Titlebook: Statistical Inference for Financial Engineering; Masanobu Taniguchi,Tomoyuki Amano,Hiroyuki Taniai Book 2014 The Author(s) 2014 62P05, 91G

BROOD

书目名称Statistical Inference for Financial Engineering影响因子(影响力)




书目名称Statistical Inference for Financial Engineering影响因子(影响力)学科排名




书目名称Statistical Inference for Financial Engineering网络公开度




书目名称Statistical Inference for Financial Engineering网络公开度学科排名




书目名称Statistical Inference for Financial Engineering被引频次




书目名称Statistical Inference for Financial Engineering被引频次学科排名




书目名称Statistical Inference for Financial Engineering年度引用




书目名称Statistical Inference for Financial Engineering年度引用学科排名




书目名称Statistical Inference for Financial Engineering读者反馈




书目名称Statistical Inference for Financial Engineering读者反馈学科排名

大骂

Empirical Likelihood Approaches for Financial Returns,pirical likelihood such as Cressie-Read power-divergence statistic and generalized empirical likelihood. Section . considers application of the generalized empirical likelihood to an inference problem for multivariate stable distributions. Technical proofs of the theorems are given in Sect. ..

adipose-tissue

Features of Financial Data,Their estimation theory is provided in a unified fashion. Optimality of the estimation and testing, etc., is described based on the local asymptotic normality (LAN) due to Le Cam. The theory and models are very general and modern.

laxative

Some Techniques for ARCH Financial Time Series,ditional variance, or “volatility” of financial assets. Revealing the fact that its inference can be greatly affected by the existence of additional noize called market microstructure, we introduce and study the asymptotics of some appropriate estimator under the microstructure with ARCH-dependent structure.

话

Features of Financial Data,s obviously complicated, modeling for financial time series is difficult. For this, first, we look at some empirical characteristics of financial data. Then, we review and examine various time series models (e.g., ARCH, general linear process, non-stationary process, etc.), which show plausibility.

阉割

Empirical Likelihood Approaches for Financial Returns,al inference. It allows us to use likelihood methods although we do not assume that the data comes from a known family. Consequently, the empirical likelihood has both effectiveness and flexibility of the likelihood method, and reliability of the nonparametric methods. The construction of this chapt

文字

欢腾

angina-pectoris

Book 2014financial time series data. In order to describe the actual financial data, various stochastic processes, e.g. non-Gaussian linear processes, non-linear processes, long-memory processes, locally stationary processes etc. are introduced and their optimal estimation is considered as well. This book al

JOT