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The Resource Finance with Monte Carlo, by Ronald W. Shonkwiler, (electronic resource)
Finance with Monte Carlo, by Ronald W. Shonkwiler, (electronic resource)
Resource Information
The item Finance with Monte Carlo, by Ronald W. Shonkwiler, (electronic resource) represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in Boston University Libraries.This item is available to borrow from all library branches.
Resource Information
The item Finance with Monte Carlo, by Ronald W. Shonkwiler, (electronic resource) represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in Boston University Libraries.
This item is available to borrow from all library branches.
 Summary
 This text introduces upper division undergraduate/beginning graduate students in mathematics, finance, or economics, to the core topics of a beginning course in finance/financial engineering. Particular emphasis is placed on exploiting the power of the Monte Carlo method to illustrate and explore financial principles. Monte Carlo is the uniquely appropriate tool for modeling the random factors that drive financial markets and simulating their implications. The Monte Carlo method is introduced early and it is used in conjunction with the geometric Brownian motion model (GBM) to illustrate and analyze the topics covered in the remainder of the text. Placing focus on Monte Carlo methods allows for students to travel a short road from theory to practical applications. Coverage includes investment science, meanvariance portfolio theory, option pricing principles, exotic options, option trading strategies, jump diffusion and exponential Lévy alternative models, and the Kelly criterion for maximizing investment growth. Novel features: inclusion of both portfolio theory and contingent claim analysis in a single text pricing methodology for exotic options expectation analysis of option trading strategies pricing models that transcend the Black–Scholes framework optimizing investment allocations concepts thoroughly explored through numerous simulation exercises numerous worked examples and illustrations The mathematical background required is a year and onehalf course in calculus, matrix algebra covering solutions of linear systems, and a knowledge of probability including expectation, densities and the normal distribution. A refresher for these topics is presented in the Appendices. The programming background needed is how to code branching, loops and subroutines in some mathematical or general purpose language. The mathematical background required is a year and onehalf course in calculus, matrix algebra covering solutions of linear systems, and a knowledge of probability including expectation, densities and the normal distribution. A refresher for these topics is presented in the Appendices. The programming background needed is how to code branching, loops and subroutines in some mathematical or general purpose language. Also by the author: (with F. Mendivil) Explorations in Monte Carlo, ©2009, ISBN: 9780387878362; (with J. Herod) Mathematical Biology: An Introduction with Maple and Matlab, Second edition, ©2009, ISBN: 9780387709833
 Language
 eng
 Extent
 XIX, 250 p. 70 illus., 17 illus. in color.
 Contents

 1. Geometric Brownian Motion and the Efficient Market Hypothesis
 2. Return and Risk
 3. Forward and Option Contracts and their Pricing
 4. Pricing Exotic Options
 5. Option Trading Strategies
 6. Alternative to GBM Prices
 7. Kelly's Criterion
 Appendices
 A. Some Mathematical Background Topics
 B. Stochastic Calculus
 C. Convergence of the Binomial Method
 D. Variance Reduction Techniques
 E. Shell Sort
 F. Next Day Prices Program
 References
 List of Notation
 List of Algorithms
 Index
 Isbn
 9781461485117
 Label
 Finance with Monte Carlo
 Title
 Finance with Monte Carlo
 Statement of responsibility
 by Ronald W. Shonkwiler
 Subject

 Mathematical Modeling and Industrial Mathematics
 Distribution (Probability theory)
 Probability Theory and Stochastic Processes
 Numerical Analysis
 Distribution (Probability theory)
 Finance
 Numerical analysis
 Electronic resources
 Quantitative Finance
 Numerical analysis
 Mathematics
 Mathematics
 Numerical Analysis
 Distribution (Probability theory)
 Finance
 Language
 eng
 Summary
 This text introduces upper division undergraduate/beginning graduate students in mathematics, finance, or economics, to the core topics of a beginning course in finance/financial engineering. Particular emphasis is placed on exploiting the power of the Monte Carlo method to illustrate and explore financial principles. Monte Carlo is the uniquely appropriate tool for modeling the random factors that drive financial markets and simulating their implications. The Monte Carlo method is introduced early and it is used in conjunction with the geometric Brownian motion model (GBM) to illustrate and analyze the topics covered in the remainder of the text. Placing focus on Monte Carlo methods allows for students to travel a short road from theory to practical applications. Coverage includes investment science, meanvariance portfolio theory, option pricing principles, exotic options, option trading strategies, jump diffusion and exponential Lévy alternative models, and the Kelly criterion for maximizing investment growth. Novel features: inclusion of both portfolio theory and contingent claim analysis in a single text pricing methodology for exotic options expectation analysis of option trading strategies pricing models that transcend the Black–Scholes framework optimizing investment allocations concepts thoroughly explored through numerous simulation exercises numerous worked examples and illustrations The mathematical background required is a year and onehalf course in calculus, matrix algebra covering solutions of linear systems, and a knowledge of probability including expectation, densities and the normal distribution. A refresher for these topics is presented in the Appendices. The programming background needed is how to code branching, loops and subroutines in some mathematical or general purpose language. The mathematical background required is a year and onehalf course in calculus, matrix algebra covering solutions of linear systems, and a knowledge of probability including expectation, densities and the normal distribution. A refresher for these topics is presented in the Appendices. The programming background needed is how to code branching, loops and subroutines in some mathematical or general purpose language. Also by the author: (with F. Mendivil) Explorations in Monte Carlo, ©2009, ISBN: 9780387878362; (with J. Herod) Mathematical Biology: An Introduction with Maple and Matlab, Second edition, ©2009, ISBN: 9780387709833
 http://library.link/vocab/creatorName
 Shonkwiler, Ronald W
 Image bit depth
 0
 LC call number
 HB135147
 Literary form
 non fiction
 http://library.link/vocab/relatedWorkOrContributorName
 SpringerLink
 Series statement
 Springer Undergraduate Texts in Mathematics and Technology,
 http://library.link/vocab/subjectName

 Mathematics
 Finance
 Numerical analysis
 Distribution (Probability theory)
 Mathematics
 Quantitative Finance
 Mathematical Modeling and Industrial Mathematics
 Probability Theory and Stochastic Processes
 Numerical Analysis
 Label
 Finance with Monte Carlo, by Ronald W. Shonkwiler, (electronic resource)
 Antecedent source
 mixed
 Carrier category
 online resource
 Carrier category code
 cr
 Carrier MARC source
 rdacarrier
 Color
 not applicable
 Content category
 text
 Content type code
 txt
 Content type MARC source
 rdacontent
 Contents
 1. Geometric Brownian Motion and the Efficient Market Hypothesis  2. Return and Risk  3. Forward and Option Contracts and their Pricing  4. Pricing Exotic Options  5. Option Trading Strategies  6. Alternative to GBM Prices  7. Kelly's Criterion  Appendices  A. Some Mathematical Background Topics  B. Stochastic Calculus  C. Convergence of the Binomial Method  D. Variance Reduction Techniques  E. Shell Sort  F. Next Day Prices Program  References  List of Notation  List of Algorithms  Index
 Dimensions
 unknown
 Extent
 XIX, 250 p. 70 illus., 17 illus. in color.
 File format
 multiple file formats
 Form of item
 electronic
 Isbn
 9781461485117
 Level of compression
 uncompressed
 Media category
 computer
 Media MARC source
 rdamedia
 Media type code
 c
 Other control number
 10.1007/9781461485117
 Other physical details
 online resource.
 Quality assurance targets
 absent
 Reformatting quality
 access
 Specific material designation
 remote
 System control number
 (DEHe213)9781461485117
 Label
 Finance with Monte Carlo, by Ronald W. Shonkwiler, (electronic resource)
 Antecedent source
 mixed
 Carrier category
 online resource
 Carrier category code
 cr
 Carrier MARC source
 rdacarrier
 Color
 not applicable
 Content category
 text
 Content type code
 txt
 Content type MARC source
 rdacontent
 Contents
 1. Geometric Brownian Motion and the Efficient Market Hypothesis  2. Return and Risk  3. Forward and Option Contracts and their Pricing  4. Pricing Exotic Options  5. Option Trading Strategies  6. Alternative to GBM Prices  7. Kelly's Criterion  Appendices  A. Some Mathematical Background Topics  B. Stochastic Calculus  C. Convergence of the Binomial Method  D. Variance Reduction Techniques  E. Shell Sort  F. Next Day Prices Program  References  List of Notation  List of Algorithms  Index
 Dimensions
 unknown
 Extent
 XIX, 250 p. 70 illus., 17 illus. in color.
 File format
 multiple file formats
 Form of item
 electronic
 Isbn
 9781461485117
 Level of compression
 uncompressed
 Media category
 computer
 Media MARC source
 rdamedia
 Media type code
 c
 Other control number
 10.1007/9781461485117
 Other physical details
 online resource.
 Quality assurance targets
 absent
 Reformatting quality
 access
 Specific material designation
 remote
 System control number
 (DEHe213)9781461485117
Subject
 Distribution (Probability theory)
 Distribution (Probability theory)
 Distribution (Probability theory)
 Electronic resources
 Finance
 Finance
 Mathematical Modeling and Industrial Mathematics
 Mathematics
 Mathematics
 Numerical Analysis
 Numerical Analysis
 Numerical analysis
 Numerical analysis
 Probability Theory and Stochastic Processes
 Quantitative Finance
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