長倉 大輔 (ナガクラ ダイスケ)

Nagakura Daisuke

写真a

所属(所属キャンパス)

経済学部 (三田)

職名

教授

HP

教員からのメッセージ 【 表示 / 非表示

  • 私の研究分野は計量経済学(Econometrics)、金融計量経済学(Financial Econometrics)、時系列分析(Time Series Analysis)です。

経歴 【 表示 / 非表示

  • 2016年04月
    -
    継続中

    慶應義塾大学経済学部, 教授

  • 2011年04月
    -
    2016年03月

    慶應義塾大学経済学部, 准教授

  • 2010年04月
    -
    2011年03月

    早稲田大学大学院ファイナンス研究科, 助教

  • 2007年09月
    -
    2010年03月

    日本銀行金融研究所

学歴 【 表示 / 非表示

  • 2007年08月

    University of Washington, 経済学部

    アメリカ合衆国, 大学院, 修了, 博士

  • 2001年03月

    横浜国立大学, 国際社会科学研究科

    大学院, 修了, 修士

  • 1999年03月

    横浜国立大学, 経済学部

    大学, 卒業

学位 【 表示 / 非表示

  • 博士(経済学), University of Washington, 課程, 2007年08月

 

論文 【 表示 / 非表示

  • Testing for Random Coefficient Autoregressive and Stochastic Unit Root Models

    Daisuke Nagakura

    Studies in Nonlinear Dynamics and Econometrics 2021年

    研究論文(学術雑誌), 単著, 査読有り

  • Computing exact score vectors for linear Gaussian state space models

    Nagakura Daisuke

    Communications in Statistics - Simulation and Computation  forthcoming 2021年

    研究論文(学術雑誌), 単著, 査読有り,  ISSN  03610918

     概要を見る

    © 2019, © 2019 Taylor & Francis Group, LLC. A recursive formula for computing the exact value of score vectors is proposed for a general form of the linear Gaussian state space model, which is more desirable than approximate values in some statistical analyses. Unlike most extant methods, our formula calculates all components of the score vector simultaneously. This approach significantly simplifies its programing, in particular, with some matrix-oriented programing languages, such as MATLAB. We also consider a way of handling initial conditions that depend on unknown parameters. This issue has not yet been explicitly addressed in the existing literature in the context of exact score computing for a general case, such as the one that we consider in this paper. It is also shown that our formula is especially useful for calculating score tests with an outer product of gradient asymptotic covariance matrix estimator.

  • Further Results on the vecd Operator and Its Applications

    Daisuke Nagakura

    Communications in Statistics, Theory and Methods  49 ( 10 ) 2321 - 2338 2020年

    研究論文(学術雑誌), 単著, 査読有り,  ISSN  03610926

     概要を見る

    © 2019, © 2019 Taylor & Francis Group, LLC. In this paper, we consider the matrix vectorization operator termed the vecd operator, which has recently been introduced in the literature. This operator stacks up distinct elements of a symmetric matrix in a way that differs from that of the well-known vech operator; it stacks up not columns, but diagonals. We give further consideration to the vecd operator and related matrices, and derive their various useful properties. We provide some statistical applications of the vecd operator to illustrate its usefulness.

  • On the Relationship between the Matrix Operators, vech and vecd

    Daisuke Nagakura

    Communications in Statistics, Theory and Method 47 ( 13 ) 3252 - 3268 2018年

    研究論文(学術雑誌), 単著, 査読有り,  ISSN  03610926

     概要を見る

    © 2018 Taylor & Francis Group, LLC. We introduce a matrix operator, which we call “vecd” operator. This operator stacks up “diagonals” of a symmetric matrix. This operator is more convenient for some statistical analyses than the commonly used “vech” operator. We show an explicit relationship between the vecd and vech operators. Using this relationship, various properties of the vecd operator are derived. As applications of the vecd operator, we derive concise and explicit expressions of the Wald and score tests for equal variances of a multivariate normal distribution and for the diagonality of variance coefficient matrices in a multivariate generalized autoregressive conditional heteroscedastic (GARCH) model, respectively.

  • A State Space Approach to Estimating the Integrated Variance under the Existence of Market Microstructure Noise

    Daisuke Nagakura (with Toshiaki Watanabe)

    Journal of Financial Econometrics 13 ( 1 ) 45 - 82 2015年

    研究論文(学術雑誌), 共著, 査読有り,  ISSN  14798409

     概要を見る

    © The Author, 2013. This article develops a state space method for estimating the integrated variance under the existence of market microstructure noise (MMN). Our method is based on a state space representation of the noisecontaminated RV (NCRV), namely, the realized variance (RV) calculated with observed prices contaminated by MMNs. The main idea of our method is to filter out the bias component, which we call the microstructure noise (MN) component, from the NCRV using the Kalman filter. We apply the proposed method to yen/dollar exchange rate data.We find that about half of the variation in NCRV is because of the MN component. The proposed method can serve as a convenient way to estimate a general class of continuous-time stochastic volatility models under the existence of MMN.

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KOARA(リポジトリ)収録論文等 【 表示 / 非表示

研究発表 【 表示 / 非表示

  • 詳細は http://user.keio.ac.jp/~nagakura/jcv.html をご覧ください

    2000年01月

    口頭発表(一般)

 

担当授業科目 【 表示 / 非表示

  • 時系列分析

    2022年度

  • 計量経済学演習

    2022年度

  • 研究会d

    2022年度

  • 研究会c

    2022年度

  • 研究会b

    2022年度

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