This book provides a comprehensive overview of statistical inference for portfolios and their various applications. A variety of asset processes are introduced, including non-Gaussian stationary processes, nonlinear processes, nonstationary processes, and the book provides a framework for statistical inference using local asymptotic normality.
This book provides a comprehensive overview of statistical inference for portfolios and their various applications. A variety of asset processes are introduced, including non-Gaussian stationary processes, nonlinear processes, nonstationary processes, and the book provides a framework for statistical inference using local asymptotic normality.
Masanobu Taniguchi is a research professor in the Department of Applied Mathematics at Waseda University, Japan. Hiroshi Shiraishi is a lecturer in the Laboratory of Mathematics, Jikei University School of Medicine, Japan. Junichi Hirukawa is an associate professor in the Faculty of Science at Niigata University, Japan. Hiroko Solvang Kato is a researcher and project leader in the Department of Genetics, Institute for Cancer Research, Oslo University Hospital, Norway.
Inhaltsangabe
Introduction Preliminaries Portfolio Theory for Dependent Return Processes Multiperiod Problem for Portfolio Theory Portfolio Estimation based on Rank Statistics Portfolio Estimation Influence by Non-Gaussian Innovatin and Exogenous Variables Numerical Examples Theoretical Foundations and Technicalities
Introduction Preliminaries Portfolio Theory for Dependent Return Processes Multiperiod Problem for Portfolio Theory Portfolio Estimation based on Rank Statistics Portfolio Estimation Influence by Non-Gaussian Innovatin and Exogenous Variables Numerical Examples Theoretical Foundations and Technicalities
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