Researcher Database

（Last updated : 2021-05-27 07:53:49）

Hanamura Shinya

Department / Course Graduate School of Management

Title / Position Professor

Academic background
1.	2016/03 Degree Acquisition	│ Waseda University Graduate School of Businesss Ph.d.(Business and Commerce)
2.	2006/03 Degree Acquisition	│ Waseda University Graduate of Finance and Business M.A
3.	～2002/06	Master of Business Administration │ Duke Fuqua School of Business
4.	～2006/03	Master Course │ Finance │ Finance │ Waseda University │ Completed
5.	～2011/02	Doctoral Program (2nd Semester) │ Business and Commerce │ Business and Commerce │ Waseda University │ Completed
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Business career
1.	2016/09/01	│ │ Preferred Networks Co.,ltd. 取締役
2.	2000/04/01 ～ 2016/03/31	│ │ Mizuho Security Company Ltd.
3.	1983/04/01 ～ 2000/03/31	│ │ The Industrial Bank of Japan

Research activities
1.		Societies for the economic studies of securities
2.		Japan Association for Applied Economics
3.		Japan Accounting Association

Subject of research
1.	The design of management incentive system based upon continuous time contract theory
2.	The empirical analysis of value relevance between accounting information and stock price through deep learning analysis
3.	Theoretical analysis of goodwill depreciation and impairment

Research summary
1.Theoretical analysis of goodwill depreciation and impairment, and the real effect of conservatism accounting 2.The design of management incentive system based upon continuous time contract theory 3.The empirical analysis of value relevance between accounting information and stock price through deep learning analysis 1.Theoretical analysis of goodwill depreciation and impairment, and the real effect of conservatism accounting The analysis analytically examines whether a company should depreciate goodwill or adopt non-deprecia- tion accounting. It may be concluded that, from the viewpoint of company value maximization and management utility maximization, both shareholder and management are able to maximize their utility simultaneously by using a relative benefit rule as the amortization schedule. On the other hand, if a company does not depreciate goodwill periodically, neither shareholder nor management can maximize their utility. In this situation, when the probability of impairment is high, management will make efforts even if shareholders decrease their bonus payments, and when the probability of impairment is low, management will not make efforts unless shareholders raise their bonus payments. This implies that impairment can be the incentive for management effort. 2.The design of management incentive system based upon continuous time contract theory This research studies a principal–agent setting in which both sides learn about future profitability from output, and the project can be abandoned/terminated if profitability is too low. With learning, shirking by the agent both reduces output and lowers the principal’s estimate of future profitability. The agent can exploit this belief discrepancy and earn information rents, reducing his incentives to exert effort. The optimal contract controls information rents to improve incentives by distorting the termination decision. The research will try to capture the management incentive system which optimize both shareholder and management. The model will rely on continuous timing of stock price and management behavior. Therefore, it is needed to solve stochastic differential equation upon incentive constraint. 3.The empirical analysis of value relevance between accounting information and stock price through machine learning and deep learning analysis The models to evaluate enterprise and predict stock price which many stock analysts use mainly focus on the single company or single sector by having scrutiny investigations. However, since we can get a lot of information about all companies accounting information, we can evaluate companies value and predict stock price cross-sectionally and numerically. In this research, Evaluating enterprise value and stock prediction are done by some machine learning techniques, such as ensemble model and LSTM, one of the deep learning methods. From the experiments, we try to analyze that the proposed model can predict feature’s stock price more accurately and have the possibility to combine other prediction methods to improve the accuracy.

Present specialized field
Economic theory, Money/Finance, Accounting (Keyword：Disclosure of accounting information and its real effect)

Papers
1.	2009/03	Bidder and Target Valuation: Evidence against the Misvaluation-Driven Takeovers of M&As in Japan │ The Waseda Business & Economic Studies │ No.45,pp.: pp.99-118 (Sole-authored)