Statistical Portfolio Estimation

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

Buch | Softcover

388 Seiten

2021
Chapman & Hall/CRC (Verlag)
978-1-032-09649-0 (ISBN)

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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.

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.

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.

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

Erscheinungsdatum	01.07.2021
Zusatzinfo	66 Illustrations, black and white
Sprache	englisch
Maße	178 x 254 mm
Gewicht	684 g
Themenwelt	Mathematik / Informatik ► Mathematik ► Angewandte Mathematik
	Mathematik / Informatik ► Mathematik ► Statistik
	Naturwissenschaften ► Biologie
	Wirtschaft ► Volkswirtschaftslehre ► Ökonometrie
ISBN-10	1-032-09649-7 / 1032096497
ISBN-13	978-1-032-09649-0 / 9781032096490
Zustand	Neuware