento, Italy, Dec. 15th, 2023.
    doi.org/10.1109/BigData59044.2023.10386605, detail
    arXiv:2309.03412 (doi.org/10.48550/arXiv.2309.03412), ssrn.com/abstract=4564308 (doi.org/10.2139/ssrn.4564308)
  5. Masanori HIRANO, Kentaro MINAMI, Kentaro IMAJO,
    “Adversarial Deep Hedging: Learning to Hedge without Price Process Modeling,”
    4th ACM International Conference on AI in Finance (ICAIF '23), pp.19-26, Brooklyn, NY, USA, Nov. 27th, 2023.
    doi.org/10.1145/3604237.3626846, detail
    arXiv:2307.13217 (doi.org/10.48550/arXiv.2307.13217), ssrn.com/abstract=4520273 (doi.org/10.2139/ssrn.4520273)
  6. Masanori HIRANO, Masahiro SUZUKI, Hiroki SAKAJI,
    “llm-japanese-dataset v0: Construction of Japanese Chat Dataset for Large Language Models and its Methodology,”
    The 12th International Workshop on Web Services and Social Media (WSSM-2023) in The 26th International Conference on Network-Based Information Systems (NBiS-2023), pp.442-454, Chiang Mai, Thailand, Sep. 6th, 2023.
    doi.org/10.1007/978-3-031-40978-3_47, detail
    arXiv:2305.12720 (doi.org/10.48550/arXiv.2305.12720), ssrn.com/abstract=4454626 (doi.org/10.2139/ssrn.4454626)
  7. 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.
    detail
  8. 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), pp.361-368, Koriyama, Japan, July 9th, 2023.
    doi.org/10.1109/IIAI-AAI59060.2023.00077, detail
    arXiv:2204.13338 (doi.org/10.48550/arXiv.2204.13338), ssrn.com/abstract=4454626 (doi.org/10.2139/ssrn.4454626)
    Accept rate (Full paper): 86 / 251 = 34%, Competitive paper award!
  9. Masanori HIRANO, Kentaro IMAJO, Kentaro Minami, Takuya SHIMADA,
    “Efficient Learning of Nested Deep Hedging using Multiple Options,”
    13th International Conference on Smart Computing and Artificial Intelligence (SCAI 2023) in 14th IIAI International Congress on Advanced Applied Informatics (IIAI AAI 2023), pp.514-521, Koriyama, Japan, July 9th, 2023.
    doi.org/10.1109/IIAI-AAI59060.2023.00104, detail
    arXiv:2305.12264 (doi.org/10.48550/arXiv.2305.12264), ssrn.com/abstract=4454377 (doi.org/10.2139/ssrn.4454377)
    Accept rate (Full paper): 86 / 251 = 34%
  10. 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), pp.130-137, Phuket, Thailand, Dec. 12th, 2022.
    doi.org/10.1109/IIAI-AAI-Winter58034.2022.00035, detail
    Competitive Paper Award
  11. 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, Online, Nov. 28th, 2022.
    doi.org/10.1109/ICA55837.2022.00009, detail
    Accept rate (Oral): 6 / 17 = 35%, Best paper award
  12. 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), pp.297-313, Valencia, Spain, Nov. 17th, 2022.
    doi.org/10.1007/978-3-031-21203-1_18, detail
    Accept rate (Long paper): 31 / 100 = 31%
  13. 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), pp.90-105, Valencia, Spain, Nov. 17th, 2022.
    doi.org/10.1007/978-3-031-21203-1_6, detail
    Accept rate (Long paper): 31 / 100 = 31%
  14. 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, Matsuyama, Ehime, Japan, Oct. 29th, 2022.
    doi.org/10.1109/BESC57393.2022.9995509, detail
    Accept rate (Long paper): 22 / 83 = 27%; Student best paper.
  15. Masahiro SUZUMI, Hiroki SAKAJI, Masanori HIRANO, Kiyoshi IZUMI,
    “Constructing and Analyzing Domain-Specific Language Model for Financial Text Mining,”
    Information Processing and Management Conference, Online, Oct. 21st, 2022.
    detail
  16. 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, Kanazawa, Japan, July 7th, 2022.
    doi.org/10.1109/IIAIAAI55812.2022.00111, detail
    Accept rate (Long paper): 80 / 239 = 33%, Best paper award!
  17. Masanori HIRANO, Kiyoshi IZUMI, Hiroki SAKAJI,
    “Implementation of Actual Data for Artificial Market Simulation,”
    The 21st International Conference on Autonomous Agents and Multiagent Systems (AAMAS2022), pp.1624-1626, Online, May 13th, 2022.
    doi.org/10.5555/3535850.3536056, detail
    www.ifaamas.org/Proceedings/aamas2022/pdfs/p1624.pdf
  18. 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), pp.1-10, Online, May 5th, 2022.
    doi.org/10.1109/CIFEr52523.2022.9776095, detail
  19. 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 (CDEC2021) in conjunction with 2021 IEEE International Conference on Big Data (Big Data), pp.3486-3494, Online, Dec. 15th, 2021.
    doi.org/10.1109/BigData52589.2021.9671702, detail
  20. 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, 2021.
    doi.org/10.1007/978-3-030-73113-7_14, detail
  21. Masanori HIRANO, Hiroyasu MATSUSHIMA, Kiyoshi IZUMI, Hiroki SAKAJI,
    “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), pp.3-18, Online, Nov. 19th, 2020.
    doi.org/10.1007/978-3-030-69322-0_1, detail
    Accept rate (Full paper): 19 / 50 = 38%, Nominated for studnet paper award!
  22. 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), pp.352-359, Online, Nov. 19th, 2020.
    doi.org/10.1007/978-3-030-69322-0_24, detail
  23. Masanori HIRANO, Kiyoshi IZUMI, Hiroyasu MATSUSHIMA, 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, Oct. 31st, 2019.
    detail
    Accept rate (Long paper): 29 / 112 = 26%, Nominated for best paper award!: 3 / 112
    Published as a Journal article
  24. 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 (FinNLP2019) in conjunction with the International Joint Conference on Artificial Intelligence (IJCAI) 2019, pp.102-107, Macao, China, Aug. 12th, 2019.
    aclanthology.org/W19-5518/, detail
  25. 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 2018 IEEE International Conference on Data Mining Workshops (ICDMW), pp.191-198, Singapore, Singapore, Nov. 17th, 2018.
    doi.org/10.1109/ICDMW.2018.00036, detail
  26. Masanori 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, Japan, Oct. 30th, 2018.
    www.u-mart.org/IWAM2018/CameraReady/IWAM2018_paper_2.pdf, detail

Domestic Conferences (Non-refereed)


  1. Kazuki Matoya, Yunzhuo Wang, Masanori Hirano, Kentaro Imajo,
    “Efficient Deep Hedging mechanism based on value function learning,” [in Japanese]
    The 38th Annual Conference of the Japanese Society for Artificial Intelligence, p.JSAI2024_4M3GS1002, Hamamatsu, Shizuoka, Japan, May 31st, 2024.
    doi.org/10.11517/pjsai.JSAI2024.0_4M3GS1002, detail
  2. Kentaro Imajo, Kei Nakagawa, Kazuki Matoya, Masanori Hirano, Masana Aoki, Taku Imahase,
    “Residual return extraction using Principal Component Equivalence method,” [in Japanese]
    The 38th Annual Conference of the Japanese Society for Artificial Intelligence, p.JSAI2024_3D5GS205, Hamamatsu, Shizuoka, Japan, May 30th, 2024.
    doi.org/10.11517/pjsai.JSAI2024.0_3D5GS205, detail
  3. Kei Nakagawa, Masanori Hirano, Kentaro Minami, Takanobu Mizuta,
    “Impact of the number of AI traders on the market --Micro-foundations of the GARCH model,” [in Japanese]
    The 38th Annual Conference of the Japanese Society for Artificial Intelligence, p.JSAI2024_3Xin201, Hamamatsu, Shizuoka, Japan, May 30th, 2024.
    doi.org/10.11517/pjsai.JSAI2024.0_3Xin201, detail
  4. Masanori Hirano,
    “Experiments of Deep Hedging using Artificial Market Simulation,” [in Japanese]
    The 38th Annual Conference of the Japanese Society for Artificial Intelligence, Hamamatsu, Shizuoka, Japan, May 29th, 2024.
    doi.org/10.11517/pjsai.JSAI2024.0_2F1GS503, detail
  5. Masanori HIRANO,
    “Construction of a Japanese Financial Benchmark for Large Language Model Evaluation in the Financial Domain,” [in Japanese]
    30th Annual Meeting of the Association for Natural Language Processing (NLP2024), pp.1570-1574, Kobe, Hyogo, Japan, Mar. 18th, 2024.
    www.anlp.jp/proceedings/annual_meeting/2024/pdf_dir/C6-4.pdf, detail
  6. Masanori HIRANO,
    “Construction of a Japanese Financial Benchmark for Large Language Model Evaluation in the Financial Domain and the Performances of Models,” [in Japanese]
    The 32nd meeting of Special Interest Group on Financial Informatics of Japanese Society for Artificial Intelligence (SIG-FIN), pp.28-35, Shibuya, Tokyo, Japan, Mar. 2nd, 2024.
    doi.org/110.11517/jsaisigtwo.2023.FIN-032_28, detail
  7. Masanori HIRANO, Ryoosuke TAKATA, Kiyoshi IZUMI,
    “PAMS: Platform for Artificial Market Simulations --Python-based Platform for Artificial Market Simulations and Challenges on its Integration with Deep Learning--,” [in Japanese]
    Joint Agent Workshops and Symposium 2023 (JAWS2023), Noboribetsu, Hokkaido, Japan, Sep. 13th, 2023.
    detail
  8. Masahiro SUZUKI, Masanori HIRANO, Hiroki SAKAJI,
    “LoRA Tuning Conversational Japanese Large Language Models using Japanese Instruction Dataset,” [in Japanese]
    The 20th Text Analytics Symposium, Sakai, Osaka, Japan, Sep. 6th, 2023.
    ken.ieice.org/ken/paper/20230906NCwg/, detail
  9. Masanori HIRANO, Masahiro SUZUKI, Hiroki SAKAJI,
    “llm-japanese-dataset v0: Building a Japanese chat dataset for large-scale language models,” [in Japanese]
    Special Interest Group on Natural Language Processing, Information Processing Society of Japan (SIG-NL, IPSJ), Yotsuya, Tokyo, Japan, Sep. 1st, 2023.
    id.nii.ac.jp/1001/00227482/, detail
  10. Long CHENG, Kiyoshi IZUMI, Masanori HIRANO,
    “Analysis of Carbon Neutrality Scenarios of Industrial Consumers Combining Power Generation, Storage, and DR Using an Electricity Market Model,”
    The 37th Annual Conference of the Japanese Society for Artificial Intelligence (JSAI2023), Kumamoto, Japan, June 8th, 2023.
    doi.org/10.11517/pjsai.JSAI2023.0_3U1IS305, detail
  11. Masanori HIRANO, Kiyoshi IZUMI,
    “Quantitative Evaluation of Multi-agent Simulation using Generative Adversarial Network -- An Alternative of Qualitative Evaluation for Artificial Market Simulation,”
    The 37th Annual Conference of the Japanese Society for Artificial Intelligence (JSAI2023), p.3U1IS301, Kumamoto, Japan, June 8th, 2023.
    doi.org/10.11517/pjsai.JSAI2023.0_3U1IS301, detail
  12. Long CHENG, Kiyoshi IZUMI, Masanori HIRANO,
    “Analysis of Power Procurement Strategies of Industrial Consumers Combining Power Generation, Storage, and DR Using Electric Power Market Simulations,” [in Japanese]
    The 30th meeting of Special Interest Group on Financial Informatics of Japanese Society for Artificial Intelligence (SIG-FIN), pp.24-31, Bunkyo, Tokyo, Japan, Mar. 4th, 2023.
    doi.org/10.11517/jsaisigtwo.2023.FIN-030_24, detail
  13. Masanori HIRANO, Kentaro MINAMI, Kentaro IMAJO,
    “Adversarial Deep Hedging Free from the Assumption of Underliers' Price Process,” [in Japanese]
    The 30th meeting of Special Interest Group on Financial Informatics of Japanese Society for Artificial Intelligence (SIG-FIN), pp.51-57, Bunkyo, Tokyo, Japan, Mar. 4th, 2023.
    doi.org/10.11517/jsaisigtwo.2023.FIN-030_51, detail
  14. 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), p.2S4IS2b01, Kyoto, Japan, June 15th, 2022.
    doi.org/10.11517/pjsai.JSAI2022.0_2S4IS2b01, detail
  15. Masanori HIRANO, Kentaro IMAJO, Kentaro Minami, Takuya SHIMADA,
    “Nested Deep Hedging Mechanism for Multiple Options Hedging,” [in Japanese]
    The 28th meeting of Special Interest Group on Financial Informatics of Japanese Society for Artificial Intelligence (SIG-FIN), pp.27-34, Bunkyo, Tokyo, Japan, Mar. 12th, 2022.
    doi.org/10.11517/jsaisigtwo.2022.FIN-028_27, detail
  16. Masahiro SUZUKI, Hiroki SAKAJI, Masanori HIRANO, Kiyoshi IZUMI,
    “Construction and Validation of a Pre-Training and Additional Pre-Training Financial Language Model,” [in Japanese]
    The 28th meeting of Special Interest Group on Financial Informatics of Japanese Society for Artificial Intelligence (SIG-FIN), pp.132-137, Bunkyo, Tokyo, Japan, Mar. 12th, 2022.
    doi.org/10.11517/jsaisigtwo.2022.FIN-028_132, detail
  17. Ryo WAKASUGI, Kiyoshi IZUMI, Masanori HIRANO,
    “Analysis of Demand Response Scenarios by Large Consumers Using an Electricity Market Model,” [in Japanese]
    The 28th meeting of Special Interest Group on Financial Informatics of Japanese Society for Artificial Intelligence (SIG-FIN), pp.19-24, Bunkyo, Tokyo, Japan, Mar. 12th, 2022.
    doi.org/10.11517/jsaisigtwo.2022.FIN-028_19, detail
  18. Ryo WAKASUGI, Kiyoshi IZUMI, Masanori HIRANO,
    “Analysis of Electricity Procurement Scenarios for Achieving Carbon Neutrality by Large Consumers,” [in Japanese]
    The 21st Special Interest Group on Data Oriented Constructive Mining and Simulation (DOCMAS), Rusutsu, Hokkai-do, Japan, Mar. 9th, 2022.
    collabodesign.org/docmas/2022/03/09/160/, detail
    Award wining!
  19. Masahiro SUZUKI, Hiroki SAKAJI, Masanori HIRANO, Kiyoshi IZUMI,
    “Construction and Validation of a Pre-Training Language Model Using Financial Documents,” [in Japanese]
    The 27th meeting of Special Interest Group on Financial Informatics of Japanese Society for Artificial Intelligence (SIG-FIN), pp.5-10, Online, Oct. 9th, 2021.
    sigfin.org/?027-02, detail
  20. Rei TAGUCHI, Hikaru WATANABE, Masanori HIRANO, Masahiro SUZUKI, Hiroki SAKAJI, Kiyoshi IZUMI, Kenji HIRAMATSU,
    “Market Causality Analysis Using Polar Indicators Generated from Financial Texts,” [in Japanese]
    The 27th meeting of Special Interest Group on Financial Informatics of Japanese Society for Artificial Intelligence (SIG-FIN), pp.36-43, Online, Oct. 9th, 2021.
    sigfin.org/?027-07, detail
  21. Masahiro SUZUMI, Hiroki SAKAJI, Masanori HIRANO, Kiyoshi IZUMI,
    “Performance Validation of Pre-Trained BERT in the Financial Domain,” [in Japanese]
    The 18th Text Analytics Symposium, IEICE Tech. Rep., vol.12, no.178, NLC2021-12, pp.26-29, Online, Sep. 16th, 2021.
    www.ieice.org/ken/paper/20210916yCfG/, detail
  22. 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 (JSAI2021), p.2N1-IS-2a-03, Online, June 9th, 2021.
    doi.org/10.11517/pjsai.JSAI2021.0_2N1IS2a03, detail
    Award wining!
  23. Ryo Wakasugi, Kiyoshi Izumi, Masanori HIRANO,
    “Demand Responce Effectiveness Analysis Using Power Market Multi-Agent Simulation and Plant Power Consumption Model,” [in Japanese]
    The 35th Annual Conference of the Japanese Society for Artificial Intelligence (JSAI2021), p.2I3-GS-5b-04, Online, June 9th, 2021.
    doi.org/10.11517/pjsai.JSAI2021.0_2I3GS5b04, detail
  24. Masanori HIRANO, Hiroyasu MATSUSHIMA, Kiyoshi IZUMI, Hiroki SAKAJI,
    “STBM: Stochastic Trading Behavior Model for Financial Markets Based on Long Short-Term Memory,”
    The 34th Annual Conference of the Japanese Society for Artificial Intelligence (JSAI2020), p.1K4-ES-2-04, Online, June 9th, 2020.
    doi.org/10.11517/pjsai.JSAI2020.0_1K4ES204, detail
  25. Masanori HIRANO, Hiroki SAKAJI, Hiroyasu MATSUSHIMA, Kiyoshi IZUMI,
    “Unsupervised Extraction for Important Sentences in Financial Documents through Learning Other Tasks,” [in Japanese]
    26th Annual Meeting of the Association for Natural Language Processing (NLP2020), pp.569-572, Online, Mar. 18th, 2020.
    www.anlp.jp/proceedings/annual_meeting/2020/pdf_dir/B3-4.pdf, detail
  26. Masanori HIRANO, Hiroki SAKAJI, Shoko KIMURA, Kiyoshi IZUMI, Hiroyasu MATSUSHIMA, Shintaro NAGAO, Atsuo KATO,
    “Development of Search Tool for Listed Company Related to ThemesUsing Text Mining,” [in Japanese]
    The 24th meeting of Special Interest Group on Financial Informatics of Japanese Society for Artificial Intelligence (SIG-FIN), pp.1-8, Kichijoji, Tokyo, Japan, Mar. 15th, 2020.
    sigfin.org/?024-41, detail
  27. Masanori HIRANO, Kiyoshi IZUMI, Hiroyasu MATSUSHIMA, Hiroki SAKAJI, Takashi SHIMADA,
    “Analysis of Limit Orders by High-Frequency Traders in Tokyo Stock Exchange,” [in Japanese]
    The 33rd Annual Conference of the Japanese Society for Artificial Intelligence, p.2O1-J-13-04, Niigata, Niigata, Japan, June 5th, 2019.
    doi.org/10.11517/pjsai.JSAI2019.0_2O1J1304, detail
  28. Masanori HIRANO, Hiroki SAKAJI, Shoko KIMURA, Kiyoshi IZUMI, Hiroyasu MATSUSHIMA, Shintaro NAGAO, Atsuo KATO,
    “Estimation of Hypernym or Hyponym using Word Co-occurrence in Documents,” [in Japanese]
    25th Annual Meeting of the Association for Natural Language Processing (NLP2019), pp.597-600, Nagoya, Aichi, Japan, Mar. 14th, 2019.
    www.anlp.jp/proceedings/annual_meeting/2019/pdf_dir/P3-22.pdf, detail
  29. Masanori HIRANO, Hiroto YONENOH, Kiyoshi IZUMI,
    “Effects Analysis of CAR Regulations on Financial Markets using Artificial Market Simulations,” [in Japanese]
    The 32nd Annual Conference of the Japanese Society for Artificial Intelligence (JSAI2018), p.2P205, Kagoshima, Kagoshima, Japan, June 6th, 2018.
    doi.org/10.11517/pjsai.JSAI2018.0_2P205, detail
    [Abstract Correction (Japanese)] / Award winning!

Preprints


  1. Masahiro Hirano,
    “Construction of a Japanese Financial Benchmark for Large Language Models,”
    arXiv:2403.15062 (doi.org/10.48550/arXiv.2403.15062), ssrn.com/abstract=4769124 (doi.org/10.2139/ssrn.4769124)
    detail
  2. Masanori HIRANO,
    “Construction of a Japanese Financial Benchmark for Large Language Model Evaluation in the Financial Domain,” [in Japanese]
    doi.org/10.51094/jxiv.564, detail
  3. Rawin Assabumrungrat, Kentaro Minami, Masanori Hirano,
    “Error Analysis of Option Pricing via Deep PDE Solvers: Empirical Study,”
    arXiv:2311.07231 (doi.org/10.48550/arXiv.2311.07231), ssrn.com/abstract=4630864 (doi.org/10.2139/ssrn.4630864)
    detail
  4. Masahiro SUZUKI, Masanori HIRANO, Hiroki SAKAJI,
    “From Base to Conversational: Japanese Instruction Dataset and Tuning Large Language Models,”
    arXiv:2309.03412 (doi.org/10.48550/arXiv.2309.03412), ssrn.com/abstract=4564308 (doi.org/10.2139/ssrn.4564308)
    doi.org/10.48550/arXiv.2309.03412, detail
  5. Masanori HIRANO, Ryosuke TAKATA, Kiyoshi IZUMI,
    “PAMS: Platform for Artificial Market Simulations -- Python-based Platform for Artificial Market Simulations and\Challenges on its Integration with Deep Learning --,” [in Japanese]
    doi.org/10.51094/jxiv.461, detail
  6. Masanori HIRANO, Kentaro MINAMI, Kentaro IMAJO,
    “Adversarial Deep Hedging: Learning to Hedge without Price Process Modeling,”
    arXiv:2307.13217 (doi.org/10.48550/arXiv.2307.13217), ssrn.com/abstract=4520273 (doi.org/10.2139/ssrn.4520273)
    detail
  7. Masahiro SUZUKI, Masanori HIRANO, Hiroki SAKAJI,
    “LoRA Tuning Conversational Japanese Large Language Models using Japanese Instruction Dataset,” [in Japanese]
    doi.org/10.51094/jxiv.422, detail
  8. Masanori HIRANO, Masahiro SUZUKI, Hiroki SAKAJI,
    “llm-japanese-dataset v0: Construction of Japanese Chat Dataset for Large Language Models,” [in Japanese]
    doi.org/10.51094/jxiv.383, detail
  9. Masanori HIRANO, Masahiro SUZUKI, Hiroki SAKAJI,
    “llm-japanese-dataset v0: Construction of Japanese Chat Dataset for Large Language Models and its Methodology,”
    arXiv:2305.12720 (doi.org/10.48550/arXiv.2305.12720), ssrn.com/abstract=4454626 (doi.org/10.2139/ssrn.4454626)
    detail
  10. Masanori HIRANO, Kentaro IMAJO, Kentaro MINAMI, Takuya SHIMADA,
    “Efficient Learning of Nested Deep Hedging using Multiple Options,”
    arXiv:2305.12264 (doi.org/10.48550/arXiv.2305.12264), ssrn.com/abstract=4454377 (doi.org/10.2139/ssrn.4454377)
    detail
  11. Masanori HIRANO, Hiroki SAKAJI, Kiyoshi IZUMI,
    “Policy Gradient Stock GAN for Realistic Discrete Order Data Generation in Financial Markets,”
    arXiv:2204.13338 (doi.org/10.48550/arXiv.2204.13338), ssrn.com/abstract=4095304 (doi.org/10.2139/ssrn.4095304)
    detail

Talks


  1. Masahiro SUZUKI, Masanori HIRANO, and Hiroki SAKAJI
    "Construction of Japanese Instruction Dataset and its Application to Tuning of Large-scale Language Models" (in Japanese)
    18th Symposium of Young Researcher Association for NLP Studies (Yans), Tokyo, Japan, August 31st, 2023
  2. Masanori HIRANO,
    "Development and Application of Deep Hedging" (in Japanese)
    MPT Forum, Tokyo, Japan, June 1st, 2023
    https://mptforum.org/kiroku/season=2023
  3. Masanori HIRANO, Kiyoshi IZUMI
    "Toward Quantitative Evaluation of Artificial Market Simulation Using GAN" (in Japanese)
    Symposium on Multi Agent Systems for Harmonization 2022 Summer Symposium, Hamamatsu, Shizuoka, Japan, Sep. 16th, 2022
  4. Masahiro SUZUKI, Hiroki SAKAJI, Masanori HIRANO, and Kiyoshi IZUMI
    "Towards a Pre-Learning BERT Model for the Financial Domain" (in Japanese)
    16th Symposium of Young Researcher Association for NLP Studies (Yans), Online, August 31st, 2021
  5. Masanori HIRANO, Hiroki SAKAJI, Kiyoshi IZUMI, and Hiroyasu MATSUSHIMA
    "Introduction of listed company search system related to theme" (in Japanese)
    14th Symposium of Young Researcher Association for NLP Studies (Yans), Sapporo, Hokkaido, Japan, August 26th, 2019
  6. Masanori HIRANO,
    "SCM League: UTokyo Izumi Lab." in ANAC Session
    Twelfth International Workshop on Agent-based Complex Automated Negotiations (ACAN2019) in conjunction with IJCAI 2019, Macau, China, Aug. 11th, 2019

Misc


  1. Masanori HIRANO, Taisei MUKAI, Hiroyasu MATSUSHIMA, and Kiyoshi IZUMI
    "Insurance Fraud Factory Manager Agent at ANAC2019 Supply Chain Management League,"
    The Tenth International Automated Negotiating Agents Competition (ANAC2019) of IJCAI 2019, Macau, China, Aug. 15th, 2019.
    Wins in 2 tracks!: 1st place in Standard Track & 1st place in Collusion Track

Grant


  1. Apr. 2021 - Mar. 2024: Research Fellow (DC1) Grant, Japan Society for the Promotion of Science (JSPS), 9,700,000 JPY (Approx. 88,000 USD)


Patents


  1. 特許6596565: 抽出システムおよびプログラム

Works


  1. japanese-lm-fin-harness (2023 release)
  2. izumi-lab/llm-japanese-dataset (2023 release)
  3. PAMS (2022 release)
  4. pfhedge (2021 release)
  5. PlhamJ (2019/04 release)
  6. Plham v0.3 (2019/03 release)

Contributed Articles


  1. Masanori HIRANO,
    "AAMAS 2022 (The 21st International Conference on Autonomous Agents and Multiagent Systems)", Journal of the Japanese Society for Artificial Intelligence, Vol.37, No.5, pp. 679-680, 2022. doi.org/10.11517/jjsai.37.5_679
  2. Masanori HIRANO,
    教育用計算機システム(ECCS)相談員の声, in "Digital Life", Information Technology Center, The University of Tokyo, pp.30-31, Vol.30 (2018.3), 2018. ISSN: 1345-3017