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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...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , , , |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Cham :
Springer International Publishing : Imprint: Springer,
2014.
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| Edición: | 1st ed. 2014. |
| Colección: | SpringerBriefs in Statistics,
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| Temas: | |
| Acceso en línea: | Texto Completo |
MARC
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| 001 | 978-3-319-03497-3 | ||
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| 005 | 20220112143457.0 | ||
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| 008 | 140326s2014 sz | s |||| 0|eng d | ||
| 020 | |a 9783319034973 |9 978-3-319-03497-3 | ||
| 024 | 7 | |a 10.1007/978-3-319-03497-3 |2 doi | |
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| 100 | 1 | |a Taniguchi, Masanobu. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a Statistical Inference for Financial Engineering |h [electronic resource] / |c by Masanobu Taniguchi, Tomoyuki Amano, Hiroaki Ogata, Hiroyuki Taniai. |
| 250 | |a 1st ed. 2014. | ||
| 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 | ||
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| 490 | 1 | |a SpringerBriefs in Statistics, |x 2191-5458 | |
| 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 Social sciences-Mathematics. | |
| 650 | 0 | |a Macroeconomics. | |
| 650 | 1 | 4 | |a Statistics in Business, Management, Economics, Finance, Insurance. |
| 650 | 2 | 4 | |a Mathematics in Business, Economics and Finance. |
| 650 | 2 | 4 | |a Macroeconomics and Monetary Economics. |
| 700 | 1 | |a Amano, Tomoyuki. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 700 | 1 | |a Ogata, Hiroaki. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 700 | 1 | |a Taniai, Hiroyuki. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
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| 773 | 0 | |t Springer Nature eBook | |
| 776 | 0 | 8 | |i Printed edition: |z 9783319034980 |
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| 950 | |a Mathematics and Statistics (SpringerNature-11649) | ||
| 950 | |a Mathematics and Statistics (R0) (SpringerNature-43713) | ||