Hayashi, Takaki

写真a

Affiliation

Graduate School of Business Administration (Hiyoshi)

Position

Professor

External Links

Academic Background 【 Display / hide

  • 2000

    University of Chicago, Department of Statistics

    United States, Graduate School, Completed, Doctoral course

Academic Degrees 【 Display / hide

  • Ph.D., University of Chicago, Coursework, 2000

 

Research Areas 【 Display / hide

  • Informatics / Statistical science (データサイエンス )

  • Humanities & Social Sciences / Business administration (経営管理)

  • Humanities & Social Sciences / Economic statistics (計量ファイナンス)

Research Keywords 【 Display / hide

  • data science

  • time series analysis

  • Business Administration

  • quantitative finance

  • financial engineering

 

Papers 【 Display / hide

  • Strategic liquidity provision in high-frequency trading

    Takaki Hayashi, Katsumasa Nishide

    International Review of Financial Analysis (Elsevier)  93   103168 2024.05

    Joint Work, Accepted

  • A modelling framework for regression with collinearity

    Kariya T., Kurata H., Hayashi T.

    Journal of Statistical Planning and Inference (Journal of Statistical Planning and Inference)  228   95 - 115 2024.01

    Accepted,  ISSN  03783758

     View Summary

    This study addresses a fundamental, yet overlooked, gap between standard theory and empirical modelling practices in the OLS regression model y=Xβ+u with collinearity. In fact, while an estimated model in practice is desired to have stability and efficiency in its “individual OLS estimates”, y itself has no capacity to identify and control the collinearity in X and hence no theory including model selection process (MSP) would fill this gap unless X is controlled in view of sampling theory. In this paper, first introducing a new concept of “empirically effective modelling” (EEM), we propose our EEM methodology (EEM-M) as an integrated process of two MSPs with data (yo,X) given. The first MSP uses X only, called the XMSP, and pre-selects a class D of models with individually inefficiency-controlled and collinearity-controlled OLS estimates, where the corresponding two controlling variables are chosen from predictive standard error of each estimate. Next, defining an inefficiency-collinearity risk index for each model, a partial ordering is introduced onto the set of models to compare without using yo, where the better-ness and admissibility of models are discussed. The second MSP is a commonly used MSP that uses (yo,X), and evaluates total model performance as a whole by such AIC, BIC, etc. to select an optimal model from D. Third, to materialize the XMSP, two algorithms are proposed with applications.

  • On the evaluation of intraday market quality in the limit-order book markets: a collaborative filtering approach

    Takaki Hayashi, Makoto Takahashi

    Japanese Journal of Statistics and Data Science 4 ( 1 ) 697 - 730 2021.05

    Research paper (scientific journal), Joint Work, Accepted

  • Exploring the Effects of Internet Memes in Social Media Marketing through A/B Testing

    Yang X., Hayashi T.

    Proceedings - 2021 IEEE 23rd Conference on Business Informatics, CBI 2021 - Main Papers (Proceedings - 2021 IEEE 23rd Conference on Business Informatics, CBI 2021 - Main Papers)  2   97 - 106 2021

     View Summary

    This study is concerned with the'Internet meme', an image with a brief message attached to a Social Network Service (SNS) post expressing one's mood humorously. Internet memes have become popular especially among young users recently. Meme marketing, one of the growing corporate strategies designed for more effective online brand communication, has been evolving in environments where younger generations have become the most active individuals and constitute the majority of the virtual Internet society of today. The purpose of this study is to quantify the effects of Internet memes in the context of social media marketing on SNS platforms. A/B testing is conducted with dozens of post experiments on an SNS platform that has the most users in China to test the effect of Internet memes by measuring the post engagement rates. Further, a statistical analysis using generalized linear mixed models is conducted for exploring the characteristics of users who tend to react to Internet memes. Practical implications for SNS marketing are also drawn.

  • Quantification of Abrupt Driving Maneuver Utilizing ETC 2.0 Probe Data: A Case Study in Japan

    Matsushita H., Hayashi T.

    8th International Conference on Logistics, Informatics and Service Sciences, LISS 2018 - Proceeding (8th International Conference on Logistics, Informatics and Service Sciences, LISS 2018 - Proceeding)   2018.12

     View Summary

    As of the end of October 2017, the utilization of ETC 2.0 in Japan is about 15%, which is growing at a faster rate than its predecessor ETC1.0. ETC 2.0 probe data is designed to store new data fields, or features, such as position information history of the vehicle and abrupt driving maneuver history. Up to the present, the use of these data has not been well spreading, and the government of Japan supports the utilization of ETC 2.0 by the administrative and private enterprises. In this study, we aim to explore a new, effective use of ETC 2.0 probe data. The probe data is sizable, accumulating about 400 GB for one month. Analysis is conducted focusing on the number of abrupt driving maneuver in ten most popular tourist areas in the Greater Tokyo Area ('Kanto region') from April 2015 to March 2016. Using the ETC 2.0 probe data, we propose a methodology to quantify abrupt driving maneuver of individual drivers and to evaluate their driving behaviors with a view towards business applications in mind.

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Papers, etc., Registered in KOARA 【 Display / hide

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Presentations 【 Display / hide

Research Projects of Competitive Funds, etc. 【 Display / hide

  • 回帰モデルにおける重共線性分析と変数・モデル選択法

    2021.04
    -
    Present

    基盤研究(C), No Setting, Coinvestigator(s)

  • 確率微分方程式モデルに基づく数理・データ科学とシミュレーション科学の融合的研究

    2017.04
    -
    2022.03

    基盤研究(A), Research grant, Coinvestigator(s)

  • 高頻度注文板データを用いた高速での株価形成に関する統計解析

    2016.04
    -
    2019.03

    MEXT,JSPS, Grant-in-Aid for Scientific Research, Grant-in-Aid for Scientific Research (C), Principal investigator

  • インターネットにおける口コミ効果の国際比較

    2015.04
    -
    2016.03

    基盤研究(B), Coinvestigator(s)

  • 超高頻度データとリー ド・ラグ

    2014.04
    -
    2017.03

    挑戦的萌芽研究, Research grant, No Setting

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Courses Taught 【 Display / hide

  • MANAGEMENT SCIENCE

    2023

  • BUSINESS STATISTICS

    2023, Postgraduate, Lecture

  • DATA SCIENCE

    2023, Postgraduate, Lecture

  • テキストデータ分析

    2023, Spring Semester, Postgraduate, Lecture

  • Business and Data Analytics

    2023, Autumn Semester, Postgraduate, Lecture

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Courses Previously Taught 【 Display / hide

  • 金融時系列解析

    東京都立大学大学院ファイナンスプログラム

    2016.10
    -
    Present

    Autumn Semester, Lecture

  • 金融データサイエンス

    東京都立大学大学院ファイナンスプログラム

    2016.04
    -
    Present

    Spring Semester, Postgraduate, Lecture

  • 決定分析

    慶應義塾大学

    2011.01
    -
    2013.03

    Autumn Semester, Postgraduate, Lecture, Within own faculty

  • Management of Japanese Firms VI

    慶應義塾大学

    2011.01
    -
    2013.03

    Autumn Semester, Postgraduate, Lecture, Within own faculty

  • アクチュアリー統計セミナーII

    東京大学大学院数理科学研究科

    2006
    -
    2008

    Postgraduate, Lecture

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Academic Activities 【 Display / hide

  • 統計数理研究所 数学協働プログラム・金融作業グループ報告書

    統計数理研究所 数学協働プログラム・金融作業グループ, 

    2016.04
    -
    2017.03

  • JST/CRDS「社会動向予測モデル検討会」

    独立行政法人科学技術振興機構(JST)・研究開発戦略センター(CRDS)・システム科学ユニット, 

    2012

  • JST/CRDS「システム科学技術俯瞰検討会」「意思決定とリスク・マネジメント分科会」

    独立行政法人科学技術振興機構(JST)・研究開発戦略センター(CRDS)・システム科学ユニット, 

    2011
    -
    2012

Committee Experiences 【 Display / hide

  • 2006
    -
    Present

    理事, Japanese Association of Financial Econometrics and Engineering