Statistical Inference for Financial Engineering

Business & Finance, Economics, Statistics, Nonfiction, Science & Nature, Mathematics, Applied
Cover of the book Statistical Inference for Financial Engineering by Masanobu Taniguchi, Tomoyuki Amano, Hiroaki Ogata, Hiroyuki Taniai, Springer International Publishing
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Author: Masanobu Taniguchi, Tomoyuki Amano, Hiroaki Ogata, Hiroyuki Taniai ISBN: 9783319034973
Publisher: Springer International Publishing Publication: March 26, 2014
Imprint: Springer Language: English
Author: Masanobu Taniguchi, Tomoyuki Amano, Hiroaki Ogata, Hiroyuki Taniai
ISBN: 9783319034973
Publisher: Springer International Publishing
Publication: March 26, 2014
Imprint: Springer
Language: English

​This monograph provides the fundamentals of statistical inference for financial engineering and covers some selected methods suitable for analyzing financial 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 also includes several statistical approaches, e.g., discriminant analysis, the empirical likelihood method, control variate method, quantile regression, realized volatility etc., which have been recently developed and are considered to be powerful tools for analyzing the financial data, establishing a new bridge between time series and financial engineering.

This book is well suited as a professional reference book on finance, statistics and statistical financial engineering. Readers are expected to have an undergraduate-level knowledge of statistics.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

​This monograph provides the fundamentals of statistical inference for financial engineering and covers some selected methods suitable for analyzing financial 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 also includes several statistical approaches, e.g., discriminant analysis, the empirical likelihood method, control variate method, quantile regression, realized volatility etc., which have been recently developed and are considered to be powerful tools for analyzing the financial data, establishing a new bridge between time series and financial engineering.

This book is well suited as a professional reference book on finance, statistics and statistical financial engineering. Readers are expected to have an undergraduate-level knowledge of statistics.

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