Coverart for item
The Resource Risk neutral pricing and financial mathematics : a primer, Peter M. Knopf, John L. Teall, (electronic book)

Risk neutral pricing and financial mathematics : a primer, Peter M. Knopf, John L. Teall, (electronic book)

Label
Risk neutral pricing and financial mathematics : a primer
Title
Risk neutral pricing and financial mathematics
Title remainder
a primer
Statement of responsibility
Peter M. Knopf, John L. Teall
Creator
Contributor
Author
Subject
Language
eng
Summary
Risk Neutral Pricing and Financial Mathematics: A Primer provides a foundation to financial mathematics for those whose undergraduate quantitative preparation does not extend beyond calculus, statistics, and linear math. It covers a broad range of foundation topics related to financial modeling, including probability, discrete and continuous time and space valuation, stochastic processes, equivalent martingales, option pricing, and term structure models, along with related valuation and hedging techniques. The joint effort of two authors with a combined 70 years of academic and practitioner e
Member of
Cataloging source
N$T
http://library.link/vocab/creatorName
Knopf, Peter M
Dewey number
658.15
Index
index present
LC call number
HG176.7
Literary form
non fiction
Nature of contents
dictionaries
http://library.link/vocab/relatedWorkOrContributorDate
1958-
http://library.link/vocab/relatedWorkOrContributorName
Teall, John L.
http://library.link/vocab/subjectName
  • Financial engineering
  • Business mathematics
Label
Risk neutral pricing and financial mathematics : a primer, Peter M. Knopf, John L. Teall, (electronic book)
Instantiates
Publication
Note
Includes index
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
  • Front Cover; Risk Neutral Pricing and Financial Mathematics; Copyright Page; Dedication; Contents; About the Authors; Preface; 1 Preliminaries and Review; 1.1 Financial Models; 1.2 Financial Securities and Instruments; 1.3 Review of Matrices and Matrix Arithmetic; 1.3.1 Matrix Arithmetic; 1.3.1.1 Matrix Arithmetic Properties; 1.3.1.2 The Inverse Matrix; Illustration: The Gauss-Jordan Method; Illustration: Solving Systems of Equations; 1.3.2 Vector Spaces, Spanning, and Linear Dependence; 1.3.2.1 Linear Dependence and Linear Independence; Illustrations: Linear Dependence and Independence
  • 1.3.2.2 Spanning the Vector Space and the BasisIllustration: Spanning the Vector Space and the Basis; 1.4 Review of Differential Calculus; 1.4.1 Essential Rules for Calculating Derivatives; 1.4.1.1 The Power Rule; 1.4.1.2 The Sum Rule; 1.4.1.3 The Chain Rule; 1.4.1.4 Product and Quotient Rules; 1.4.1.5 Exponential and Log Function Rules; 1.4.2 The Differential; Illustration: The Differential and the Error; 1.4.3 Partial Derivatives; 1.4.3.1 The Chain Rule for Two Independent Variables; 1.4.4 Taylor Polynomials and Expansions; 1.4.5 Optimization and the Method of Lagrange Multipliers
  • Illustration: Lagrange Optimization1.5 Review of Integral Calculus; 1.5.1 Antiderivatives; 1.5.2 Definite Integrals; 1.5.2.1 Reimann Sums; 1.5.3 Change of Variables Technique to Evaluate Integrals; Illustration: Change of Variables Technique for the Indefinite Integral; 1.5.3.1 Change of Variables Technique for the Definite Integral; 1.6 Exercises; Notes; 2 Probability and Risk; 2.1 Uncertainty in Finance; 2.2 Sets and Measures; 2.2.1 Sets; Illustration: Toss of Two Dice; 2.2.1.1 Finite, Countable, and Uncountable Sets; 2.2.2 Measurable Spaces and Measures; 2.3 Probability Spaces
  • 2.3.1 Physical and Risk-Neutral ProbabilitiesIllustration: Probability Space; 2.3.2 Random Variables; Illustration: Discrete Random Variables; 2.4 Statistics and Metrics; 2.4.1 Metrics in Discrete Spaces; 2.4.1.1 Expected Value, Variance, and Standard Deviation; Illustration; 2.4.1.2 Co-movement Statistics; 2.4.2 Metrics in Continuous Spaces; Illustration: Distributions in a Continuous Space; 2.4.2.1 Expected Value and Variance; 2.5 Conditional Probability; Illustration: Drawing a Spade; 2.5.1 Bayes Theorem; Illustration: Detecting Illegal Insider Trading; 2.5.2 Independent Random Variables
  • Illustration2.5.2.1 Multiple Random Variables; 2.6 Distributions and Probability Density Functions; 2.6.1 The Binomial Random Variable; Illustration: Coin Tossing; Illustration: DK Trades; 2.6.2 The Uniform Random Variable; Illustration: Uniform Random Variable; 2.6.3 The Normal Random Variable; 2.6.3.1 Calculating Cumulative Normal Density; 2.6.3.2 Linear Combinations of Independent Normal Random Variables; 2.6.4 The Lognormal Random Variable; 2.6.4.1 The Expected Value of the Lognormal Distribution; Illustration: Risky Securities; 2.6.5 The Poisson Random Variable
Control code
SCIDI915560702
Dimensions
unknown
Extent
1 online resource
File format
unknown
Form of item
online
Isbn
9780128017272
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Reformatting quality
preservation
Sound
unknown sound
Specific material designation
remote
Label
Risk neutral pricing and financial mathematics : a primer, Peter M. Knopf, John L. Teall, (electronic book)
Publication
Note
Includes index
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
  • Front Cover; Risk Neutral Pricing and Financial Mathematics; Copyright Page; Dedication; Contents; About the Authors; Preface; 1 Preliminaries and Review; 1.1 Financial Models; 1.2 Financial Securities and Instruments; 1.3 Review of Matrices and Matrix Arithmetic; 1.3.1 Matrix Arithmetic; 1.3.1.1 Matrix Arithmetic Properties; 1.3.1.2 The Inverse Matrix; Illustration: The Gauss-Jordan Method; Illustration: Solving Systems of Equations; 1.3.2 Vector Spaces, Spanning, and Linear Dependence; 1.3.2.1 Linear Dependence and Linear Independence; Illustrations: Linear Dependence and Independence
  • 1.3.2.2 Spanning the Vector Space and the BasisIllustration: Spanning the Vector Space and the Basis; 1.4 Review of Differential Calculus; 1.4.1 Essential Rules for Calculating Derivatives; 1.4.1.1 The Power Rule; 1.4.1.2 The Sum Rule; 1.4.1.3 The Chain Rule; 1.4.1.4 Product and Quotient Rules; 1.4.1.5 Exponential and Log Function Rules; 1.4.2 The Differential; Illustration: The Differential and the Error; 1.4.3 Partial Derivatives; 1.4.3.1 The Chain Rule for Two Independent Variables; 1.4.4 Taylor Polynomials and Expansions; 1.4.5 Optimization and the Method of Lagrange Multipliers
  • Illustration: Lagrange Optimization1.5 Review of Integral Calculus; 1.5.1 Antiderivatives; 1.5.2 Definite Integrals; 1.5.2.1 Reimann Sums; 1.5.3 Change of Variables Technique to Evaluate Integrals; Illustration: Change of Variables Technique for the Indefinite Integral; 1.5.3.1 Change of Variables Technique for the Definite Integral; 1.6 Exercises; Notes; 2 Probability and Risk; 2.1 Uncertainty in Finance; 2.2 Sets and Measures; 2.2.1 Sets; Illustration: Toss of Two Dice; 2.2.1.1 Finite, Countable, and Uncountable Sets; 2.2.2 Measurable Spaces and Measures; 2.3 Probability Spaces
  • 2.3.1 Physical and Risk-Neutral ProbabilitiesIllustration: Probability Space; 2.3.2 Random Variables; Illustration: Discrete Random Variables; 2.4 Statistics and Metrics; 2.4.1 Metrics in Discrete Spaces; 2.4.1.1 Expected Value, Variance, and Standard Deviation; Illustration; 2.4.1.2 Co-movement Statistics; 2.4.2 Metrics in Continuous Spaces; Illustration: Distributions in a Continuous Space; 2.4.2.1 Expected Value and Variance; 2.5 Conditional Probability; Illustration: Drawing a Spade; 2.5.1 Bayes Theorem; Illustration: Detecting Illegal Insider Trading; 2.5.2 Independent Random Variables
  • Illustration2.5.2.1 Multiple Random Variables; 2.6 Distributions and Probability Density Functions; 2.6.1 The Binomial Random Variable; Illustration: Coin Tossing; Illustration: DK Trades; 2.6.2 The Uniform Random Variable; Illustration: Uniform Random Variable; 2.6.3 The Normal Random Variable; 2.6.3.1 Calculating Cumulative Normal Density; 2.6.3.2 Linear Combinations of Independent Normal Random Variables; 2.6.4 The Lognormal Random Variable; 2.6.4.1 The Expected Value of the Lognormal Distribution; Illustration: Risky Securities; 2.6.5 The Poisson Random Variable
Control code
SCIDI915560702
Dimensions
unknown
Extent
1 online resource
File format
unknown
Form of item
online
Isbn
9780128017272
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Reformatting quality
preservation
Sound
unknown sound
Specific material designation
remote

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