Handbook In monte carlo simulation : applications in financial engineering, risk management and economics/ (Record no. 186856)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 00428nam a2200133Ia 4500 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9780470531112 |
| 040 ## - CATALOGING SOURCE | |
| Transcribing agency | CUS |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 330.01515282 |
| Item number | BRA/H |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Brandimarte, Paolo |
| 245 #0 - TITLE STATEMENT | |
| Title | Handbook In monte carlo simulation : applications in financial engineering, risk management and economics/ |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Place of publication, distribution, etc. | New Jersey: |
| Name of publisher, distributor, etc. | Wiley, |
| Date of publication, distribution, etc. | 2014. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 662p. |
| 505 ## - FORMATTED CONTENTS NOTE | |
| Formatted contents note | Part I Overview and Motivation <br/><br/>1 Introduction to Monte Carlo Methods <br/><br/>1.1 Historical origin of Monte Carlo simulation <br/><br/>1.2 Monte Carlo simulation vs. Monte Carlo sampling <br/><br/>1.3 System dynamics and the mechanics of Monte Carlo simulation <br/><br/>1.3.1 Discrete-time models <br/><br/>1.3.2 Continuous-time models <br/><br/>1.3.3 Discrete-event models <br/><br/>1.4 Simulation and optimization <br/><br/>1.4.1 Nonconvex optimization <br/><br/>1.4.2 Stochastic optimization <br/><br/>1.4.3 Stochastic dynamic programming <br/><br/>1.5 Pitfalls in Monte Carlo simulation. <br/><br/>1.5.1 Technical issues <br/><br/>1.5.2 Philosophical issues <br/><br/>1.6 Software tools for Monte Carlo simulation <br/><br/>1.7 Prerequisites <br/><br/>1.7.1 Mathematical background <br/><br/>1.7.2 Financial background <br/><br/>1.7.3 Technical background <br/><br/>For further reading <br/><br/>References <br/><br/>2 Numerical Integration Methods <br/><br/>2.1 Classical quadrature formulas <br/><br/>2.1.1 The rectangle rule <br/><br/>2.1.2 Interpolatory quadrature formulas <br/><br/>2.1.3 An alternative derivation <br/><br/>2.2 Gaussian quadrature <br/><br/>2.2.1 Theory of Gaussian quadrature: The role of orthogonal polynomials <br/><br/>2.2.2 Gaussian quadrature in R. <br/><br/>2.3 Extension to higher dimensions: Product rules <br/><br/>2.4 Alternative approaches for high-dimensional integration <br/><br/>2.4.1 Monte Carlo integration <br/><br/>2.4.2 Low-discrepancy sequences <br/><br/>2.4.3 Lattice methods <br/><br/>2.5 Relationship with moment matching <br/><br/>2.5.1 Binomial lattices <br/><br/>2.5.2 Scenario generation in stochastic programming <br/><br/>2.6 Numerical integration in R <br/><br/>For further reading <br/><br/>References <br/><br/>Part II Input Analysis: Modeling and Estimation <br/><br/>3 Stochastic Modeling in Finance and Economics <br/><br/>3.1 Introductory examples <br/><br/>3.1.1 Single-period portfolio optimization and modeling returns. <br/><br/>3.1.2 Consumption-saving with uncertain labor income <br/><br/>3.1.3 Continuous-time models for asset prices and interest rates <br/><br/>3.2 Some common probability distributions <br/><br/>3.2.1 Bernoulli, binomial, and geometric variables <br/><br/>3.2.2 Exponential and Poisson distributions <br/><br/>3.2.3 Normal and related distributions <br/><br/>3.2.4 Beta distribution <br/><br/>3.2.5 Gamma distribution <br/><br/>3.2.6 Empirical distributions -<br/><br/>3.3 Multivariate distributions: Covariance and correlation <br/><br/>3.3.1 Multivariate distributions <br/><br/>3.3.2 Covariance and Pearson's correlation <br/><br/>3.3.3 R functions for covariance and correlation. <br/><br/>3.3.4 Some typical multivariate distributions <br/><br/>3.4 Modeling dependence with copulas <br/><br/>3.4.1 Kendall's tau and Spearman's rho <br/><br/>3.4.2 Tail dependence <br/><br/>3.5 Linear regression models: A probabilistic view <br/><br/>3.6 Time series models <br/><br/>3.6.1 Moving-average processes <br/><br/>3.6.2 Autoregressive processes <br/><br/>3.6.3 ARMA and ARIMA processes <br/><br/>3.6.4 Vector autoregressive models <br/><br/>3.6.5 Modeling stochastic volatility <br/><br/>3.7 Stochastic differential equations <br/><br/>3.7.1 From discrete to continuous time <br/><br/>3.7.2 Standard Wiener process <br/><br/>3.7.3 Stochastic integration and Itô's lemma. |
| 650 ## - SUBJECT | |
| Keyword | Monte Carlo method |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | Reference Books |
| Withdrawn status | Lost status | Damaged status | Not for loan | Collection Type | Home library | Current library | Shelving location | Date acquired | Full call number | Accession number | Date last seen | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Not For Loan | Reference Collection | Central Library, Sikkim University | Central Library, Sikkim University | Reference | 29/08/2016 | 330.01515282 BRA/H | P41870 | 23/09/2022 | Reference Books |