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Graduate School of Economics and Management, Tohoku University

 
                                          

2023 Hosoya Prize

    July 6, 2023   

    The recipients of the 5th Hosoya Prize

    Yoshimasa Uematsu (Hitotsubashi University)
    Uematsu, Y. and T. Yamagata (2023). "Estimation of sparsity-induced weak factor models," Journal of Business & Economic Statistics, 41, 213-227.

    Review comments:
    Dr. Uematsu proposed sparsity-induced weak factor models with efficient estimation. The weakness of factor models is defined by the divergence order of eigenvalues for covariance matrices. Weak factor models assume the order is less than or equal to the dimension N, which is regarded as an extension from traditional factor models whose order is always equal to N. Dr. Uematsu employed SOFAR estimation for such weak factor models and established asymptotic/non-asymptotic validations for it. In the empirical analysis, he applied weak factor models to financial time series to demonstrate interesting interpretations for the factor loading matrix, which is usually not available in traditional factor models, to identify weak factors in Fama-French five factor models and to discuss weakness of factors for stock returns. The extension from strong to weak factor models is regarded as essential contributions accounting for several interesting features in financial time series analysis, and suits Hosoya Prize to promote data science research in social sciences.

    Yasumasa Matsuda (chair, Tohoku Univ.)
    Kosuke Oya (Osaka Univ.)
    Mototsugu Shintani (Univ. Tokyo)
    Nobuhiko Terui (Tokyo Univ. of Science)
    Peter M. Robinson (London School of Economics and Political Science)


    Brief history of Dr. Uematsu
    BA in Economics, Hitotsubashi University, March 2007
    PhD in Economics, Hitotsubashi University, September 2013
    Associate professor at Dept. data Science, Hitotsubashi University, April 2022 -

    The 5th Hosoya prize lecture by the recipient will be held on November 2nd, 2023 at Tohoku Univ.