Statistical analysis of financial data : (Record no. 92015)

MARC details
000 -LEADER
fixed length control field 02447nam a22002057a 4500
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 240305b2021 |||||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781032173467
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 332.0151955 GEN-J
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Gentle, James E.
245 ## - TITLE STATEMENT
Title Statistical analysis of financial data :
Remainder of title with examples in R /
Statement of responsibility, etc. James E. Gentle
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc. Boca Raton
Name of publisher, distributor, etc. CRC Press
Date of publication, distribution, etc. 2021
300 ## - PHYSICAL DESCRIPTION
Extent 645p.
440 ## - SERIES STATEMENT/ADDED ENTRY--TITLE
Title Texts in Statistical Science
500 ## - GENERAL NOTE
General note 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.<br/><br/><br/><br/>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.<br/><br/><br/><br/>Features<br/><br/><br/>* Covers statistical methods for analyzing models appropriate for financial data, especially models with outliers or heavy-tailed distributions.<br/><br/><br/>* Describes both the basics of R and advanced techniques useful in financial data analysis.<br/><br/><br/>* Driven by real, current financial data, not just stale data deposited on some static website.<br/><br/><br/>* 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 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Statistical Analysis
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Financial Data
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Finance--Mathematical models.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Finance--Econometric models.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element R (Computer program language)
952 ## - LOCATION AND ITEM INFORMATION (KOHA)
Withdrawn status
Holdings
Lost status Source of classification or shelving scheme Damaged status Not for loan Collection code Home library Current library Shelving location Date acquired Total Checkouts Full call number Barcode Date last seen Price effective from Koha item type
  Dewey Decimal Classification     330 BITS Pilani Hyderabad BITS Pilani Hyderabad General Stack (For lending) 05/03/2024   332.0151955 GEN-J 48468 13/07/2024 05/03/2024 Books
An institution deemed to be a University Estd. Vide Sec.3 of the UGC
Act,1956 under notification # F.12-23/63.U-2 of Jun 18,1964

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