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Stochastic Analysis for Finance with Simulations

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Cover of 'Stochastic Analysis for Finance with Simulations'

Table of Contents

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    Book Overview
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    Chapter 1 Fundamental Concepts
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    Chapter 2 Financial Derivatives
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    Chapter 3 The Lebesgue Integral
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    Chapter 4 Basic Probability Theory
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    Chapter 5 Conditional Expectation
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    Chapter 6 Stochastic Processes
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    Chapter 7 Brownian Motion
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    Chapter 8 Girsanov’s Theorem
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    Chapter 9 The Reflection Principle of Brownian Motion
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    Chapter 10 The Itô Integral
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    Chapter 11 The Itô Formula
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    Chapter 12 Stochastic Differential Equations
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    Chapter 13 The Feynman–Kac Theorem
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    Chapter 14 The Binomial Tree Method for Option Pricing
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    Chapter 15 The Black–Scholes–Merton Differential Equation
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    Chapter 16 The Martingale Method
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    Chapter 17 Pricing of Vanilla Options
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    Chapter 18 Pricing of Exotic Options
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    Chapter 19 American Options
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    Chapter 20 The Capital Asset Pricing Model
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    Chapter 21 Dynamic Programming
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    Chapter 22 Bond Pricing
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    Chapter 23 Interest Rate Models
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    Chapter 24 Numeraires
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    Chapter 25 Numerical Estimation of Volatility
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    Chapter 26 Time Series
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    Chapter 27 Random Numbers
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    Chapter 28 The Monte Carlo Method for Option Pricing Monte Carlo method
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    Chapter 29 Numerical Solution of the Black–Scholes–Merton Equation
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    Chapter 30 Numerical Solution of Stochastic Differential Equations
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Citations

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Title
Stochastic Analysis for Finance with Simulations
Published by
Springer International Publishing, January 2016
DOI 10.1007/978-3-319-25589-7
ISBNs
978-3-31-925589-7, 978-3-31-925587-3
Authors

Geon Ho Choe, Choe, Geon Ho

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 19 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 21%
Unspecified 3 16%
Student > Ph. D. Student 3 16%
Student > Bachelor 2 11%
Researcher 2 11%
Other 5 26%
Readers by discipline Count As %
Mathematics 5 26%
Unspecified 4 21%
Computer Science 2 11%
Decision Sciences 2 11%
Engineering 2 11%
Other 4 21%