Kenichiro Tamaki

Second‐order properties of locally stationary processes

In this article, we investigate an optimal property of the maximum likelihood estimator of Gaussian locally stationary processes by the second-order approximation. In the case where the model is correctly specified, it is shown that appropriate modifications of the maximum likelihood estimator for Gaussian locally stationary processes is second-order asymptotically efficient. We also discuss second-order robustness properties. Copyright 2009 The Author. Journal compilation 2009 Blackwell Publishing Ltd

Statistical Estimation of Portfolios for Dependent Financial Returns

1 Department of Applied Mathematics, Waseda University, Tokyo 169-8555, Japan 2 Department of Statistics/Graduate Institute of Statistics & Actuarial Science, Feng Chia University Taichung 407, Taiwan 3 Department of Mathematics, Faculty of Science, Niigata University, Niigata 950-2181, Japan 4 The Jikei University School of Medicine, Tokyo 105-8461, Japan 5 ECARES-Solvay Brussels School of Economics and Management, Universite Libre de Bruxelles, 1050 Brussels, Belgium