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Masanori Hirano 0001
Person information
- unicode name: 平野 正徳
- affiliation: University of Tokyo
Other persons with the same name
- Masanori Hirano — disambiguation page
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2020 – today
- 2024
- [i8]Masanori Hirano:
Experimental Analysis of Deep Hedging Using Artificial Market Simulations for Underlying Asset Simulators. CoRR abs/2404.09462 (2024) - [i7]Masanori Hirano, Kentaro Imajo:
Construction of Domain-specified Japanese Large Language Model for Finance through Continual Pre-training. CoRR abs/2404.10555 (2024) - 2023
- [j5]Masahiro Suzuki
, Hiroki Sakaji
, Masanori Hirano
, Kiyoshi Izumi:
Constructing and analyzing domain-specific language model for financial text mining. Inf. Process. Manag. 60(2): 103194 (2023) - [j4]Masanori Hirano
, Kiyoshi Izumi:
Neural-network-based parameter tuning for multi-agent simulation using deep reinforcement learning. World Wide Web (WWW) 26(5): 3535-3559 (2023) - [c18]Masahiro Suzuki
, Masanori Hirano, Hiroki Sakaji:
From Base to Conversational: Japanese Instruction Dataset and Tuning Large Language Models. IEEE Big Data 2023: 5684-5693 - [c17]Masanori Hirano
, Kentaro Minami, Kentaro Imajo:
Adversarial Deep Hedging: Learning to Hedge without Price Process Modeling. ICAIF 2023: 19-26 - [c16]Masanori Hirano
, Hiroki Sakaji, Kiyoshi Izumi:
Policy Gradient Stock GAN for Realistic Discrete Order Data Generation in Financial Markets. IIAI-AAI 2023: 361-368 - [c15]Masanori Hirano
, Kentaro Imajo, Kentaro Minami, Takuya Shimada:
Efficient Learning of Nested Deep Hedging using Multiple Options. IIAI-AAI 2023: 514-521 - [c14]Masanori Hirano
, Masahiro Suzuki
, Hiroki Sakaji:
llm-japanese-dataset v0: Construction of Japanese Chat Dataset for Large Language Models and Its Methodology. NBiS 2023: 442-454 - [i6]Masanori Hirano
, Masahiro Suzuki
, Hiroki Sakaji:
llm-japanese-dataset v0: Construction of Japanese Chat Dataset for Large Language Models and its Methodology. CoRR abs/2305.12720 (2023) - [i5]Masanori Hirano
, Kentaro Minami, Kentaro Imajo:
Adversarial Deep Hedging: Learning to Hedge without Price Process Modeling. CoRR abs/2307.13217 (2023) - [i4]Masahiro Suzuki
, Masanori Hirano, Hiroki Sakaji:
From Base to Conversational: Japanese Instruction Dataset and Tuning Large Language Models. CoRR abs/2309.03412 (2023) - [i3]Masanori Hirano, Ryosuke Takata, Kiyoshi Izumi:
PAMS: Platform for Artificial Market Simulations. CoRR abs/2309.10729 (2023) - [i2]Rawin Assabumrungrat, Kentaro Minami, Masanori Hirano:
Error Analysis of Option Pricing via Deep PDE Solvers: Empirical Study. CoRR abs/2311.07231 (2023) - 2022
- [j3]Masanori Hirano
, Kiyoshi Izumi
, Hiroki Sakaji:
STBM+: Advanced Stochastic Trading Behavior Model for Financial Markets using Residual Blocks or Transformers. New Gener. Comput. 40(1): 7-24 (2022) - [c13]Masanori Hirano, Kiyoshi Izumi, Hiroki Sakaji:
Implementation of Actual Data for Artificial Market Simulation. AAMAS 2022: 1624-1626 - [c12]Masanori Hirano
, Kiyoshi Izumi:
Parameter Tuning Method for Multi-agent Simulation using Reinforcement Learning. BESC 2022: 1-7 - [c11]Masanori Hirano
, Hiroki Sakaji, Kiyoshi Izumi:
Concept and Practice of Artificial Market Data Mining Platform. CIFEr 2022: 1-10 - [c10]Masanori Hirano
, Kiyoshi Izumi:
Quantitative Tuning of Artificial Market Simulation using Generative Adversarial Network. ICA 2022: 12-17 - [c9]Masanori Hirano
, Kiyoshi Izumi:
Efficient Parameter Tuning for Multi-agent Simulation Using Deep Reinforcement Learning. IIAI-AAI-Winter 2022: 130-137 - [c8]Masanori Hirano
, Ryo Wakasugi, Kiyoshi Izumi:
Analysis of Demand Response Scenarios by Industrial Consumers Using Artificial Electric Power Market Simulations. IIAI-AAI 2022: 547-554 - [c7]Masanori Hirano
, Ryo Wakasugi, Kiyoshi Izumi
:
Analysis of Carbon Neutrality Scenarios of Industrial Consumers Using Electric Power Market Simulations. PRIMA 2022: 90-105 - [c6]Masanori Hirano
, Kiyoshi Izumi
:
Does Order Simultaneity Affect the Data Mining Task in Financial Markets? - Effect Analysis of Order Simultaneity Using Artificial Market. PRIMA 2022: 297-313 - [i1]Masanori Hirano
, Hiroki Sakaji, Kiyoshi Izumi:
Policy Gradient Stock GAN for Realistic Discrete Order Data Generation in Financial Markets. CoRR abs/2204.13338 (2022) - 2021
- [c5]Rei Taguchi, Hikaru Watanabe, Masanori Hirano
, Masahiro Suzuki
, Hiroki Sakaji, Kiyoshi Izumi
, Kenji Hiramatsu:
Market Trend Analysis Using Polarity Index Generated from Analyst Reports. IEEE BigData 2021: 3486-3494 - 2020
- [j2]Masanori Hirano
, Kiyoshi Izumi
, Hiroyasu Matsushima
, Hiroki Sakaji:
Comparing Actual and Simulated HFT Traders' Behavior for Agent Design. J. Artif. Soc. Soc. Simul. 23(3) (2020) - [c4]Masanori Hirano
, Hiroyasu Matsushima
, Kiyoshi Izumi, Hiroki Sakaji:
STBM: Stochastic Trading Behavior Model for Financial Markets. JSAI 2020: 157-165 - [c3]Masanori Hirano
, Hiroyasu Matsushima
, Kiyoshi Izumi
, Hiroki Sakaji:
Implementation of Real Data for Financial Market Simulation Using Clustering, Deep Learning, and Artificial Financial Market. PRIMA 2020: 3-18 - [c2]Masanori Hirano
, Hiroyasu Matsushima
, Kiyoshi Izumi
, Taisei Mukai
:
Simulation of Unintentional Collusion Caused by Auto Pricing in Supply Chain Markets. PRIMA 2020: 352-359
2010 – 2019
- 2019
- [j1]Masanori Hirano
, Hiroki Sakaji, Shoko Kimura, Kiyoshi Izumi
, Hiroyasu Matsushima
, Shintaro Nagao, Atsuo Kato:
Related Stocks Selection with Data Collaboration Using Text Mining. Inf. 10(3): 102 (2019) - 2018
- [c1]Masanori Hirano
, Hiroki Sakaji, Shoko Kimura, Kiyoshi Izumi
, Hiroyasu Matsushima
, Shintaro Nagao, Atsuo Kato:
Selection of Related Stocks using Financial Text Mining. ICDM Workshops 2018: 191-198
Coauthor Index
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last updated on 2024-05-31 01:38 CEST by the dblp team
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