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Foundations of quantitative finance book IV: (Record no. 7627)

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000 -LEADER
fixed length control field	06437nam a22002177a 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field	20241202201419.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field	241201b \|\|\|\|\|\|\|\| \|\|\|\| 00\| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number	9781032206523
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number	332.015195
Item number	REI
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name	Reitano, Robert R
245 ## - TITLE STATEMENT
Title	Foundations of quantitative finance book IV:
Remainder of title	distribution functions and expectations
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Name of publisher, distributor, etc.	CRC Press
Place of publication, distribution, etc.	Boca Raton
Date of publication, distribution, etc.	2024
300 ## - PHYSICAL DESCRIPTION
Extent	xvii, 250 p.
365 ## - TRADE PRICE
Price type code	GBP
Price amount	76.99
490 ## - SERIES STATEMENT
Series statement	Chapman and Hall/CRC Financial Mathematics Series
500 ## - GENERAL NOTE
General note	Table of content:<br/>Preface<br/><br/>Introduction<br/><br/>1 Distribution and Density Functions<br/><br/>l.l Summary of Book II Results<br/><br/>l.l.l DistributionFunctionsonJR<br/><br/>l.l.2 Distribution Functions on JRn<br/><br/>l.2 DecompositionofDistributionFunctionsonJR<br/><br/>l.3 DensityFunctionsonJR<br/><br/>l.3.l TheLebesgueApproach<br/><br/>l.3.2 RiemannApproach<br/><br/>l.3.3 Riemann-Stieltjes Framework<br/><br/>l.4 Examples of Distribution Functions on JR<br/><br/>l.4.l DiscreteDistributionFunctions<br/><br/>l.4.2 ContinuousDistributionFunctions<br/><br/>l.4.3 MixedDistributionFunctions<br/><br/>2 Transformed Random Variables-<br/><br/>2.l MonotonicTransformations<br/><br/>2.2 SumsofIndependentRandomVariables<br/><br/>2.2.l DistributionFunctionsofSums<br/><br/>2.2.2 Density Functions of Sums <br/><br/>2.3 Ratios of Random Variables<br/><br/>2.3.l Independent Random Variable<br/><br/>2.3.2 Example without Independence<br/><br/>3 Order Statistics <br/><br/>3.l-M -Samples and Order Statistics<br/><br/>3.2-Distribution Functions for kth Order Statistics<br/><br/>3.3-Density Functions for kth Order Statistics<br/><br/>3.4-Joint Distribution of all Order Statistics<br/><br/>3.5-Density Functions on JRn<br/><br/>3.6-Multivariate Density Functions<br/><br/>-3.6.l Joint Density of all Order Statistics<br/><br/>-3.6.2 Marginal Densities and Distributions<br/><br/>-3.6.3 Conditional Densities and Distributions<br/><br/>3.7-The Renyi Representation Theorem<br/><br/> <br/><br/>4 EXpectationsofRandomVariables1<br/><br/>4.l General Definitions<br/><br/>4.l.l Is Expectation Well Defined?<br/><br/>4.l.2 Formal Resolution of Well-Definedness<br/><br/>4.2 Moments of Distributions<br/><br/>4.2.l Common Types of Moments<br/><br/>4.2.2 Moment Generating Function<br/><br/>4.2.3 Moments of Sums - Theory<br/><br/>4.2.4 Moments of Sums - Applications<br/><br/>4.2.5 Properties of Moments<br/><br/>4.2.6 Moment Examples-Discrete Distributions<br/><br/>4.2.7 Moment Examples-Continuous Distributions<br/><br/>4.3 Moment Inequalities<br/><br/>4.3.l Chebyshev's Inequality<br/><br/>4.3.2 Jensen's Inequality<br/><br/>4.3.3 Kolmogorov's Inequality<br/><br/>4.3.4 Cauchy-Schwarz Inequality<br/><br/>4.3.5 Holder and Lyapunov Inequalities<br/><br/>4.4 Uniqueness of Moments<br/><br/>4.4.l Applications of Moment Uniqueness<br/><br/>4.5 Weak Convergence and Moment Limits<br/><br/>5 Simulating Samples of RVs - EXamples <br/><br/>5.l Random Samples<br/><br/>5.l.l Discrete Distributions<br/><br/>5.l.2 Simpler Continuous Distributions<br/><br/>5.l.3 Normal and Lognormal Distributions<br/><br/>5.l.4 Student T Distribution<br/><br/> <br/><br/>5.2 Ordered Random Samples<br/><br/>5.2.l Direct Approaches<br/><br/>5.2.2 The Renyi Representation<br/><br/>6 Limit Theorems <br/><br/>6.l Introduction<br/><br/>6.2 Weak Convergence of Distributions<br/><br/>6.2.l Student T ⇒ Normal<br/><br/>6.2.2 Poisson Limit Theorem<br/><br/>6.2.3 "Weak Law of Small Numbers"<br/><br/>6.2.4 De Moivre-Laplace Theorem<br/><br/>6.2.5 The Central Limit Theorem l<br/><br/>6.2.6 Smirnov's Theorem on Uniform Order Statistics<br/><br/>6.2.7 A Limit Theorem on General Quantiles<br/><br/>6.2.8 A Limit Theorem on Exponential Order Statistics<br/><br/>6.3 Laws of Large Numbers<br/><br/>6.3.l Tail Events and Kolmogorov's 0-l Law<br/><br/>6.3.2 Weak Laws of Large Numbers<br/><br/>6.3.3 Strong Laws of Large Numbers<br/><br/>6.3.4 A Limit Theorem in EVT<br/><br/>6.4 Convergence of Empirical Distributions<br/><br/>6.4.l Definition and Basic Properties<br/><br/>6.4.2 The Glivenko-Cantelli Theorem<br/><br/>6.4.3 Distributional Estimates for Dn(s)<br/><br/>7 Estimating Tail Events 2 <br/><br/>7.l Large Deviation Theory 2<br/><br/>7.l.l Chernoff Bound<br/><br/>7.l.2 Cramer-Chernoff Theorem<br/><br/>7.2 Extreme Value Theory 2<br/><br/>7.2.l Fisher-Tippett-Gnedenko theorem<br/><br/>7.2.2 The Hill Estimator, 1 > 0<br/><br/>7.2.3 F E D(G,) is Asymptotically Pareto for 1 > 0<br/><br/>7.2.4 F E D(G,), 1 > 0, then 1H � 1<br/><br/>7.2.5 F E D(G,), 1 > 0, then 1H -1 1<br/><br/>7.2.6 Asymptotic Normality of the Hill Estimator<br/>7.2.7 The Pickands-Balkema-de Haan Theorem: 1 > 0<br/><br/>References <br/>[https://www.routledge.com/Foundations-of-Quantitative-Finance-Book-IV-Distribution-Functions-and-Expectations/Reitano/p/book/9781032206523]
520 ## - SUMMARY, ETC.
Summary, etc.	Every finance professional wants and needs a competitive edge. A firm foundation in advanced mathematics can translate into dramatic advantages to professionals willing to obtain it. Many are not—and that is the competitive edge these books offer the astute reader.<br/><br/>Published under the collective title of Foundations of Quantitative Finance, this set of ten books develops the advanced topics in mathematics that finance professionals need to advance their careers. These books expand the theory most do not learn in graduate finance programs, or in most financial mathematics undergraduate and graduate courses.<br/><br/>As an investment executive and authoritative instructor, Robert R. Reitano presents the mathematical theories he encountered and used in nearly three decades in the financial services industry and two decades in academia where he taught in highly respected graduate programs.<br/><br/>Readers should be quantitatively literate and familiar with the developments in the earlier books in the set. While the set offers a continuous progression through these topics, each title can be studied independently.<br/><br/>(https://www.routledge.com/Foundations-of-Quantitative-Finance-Book-IV-Distribution-Functions-and-Expectations/Reitano/p/book/9781032206523)
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element	Finance--Mathematical models
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name	Integrals
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type	Book
Source of classification or shelving scheme	Dewey Decimal Classification

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Withdrawn status	Lost status	Source of classification or shelving scheme	Damaged status	Not for loan	Collection code	Bill No	Bill Date	Home library	Current library	Shelving location	Date acquired	Source of acquisition	Cost, normal purchase price	Total Checkouts	Full call number	Accession Number	Date last seen	Copy number	Cost, replacement price	Price effective from	Koha item type
		Dewey Decimal Classification			Finance & Accounting	1182328	28-11-2024	Indian Institute of Management LRC	Indian Institute of Management LRC	General Stacks	12/02/2024	Atlantic Publishers & Distributors	5785.03		332.015195 REI	006716	12/02/2024	1	8900.04	12/02/2024	Book