Name: Machine Learning in Finance Japan
Start: 2019-09-04T08:00:00+01:00
End: 2019-09-05T17:30:00+01:00
Location: Finolab

Speakers

Hiroyasu Hirayama

CEO

P05 technologies, Inc.

Hiroyasu Hirayama, CEO, P05 Technologies, Inc.

Hiroyasu works as a CEO for P05 Technologies, Inc. After having worked as head of FX at Deutsche Bank, BNP Paribas, RBS and RBC., he set up Subak Technologies Inc., where he developed credit scoring models based on machine learning algorithms.

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.

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.

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.

Yutaka Sakurai

Director-general

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

FINOLAB

Mr. Shibata is currently in charge of FINOLAB community operation. 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 Executive Fellow at Japan Digital Design. He holds a Bachelor of Economics from University of Tokyo and a Master of Science in Development Economics from University of Oxford.

Training

Networking

Group Discussion

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

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

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

Companies who trust us with their Risk Management Training

HSBC Global Markets offer sophisticated 24-hour coverage across our main trading and sales platforms in London, New York and Hong Kong, and we provide a wide range of solutions for our Corporate and Institutional clients. Our knowledge of local markets, coupled with HSBC's global reach, enables us to provide a comprehensive and bespoke service across every major asset class.
We provide access to Equities, Fixed Income including Credit and Rates, Foreign Exchange, Commodities and Prime Services, in addition to Research, across both developed and emerging markets.
As a global investor, by partnering with us you'll benefit from HSBC's local knowledge in over 60 countries, balanced by our understanding of global economics.
Find out more about our solutions or explore our thought leadership series on the Dealing Room of Tomorrow.