Statistical Portfolio Estimation

Masanobu Taniguchi, Hiroshi Shiraishi, Junichi Hirukawa, Hiroko Kato Solvang, Takashi Yamashita

August 21, 2017 by Chapman and Hall/CRC
Reference - 378 Pages - 66 B/W Illustrations
ISBN 9781466505605 - CAT# K14575


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    • Provides an overview of the theory and applications of statistical portfolio estimation
    • Includes necessary background material in stochastic processes and limit theorems
    • Covers dependent return processes, multiperiod problems, estimation based on rank statistics, and non-Gaussian processes
    • Includes illustrative examples throughout, and a chapter of detailed worked examples
    • Theoretical details and technical points are included in a final chapter so as not to disrupt the flow of the text


The composition of portfolios is one of the most fundamental and important methods in financial engineering, used to control the risk of investments. 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, non-stationary processes, and the book provides a framework for statistical inference using local asymptotic normality (LAN). The approach is generalized for portfolio estimation, so that many important problems can be covered.

This book can primarily be used as a reference by researchers from statistics, mathematics, finance, econometrics, and genomics. It can also be used as a textbook by senior undergraduate and graduate students in these fields.


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