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Statistical Analysis of Financial Data

Statistical Analysis of Financial Data : With Examples in R. 金融データの統計分析

・ISBN 978-1-138-59949-9 2020 hard GB£ 145.99

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・ISBN 978-1-032-17346-7 2021 paper GB£ 54.99

¥17,420.- (税込) (※)価格はご注文時の参考価格となります。
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電子版あり 大学・学術機関向け電子ブック(eBook)ISBN 9780429485602
著者・編者Gentle, James,
シリーズChapman & Hall/CRC Texts in Statistical Science Series
出版社(Chapman & Hall / CRC, US)
ページ数666 pp.
言語ENG
ニュース番号<656-262 656-364>

解説

Statistical Analysis of Financial Data covers the use of statistical analysis and the methods of data science to model and analyze financial data. The first chapter is an overview of financial markets, describing the market operations and using exploratory data analysis to illustrate the nature of financial data. The software used to obtain the data for the examples in the first chapter and for all computations and to produce the graphs is R. However discussion of R is deferred to an appendix to the first chapter, where the basics of R, especially those most relevant in financial applications, are presented and illustrated. The appendix also describes how to use R to obtain current financial data from the internet.

Chapter 2 describes the methods of exploratory data analysis, especially graphical methods, and illustrates them on real financial data. Chapter 3 covers probability distributions useful in financial analysis, especially heavy-tailed distributions, and describes methods of computer simulation of financial data. Chapter 4 covers basic methods of statistical inference, especially the use of linear models in analysis, and Chapter 5 describes methods of time series with special emphasis on models and methods applicable to analysis of financial data.

Features

* Covers statistical methods for analyzing models appropriate for financial data, especially models with outliers or heavy-tailed distributions.

* Describes both the basics of R and advanced techniques useful in financial data analysis.

* Driven by real, current financial data, not just stale data deposited on some static website.

* Includes a large number of exercises, many requiring the use of open-source software to acquire real financial data from the internet and to analyze it.