研究者詳細 - 長倉　大輔

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.
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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.
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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.
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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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