000			03831nam a2200325 i 4500
003			CSPC
005			20231213174001.0
008			231204s2020 flua b 001 0 eng
020			_a9781032173467
040			_cCSPC _aCSPC _beng
050	0	0	_aHG106 _b.G466 2020
082	0	4	_a332.0151955 _bG289s _223
100	1		_aGentle, James E., _d1943- _eauthor.
245	1	0	_aStatistical analysis of financial data : _bwith examples in R / _cJames E. Gentle.
264		1	_aBoca Raton, Florida : _bCRC Press, _c2020.
300			_axix, 645 pages : _billustrations ; _c24 cm.
336			_2rdacontent _atext
337			_2rdamedia _aunmediated
338			_2rdacarrier _avolume
490	1		_aChapman & Hall/CRC texts in statistical science series
504			_aIncludes bibliographical references and index.
505	0		_aFinancial time series -- Financial assets and markets -- Frequency distributions of returns -- Volatility -- Market dynamics -- Stylized facts about financial data -- Data reduction -- The empirical cumulative distribution function -- Nonparametric probability density estimation -- Graphical methods in exploratory analysis -- Random variables and probability distributions -- Some useful probability distributions -- Simulating observations of a random variables -- Models -- Criteria and methods for statistical modeling -- Optimization in statistical modeling; least squares and maximum likelihood -- Statistical inference -- Models of relationship among variables -- Assessing the adequacy of models -- Basic linear operations -- Analysis of discrete time series models -- Autoregressive and moving average models -- Conditional heteroscedasticity -- Unit root and cointegration
520			_aStatistical 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.
650		0	_aFinance _xMathematical models.
650		0	_aFinance _xEconometric models.
650		0	_aR (Computer program language)
830		0	_aTexts in statistical science.
942			_2ddc _cBK _h332.0151955 _iG289s _kCIR _m2020 _n0
999			_c26671 _d26671