Machine Learning in Finance Japan

This training course will provide delegates with an in-depth, technical understanding of machine learning applications, models, and more advanced tools and solutions through a quantitative approach.

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Machine Learning in Finance

4-5 September 2019
Tokyo

 

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This training course will provide delegates with an in-depth, technical understanding of machine learning applications, models, and more advanced tools and solutions through a quantitative approach.
 

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Hiroyasu Hirayama

Director

AI Finance Application Research Institute

Prior to the current role, Hiroyasu was head of FX derivatives sales at Deutsche Bank, BNP Paribas, RBS

and Bank of New York Mellon most recently. He holds a bachelor degree in engineering from University of Tokyo and a master degree from Tsukuba University.

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Daigo Honda

group manager

Linea Co., Ltd

Daigo Honda is the manager of the Mathematical Engineering Group in Linea Co., Ltd., where he has been responsible for the products utilizing financial engineering and machine learning. Since he joined the company in 2014, he developed and managed solutions in the following fields: pricing and risk measurement of derivatives and structured products, credit risk modeling utilizing machine learning, behavioral option modeling of core deposits and loan prepayment, etc. He holds a Ph.D. in Theoretical Physics from the University of Tokyo.

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Fumio Ishizaki

chief researcher

AI Finance Application Research Institute

Fumio Ishizaki is the Chief Researcher for AI Finance Application Research Institute. He worked at universities for more than twenty years. He has published papers in the area of applied probability, communication networks and so on. He received Dr. Eng. from Kyoto University.

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Shunsuke Ohkoda

chief engineer

Linea Co., Ltd.

Shunsuke Ohkoda is the Chief Engineer for Linea. Co., Ltd. He has engaged in application development using financial engineering, and AI projects in finance since he joined the company in 2015. Recently he has been responsible for research and development of earnings forecast modeling and economic network analysis with machine learning and AI.

He holds a Doctor’s Degree in theoretical physics from the University of Osaka.

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Yutaka Sakurai

Head

AI Finance Application Research Institute

Yutaka Sakurai is data science and AI expert with a strong background in Financial theory and practice. After more than twenty years' experience of fund manager, trader and quant in Bank of Tokyo-Mitsubishi and Sony Bank, he became a managing director of Research and Pricing Technology Inc.  in 2010. He started AI Finance Application Research Institute in 2017. He published a number of books on Finance and AI.

Makoto Shibata

Head of FINOLAB/Chief Community Officer and Audit & Supervisory Board Member, UI Bank Co., Ltd

FINOLAB

Mr. Shibata is currently in charge of FINOLAB community operation since 2019. In his former position at The Bank of Tokyo-Mitsubishi UFJ, he was leading R&D initiatives in emerging technology and online/mobile financial service. He also held positions in corporate planning, accounting, corporate finance and retail customer services at the bank. He is one of the founders of FINOVATORS. And became an external board member at new digital bank, UI Bank, when it acquired a banking license in 2021. He holds a Bachelor of Economics from University of Tokyo and a Master of Science in Development Economics from University of Oxford.

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Training
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Networking
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Group Discussion
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Learning Outcomes
  • Best practice approaches to machine learning applications in finance from a quantitative viewpoint
  • The capabilities of machine learning tools in portfolio construction, trading, risk management and beyond
  • Insight into the big data revolution and the building blocks of machine learning tools in finance  
  • The theory behind machine learning, deep learning and neural networks, and how these methods can be applied in your organization
  • A clear view of ML/AI capabilities, how they can help you solve problems more effectively and drive your business forward
  • Get to grips with modern data analysis, structured and unstructured data and new models
     
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Who Should Attend?

This workshop is specifically designed for professionals working for financial institutions, buy-side firms, regulatory bodies, advisory firms and technology sector however Risk Training welcomes anyone who would benefit from this training.

Specific job titles may include but are not limited to:

  • Machine learning
  • Portfolio management
  • Asset allocation
  • Data science
  • Financial engineering
  • Quantitative analytics
  • Quantitative modelling
  • Innovation
  • Forecasting
  • Infrastructure and technology
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Course Highlights
  • In-depth understanding of machine learning applications
  • How to apply artificial intelligence and data analytics in financial market
  • Understanding fundamentals of machine learning methodology
  • Learn the theory behind machine learning, deep learning and neural networks
  • Gain insights into the latest and most widely used industry applications
  • Get a clear view of ML/AI capabilities in finance to drive your business forward

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Annie Wu

Senior Conference Producer