Statistical Portfolio Estimation
Sep 2017 · CRC Press
I-Ebook
388
Amakhasi
family_home
Kufanelekile
info
reportIzilinganiso nezibuyekezo aziqinisekisiwe Funda Kabanzi
Mayelana nale ebook
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.
Mayelana nomlobi
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.
Nikeza le ebook isilinganiso
Sitshele ukuthi ucabangani.
Ulwazi lokufunda
Amasmathifoni namathebulethi
Faka uhlelo lokusebenza lwe-Google Play Amabhuku lwe-Android ne-iPad/iPhone. Livunyelaniswa ngokuzenzakalela ne-akhawunti yakho liphinde likuvumele ukuthi ufunde uxhunywe ku-inthanethi noma ungaxhunyiwe noma ngabe ukuphi.
Amakhompyutha aphathekayo namakhompyutha
Ungalalela ama-audiobook athengwe ku-Google Play usebenzisa isiphequluli sewebhu sekhompuyutha yakho.
Ama-eReaders namanye amadivayisi
Ukuze ufunde kumadivayisi e-e-ink afana ne-Kobo eReaders, uzodinga ukudawuniloda ifayela futhi ulidlulisele kudivayisi yakho. Landela imiyalelo Yesikhungo Sosizo eningiliziwe ukuze udlulise amafayela kuma-eReader asekelwayo.
