Statistical Inference for Financial Engineering

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...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Taniguchi, Masanobu (Συγγραφέας), Amano, Tomoyuki (Συγγραφέας), Ogata, Hiroaki (Συγγραφέας), Taniai, Hiroyuki (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2014.
Σειρά:SpringerBriefs in Statistics,
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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100 1 |a Taniguchi, Masanobu.  |e author. 
245 1 0 |a Statistical Inference for Financial Engineering  |h [electronic resource] /  |c by Masanobu Taniguchi, Tomoyuki Amano, Hiroaki Ogata, Hiroyuki Taniai. 
264 1 |a Cham :  |b Springer International Publishing :  |b Imprint: Springer,  |c 2014. 
300 |a X, 118 p. 15 illus., 6 illus. in color.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |b PDF  |2 rda 
490 1 |a SpringerBriefs in Statistics,  |x 2191-544X 
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 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. 
650 0 |a Statistics. 
650 0 |a Economics, Mathematical. 
650 0 |a Macroeconomics. 
650 1 4 |a Statistics. 
650 2 4 |a Statistics for Business/Economics/Mathematical Finance/Insurance. 
650 2 4 |a Quantitative Finance. 
650 2 4 |a Macroeconomics/Monetary Economics//Financial Economics. 
700 1 |a Amano, Tomoyuki.  |e author. 
700 1 |a Ogata, Hiroaki.  |e author. 
700 1 |a Taniai, Hiroyuki.  |e author. 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer eBooks 
776 0 8 |i Printed edition:  |z 9783319034966 
830 0 |a SpringerBriefs in Statistics,  |x 2191-544X 
856 4 0 |u http://dx.doi.org/10.1007/978-3-319-03497-3  |z Full Text via HEAL-Link 
912 |a ZDB-2-SMA 
950 |a Mathematics and Statistics (Springer-11649)