Statistical inference for financial engineering / Masanobu Taniguchi, Tomoyuki Amano, Hiroaki Ogata, Hiroyuki Taniai.

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...

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Bibliographic Details
Online Access: Full Text (via Springer)
Main Authors: Taniguchi, Masanobu (Author), Amano, Tomoyuki (Author), Ogata, Hiroaki (Author), Taniai, Hiroyuki (Author)
Format: eBook
Language:English
Published: Cham : Springer, [2014]
Series:SpringerBriefs in statistics.
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MARC

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505 0 |a Preface -- Features of Financial Data -- Empirical Likelihood Approaches for Financial Returns -- Various Methods for Financial Engineering -- Some Techniques for ARCH Financial Time Series -- Index. 
520 |a 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 et cetera 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 et cetera, 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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