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1.

電子ブック
ＥＢ
1. Financial Instrument Pricing Using C++, 2nd Edition
Daniel J. Duffy
出版情報: Wiley Online Library - AutoHoldings Books , John Wiley & Sons, Inc., 2018
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2.

電子ブック
ＥＢ
2. Finite Difference Methods in Financial Engineering : A Partial Differential Equation Approach {Wiley Finance Series}
Daniel J. Duffy
出版情報: Wiley Online Library - AutoHoldings Books , John Wiley & Sons, Inc., 2006
所蔵情報: loading…
目次情報: 続きを見る
Goals of this Book and Global Overview / 0：
What is this book? / 0.1：
Why has this book been written? / 0.2：
For whom is this book intended? / 0.3：
Why should I read this book? / 0.4：
The structure of this book / 0.5：
What this book does not cover / 0.6：
Contact, feedback and more information / 0.7：
The Continuous Theory of Partial Differential Equations / Part I：
An Introduction to Ordinary Differential Equations / 1：
Introduction and objectives / 1.1：
Two-point boundary value problem / 1.2：
Linear boundary value problems / 1.3：
Initial value problems / 1.4：
Some special cases / 1.5：
Summary and conclusions / 1.6：
An Introduction to Partial Differential Equations / 2：
Partial differential equations / 2.1：
Specialisations / 2.3：
Parabolic partial differential equations / 2.4：
Hyperbolic equations / 2.5：
Systems of equations / 2.6：
Equations containing integrals / 2.7：
Second-Order Parabolic Differential Equations / 2.8：
Linear parabolic equations / 3.1：
The continuous problem / 3.3：
The maximum principle for parabolic equations / 3.4：
A special case: one-factor generalised Black-Scholes models / 3.5：
Fundamental solution and the Green's function / 3.6：
Integral representation of the solution of parabolic PDEs / 3.7：
Parabolic equations in one space dimension / 3.8：
An Introduction to the Heat Equation in One Dimension / 3.9：
Motivation and background / 4.1：
The heat equation and financial engineering / 4.3：
The separation of variables technique / 4.4：
Transformation techniques for the heat equation / 4.5：
An Introduction to the Method of Characteristics / 4.6：
First-order hyperbolic equations / 5.1：
Second-order hyperbolic equations / 5.3：
Applications to financial engineering / 5.4：
Propagation of discontinuities / 5.5：
Finite Difference Methods: The Fundamentals / 5.7：
An Introduction to the Finite Difference Method / 6：
Fundamentals of numerical differentiation / 6.1：
Caveat: accuracy and round-off errors / 6.3：
Where are divided differences used in instrument pricing? / 6.4：
Nonlinear initial value problems / 6.5：
Scalar initial value problems / 6.7：
An Introduction to the Method of Lines / 6.8：
Classifying semi-discretisation methods / 7.1：
Semi-discretisation in space using FDM / 7.3：
Numerical approximation of first-order systems / 7.4：
General Theory of the Finite Difference Method / 7.5：
Some fundamental concepts / 8.1：
Stability and the Fourier transform / 8.3：
The discrete Fourier transform / 8.4：
Stability for initial boundary value problems / 8.5：
Finite Difference Schemes for First-Order Partial Differential Equations / 8.6：
Scoping the problem / 9.1：
Why first-order equations are different: Essential difficulties / 9.3：
A simple explicit scheme / 9.4：
Some common schemes for initial value problems / 9.5：
Some common schemes for initial boundary value problems / 9.6：
Monotone and positive-type schemes / 9.7：
Extensions, generalisations and other applications / 9.8：
FDM for the One-Dimensional Convection-Diffusion Equation / 9.9：
Approximation of derivatives on the boundaries / 10.1：
Time-dependent convection-diffusion equations / 10.3：
Fully discrete schemes / 10.4：
Specifying initial and boundary conditions / 10.5：
Semi-discretisation in space / 10.6：
Semi-discretisation in time / 10.7：
Exponentially Fitted Finite Difference Schemes / 10.8：
Motivating exponential fitting / 11.1：
Exponential fitting and time-dependent convection-diffusion / 11.3：
Stability and convergence analysis / 11.4：
Approximating the derivative of the solution / 11.5：
Special limiting cases / 11.6：
Applying FDM to One-Factor Instrument Pricing / 11.7：
Exact Solutions and Explicit Finite Difference Method for One-Factor Models / 12：
Exact solutions and benchmark cases / 12.1：
Perturbation analysis and risk engines / 12.3：
The trinomial method: Preview / 12.4：
Using exponential fitting with explicit time marching / 12.5：
Approximating the Greeks / 12.6：
Appendix: the formula for Vega / 12.7：
An Introduction to the Trinomial Method / 13：
Motivating the trinomial method / 13.1：
Trinomial method: Comparisons with other methods / 13.3：
The trinomial method for barrier options / 13.4：
Exponentially Fitted Difference Schemes for Barrier Options / 13.5：
What are barrier options? / 14.1：
Initial boundary value problems for barrier options / 14.3：
Using exponential fitting for barrier options / 14.4：
Time-dependent volatility / 14.5：
Some other kinds of exotic options / 14.6：
Comparisons with exact solutions / 14.7：
Other schemes and approximations / 14.8：
Extensions to the model / 14.9：
Advanced Issues in Barrier and Lookback Option Modelling / 14.10：
Kinds of boundaries and boundary conditions / 15.1：
Discrete and continuous monitoring / 15.3：
Continuity corrections for discrete barrier options / 15.4：
Complex barrier options / 15.5：
The Meshless (Meshfree) Method in Financial Engineering / 15.6：
Motivating the meshless method / 16.1：
An introduction to radial basis functions / 16.3：
Semi-discretisations and convection-diffusion equations / 16.4：
Applications of the one-factor Black-Scholes equation / 16.5：
Advantages and disadvantages of meshless / 16.6：
Extending the Black-Scholes Model: Jump Processes / 16.7：
Jump-diffusion processes / 17.1：
Partial integro-differential equations and financial applications / 17.3：
Numerical solution of PIDE: Preliminaries / 17.4：
Techniques for the numerical solution of PIDEs / 17.5：
Implicit and explicit methods / 17.6：
Implicit-explicit Runge-Kutta methods / 17.7：
Using operator splitting / 17.8：
Splitting and predictor-corrector methods / 17.9：
FDM for Multidimensional Problems / 17.10：
Finite Difference Schemes for Multidimensional Problems / 18：
Elliptic equations / 18.1：
Diffusion and heat equations / 18.3：
Advection equation in two dimensions / 18.4：
Convection-diffusion equation / 18.5：
An Introduction to Alternating Direction Implicit and Splitting Methods / 18.6：
What is ADI, really? / 19.1：
Improvements on the basic ADI scheme / 19.3：
ADI for first-order hyperbolic equations / 19.4：
ADI classico and three-dimensional problems / 19.5：
The Hopscotch method / 19.6：
Boundary conditions / 19.7：
Advanced Operator Splitting Methods: Fractional Steps / 19.8：
Initial examples / 20.1：
Problems with mixed derivatives / 20.3：
Predictor-corrector methods (approximation correctors) / 20.4：
Partial integro-differential equations / 20.5：
More general results / 20.6：
Modern Splitting Methods / 20.7：
A different kind of splitting: The IMEX schemes / 21.1：
Applicability of IMEX schemes to Asian option pricing / 21.4：
Applying FDM to Multi-Factor Instrument Pricing / 21.5：
Options with Stochastic Volatility: The Heston Model / 22：
An introduction to Ornstein-Uhlenbeck processes / 22.1：
Stochastic differential equations and the Heston model / 22.3：
Using finite difference schemes: Prologue / 22.4：
A detailed example / 22.6：
Finite Difference Methods for Asian Options and Other 'Mixed' Problems / 22.7：
An introduction to Asian options / 23.1：
My first PDE formulation / 23.3：
Using operator splitting methods / 23.4：
Cheyette interest models / 23.5：
New developments / 23.6：
Multi-Asset Options / 23.7：
A taxonomy of multi-asset options / 24.1：
Common framework for multi-asset options / 24.3：
An overview of finite difference schemes for multi-asset problems / 24.4：
Numerical solution of elliptic equations / 24.5：
Solving multi-asset Black-Scholes equations / 24.6：
Special guidelines and caveats / 24.7：
Finite Difference Methods for Fixed-Income Problems / 24.8：
An introduction to interest rate modelling / 25.1：
Single-factor models / 25.3：
Some specific stochastic models / 25.4：
An introduction to multidimensional models / 25.5：
The thorny issue of boundary conditions / 25.6：
Introduction to approximate methods for interest rate models / 25.7：
Free and Moving Boundary Value Problems / 25.8：
Background to Free and Moving Boundary Value Problems / 26：
Notation and definitions / 26.1：
Some preliminary examples / 26.3：
Solutions in financial engineering: A preview / 26.4：
Numerical Methods for Free Boundary Value Problems: Front-Fixing Methods / 26.5：
An introduction to front-fixing methods / 27.1：
A crash course on partial derivatives / 27.3：
Functions and implicit forms / 27.4：
Front fixing for the heat equation / 27.5：
Front fixing for general problems / 27.6：
Multidimensional problems / 27.7：
Front fixing and American options / 27.8：
Other finite difference schemes / 27.9：
Viscosity Solutions and Penalty Methods for American Option Problems / 27.10：
Definitions and main results for parabolic problems / 28.1：
An introduction to semi-linear equations and penalty method / 28.3：
Implicit, explicit and semi-implicit schemes / 28.4：
Multi-asset American options / 28.5：
Variational Formulation of American Option Problems / 28.6：
A short history of variational inequalities / 29.1：
A first parabolic variational inequality / 29.3：
Functional analysis background / 29.4：
Kinds of variational inequalities / 29.5：
Variational inequalities using Rothe's methods / 29.6：
American options and variational inequalities / 29.7：
Design and Implementation In C++ / 29.8：
Finding the Appropriate Finite Difference Schemes for your Financial Engineering Problem / 30：
The financial model / 30.1：
The viewpoints in the continuous model / 30.3：
The viewpoints in the discrete model / 30.4：
Auxiliary numerical methods / 30.5：
New Developments / 30.6：
Design and Implementation of First-Order Problems / 30.7：
Software requirements / 31.1：
Modular decomposition / 31.3：
Useful C++ data structures / 31.4：
One-factor models / 31.5：
Multi-factor models / 31.6：
Generalisations and applications to quantitative finance / 31.7：
Appendix: Useful data structures in C++ / 31.8：
Moving to Black-Scholes / 32：
The PDE model / 32.1：
The FDM model / 32.3：
Algorithms and data structures / 32.4：
The C++ model / 32.5：
Test case: The two-dimensional heat equation / 32.6：
Finite difference solution / 32.7：
Moving to software and method implementation / 32.8：
Generalisations / 32.9：
C++ Class Hierarchies for One-Factor and Two-Factor Payoffs / 32.10：
Abstract and concrete payoff classes / 33.1：
Using payoff classes / 33.3：
Lightweight payoff classes / 33.4：
Super-lightweight payoff functions / 33.5：
Payoff functions for multi-asset option problems / 33.6：
Caveat: non-smooth payoff and convergence degradation / 33.7：
Appendices / 33.8：
An introduction to integral and partial integro-differential equations / A1：
An introduction to the finite element method / A2：
Bibliography
Index
Goals of this Book and Global Overview / 0：
What is this book? / 0.1：
Why has this book been written? / 0.2：
3.

電子ブック
ＥＢ
3. C# for Financial Markets
Daniel J. Duffy, Andrea Germani
出版情報: Wiley Online Library - AutoHoldings Books , Chichester : John Wiley & Sons, Incorporated, 2013
所蔵情報: loading…
4.

図書
図書
4. Finite difference methods in financial engineering : a partial differential equation approach
Daniel J. Duffy
出版情報: Chichester : Wiley, c2006  xv, 423 p. ; 26 cm.
シリーズ名: Wiley finance series
所蔵情報: loading…
目次情報: 続きを見る
Goals of this Book and Global Overview / 0：
What is this book? / 0.1：
Why has this book been written? / 0.2：
For whom is this book intended? / 0.3：
Why should I read this book? / 0.4：
The structure of this book / 0.5：
What this book does not cover / 0.6：
Contact, feedback and more information / 0.7：
The Continuous Theory of Partial Differential Equations / Part I：
An Introduction to Ordinary Differential Equations / 1：
Introduction and objectives / 1.1：
Two-point boundary value problem / 1.2：
Linear boundary value problems / 1.3：
Initial value problems / 1.4：
Some special cases / 1.5：
Summary and conclusions / 1.6：
An Introduction to Partial Differential Equations / 2：
Partial differential equations / 2.1：
Specialisations / 2.3：
Parabolic partial differential equations / 2.4：
Hyperbolic equations / 2.5：
Systems of equations / 2.6：
Equations containing integrals / 2.7：
Second-Order Parabolic Differential Equations / 2.8：
Linear parabolic equations / 3.1：
The continuous problem / 3.3：
The maximum principle for parabolic equations / 3.4：
A special case: one-factor generalised Black-Scholes models / 3.5：
Fundamental solution and the Green's function / 3.6：
Integral representation of the solution of parabolic PDEs / 3.7：
Parabolic equations in one space dimension / 3.8：
An Introduction to the Heat Equation in One Dimension / 3.9：
Motivation and background / 4.1：
The heat equation and financial engineering / 4.3：
The separation of variables technique / 4.4：
Transformation techniques for the heat equation / 4.5：
An Introduction to the Method of Characteristics / 4.6：
First-order hyperbolic equations / 5.1：
Second-order hyperbolic equations / 5.3：
Applications to financial engineering / 5.4：
Propagation of discontinuities / 5.5：
Finite Difference Methods: The Fundamentals / 5.7：
An Introduction to the Finite Difference Method / 6：
Fundamentals of numerical differentiation / 6.1：
Caveat: accuracy and round-off errors / 6.3：
Where are divided differences used in instrument pricing? / 6.4：
Nonlinear initial value problems / 6.5：
Scalar initial value problems / 6.7：
An Introduction to the Method of Lines / 6.8：
Classifying semi-discretisation methods / 7.1：
Semi-discretisation in space using FDM / 7.3：
Numerical approximation of first-order systems / 7.4：
General Theory of the Finite Difference Method / 7.5：
Some fundamental concepts / 8.1：
Stability and the Fourier transform / 8.3：
The discrete Fourier transform / 8.4：
Stability for initial boundary value problems / 8.5：
Finite Difference Schemes for First-Order Partial Differential Equations / 8.6：
Scoping the problem / 9.1：
Why first-order equations are different: Essential difficulties / 9.3：
A simple explicit scheme / 9.4：
Some common schemes for initial value problems / 9.5：
Some common schemes for initial boundary value problems / 9.6：
Monotone and positive-type schemes / 9.7：
Extensions, generalisations and other applications / 9.8：
FDM for the One-Dimensional Convection-Diffusion Equation / 9.9：
Approximation of derivatives on the boundaries / 10.1：
Time-dependent convection-diffusion equations / 10.3：
Fully discrete schemes / 10.4：
Specifying initial and boundary conditions / 10.5：
Semi-discretisation in space / 10.6：
Semi-discretisation in time / 10.7：
Exponentially Fitted Finite Difference Schemes / 10.8：
Motivating exponential fitting / 11.1：
Exponential fitting and time-dependent convection-diffusion / 11.3：
Stability and convergence analysis / 11.4：
Approximating the derivative of the solution / 11.5：
Special limiting cases / 11.6：
Applying FDM to One-Factor Instrument Pricing / 11.7：
Exact Solutions and Explicit Finite Difference Method for One-Factor Models / 12：
Exact solutions and benchmark cases / 12.1：
Perturbation analysis and risk engines / 12.3：
The trinomial method: Preview / 12.4：
Using exponential fitting with explicit time marching / 12.5：
Approximating the Greeks / 12.6：
Appendix: the formula for Vega / 12.7：
An Introduction to the Trinomial Method / 13：
Motivating the trinomial method / 13.1：
Trinomial method: Comparisons with other methods / 13.3：
The trinomial method for barrier options / 13.4：
Exponentially Fitted Difference Schemes for Barrier Options / 13.5：
What are barrier options? / 14.1：
Initial boundary value problems for barrier options / 14.3：
Using exponential fitting for barrier options / 14.4：
Time-dependent volatility / 14.5：
Some other kinds of exotic options / 14.6：
Comparisons with exact solutions / 14.7：
Other schemes and approximations / 14.8：
Extensions to the model / 14.9：
Advanced Issues in Barrier and Lookback Option Modelling / 14.10：
Kinds of boundaries and boundary conditions / 15.1：
Discrete and continuous monitoring / 15.3：
Continuity corrections for discrete barrier options / 15.4：
Complex barrier options / 15.5：
The Meshless (Meshfree) Method in Financial Engineering / 15.6：
Motivating the meshless method / 16.1：
An introduction to radial basis functions / 16.3：
Semi-discretisations and convection-diffusion equations / 16.4：
Applications of the one-factor Black-Scholes equation / 16.5：
Advantages and disadvantages of meshless / 16.6：
Extending the Black-Scholes Model: Jump Processes / 16.7：
Jump-diffusion processes / 17.1：
Partial integro-differential equations and financial applications / 17.3：
Numerical solution of PIDE: Preliminaries / 17.4：
Techniques for the numerical solution of PIDEs / 17.5：
Implicit and explicit methods / 17.6：
Implicit-explicit Runge-Kutta methods / 17.7：
Using operator splitting / 17.8：
Splitting and predictor-corrector methods / 17.9：
FDM for Multidimensional Problems / 17.10：
Finite Difference Schemes for Multidimensional Problems / 18：
Elliptic equations / 18.1：
Diffusion and heat equations / 18.3：
Advection equation in two dimensions / 18.4：
Convection-diffusion equation / 18.5：
An Introduction to Alternating Direction Implicit and Splitting Methods / 18.6：
What is ADI, really? / 19.1：
Improvements on the basic ADI scheme / 19.3：
ADI for first-order hyperbolic equations / 19.4：
ADI classico and three-dimensional problems / 19.5：
The Hopscotch method / 19.6：
Boundary conditions / 19.7：
Advanced Operator Splitting Methods: Fractional Steps / 19.8：
Initial examples / 20.1：
Problems with mixed derivatives / 20.3：
Predictor-corrector methods (approximation correctors) / 20.4：
Partial integro-differential equations / 20.5：
More general results / 20.6：
Modern Splitting Methods / 20.7：
A different kind of splitting: The IMEX schemes / 21.1：
Applicability of IMEX schemes to Asian option pricing / 21.4：
Applying FDM to Multi-Factor Instrument Pricing / 21.5：
Options with Stochastic Volatility: The Heston Model / 22：
An introduction to Ornstein-Uhlenbeck processes / 22.1：
Stochastic differential equations and the Heston model / 22.3：
Using finite difference schemes: Prologue / 22.4：
A detailed example / 22.6：
Finite Difference Methods for Asian Options and Other 'Mixed' Problems / 22.7：
An introduction to Asian options / 23.1：
My first PDE formulation / 23.3：
Using operator splitting methods / 23.4：
Cheyette interest models / 23.5：
New developments / 23.6：
Multi-Asset Options / 23.7：
A taxonomy of multi-asset options / 24.1：
Common framework for multi-asset options / 24.3：
An overview of finite difference schemes for multi-asset problems / 24.4：
Numerical solution of elliptic equations / 24.5：
Solving multi-asset Black-Scholes equations / 24.6：
Special guidelines and caveats / 24.7：
Finite Difference Methods for Fixed-Income Problems / 24.8：
An introduction to interest rate modelling / 25.1：
Single-factor models / 25.3：
Some specific stochastic models / 25.4：
An introduction to multidimensional models / 25.5：
The thorny issue of boundary conditions / 25.6：
Introduction to approximate methods for interest rate models / 25.7：
Free and Moving Boundary Value Problems / 25.8：
Background to Free and Moving Boundary Value Problems / 26：
Notation and definitions / 26.1：
Some preliminary examples / 26.3：
Solutions in financial engineering: A preview / 26.4：
Numerical Methods for Free Boundary Value Problems: Front-Fixing Methods / 26.5：
An introduction to front-fixing methods / 27.1：
A crash course on partial derivatives / 27.3：
Functions and implicit forms / 27.4：
Front fixing for the heat equation / 27.5：
Front fixing for general problems / 27.6：
Multidimensional problems / 27.7：
Front fixing and American options / 27.8：
Other finite difference schemes / 27.9：
Viscosity Solutions and Penalty Methods for American Option Problems / 27.10：
Definitions and main results for parabolic problems / 28.1：
An introduction to semi-linear equations and penalty method / 28.3：
Implicit, explicit and semi-implicit schemes / 28.4：
Multi-asset American options / 28.5：
Variational Formulation of American Option Problems / 28.6：
A short history of variational inequalities / 29.1：
A first parabolic variational inequality / 29.3：
Functional analysis background / 29.4：
Kinds of variational inequalities / 29.5：
Variational inequalities using Rothe's methods / 29.6：
American options and variational inequalities / 29.7：
Design and Implementation In C++ / 29.8：
Finding the Appropriate Finite Difference Schemes for your Financial Engineering Problem / 30：
The financial model / 30.1：
The viewpoints in the continuous model / 30.3：
The viewpoints in the discrete model / 30.4：
Auxiliary numerical methods / 30.5：
New Developments / 30.6：
Design and Implementation of First-Order Problems / 30.7：
Software requirements / 31.1：
Modular decomposition / 31.3：
Useful C++ data structures / 31.4：
One-factor models / 31.5：
Multi-factor models / 31.6：
Generalisations and applications to quantitative finance / 31.7：
Appendix: Useful data structures in C++ / 31.8：
Moving to Black-Scholes / 32：
The PDE model / 32.1：
The FDM model / 32.3：
Algorithms and data structures / 32.4：
The C++ model / 32.5：
Test case: The two-dimensional heat equation / 32.6：
Finite difference solution / 32.7：
Moving to software and method implementation / 32.8：
Generalisations / 32.9：
C++ Class Hierarchies for One-Factor and Two-Factor Payoffs / 32.10：
Abstract and concrete payoff classes / 33.1：
Using payoff classes / 33.3：
Lightweight payoff classes / 33.4：
Super-lightweight payoff functions / 33.5：
Payoff functions for multi-asset option problems / 33.6：
Caveat: non-smooth payoff and convergence degradation / 33.7：
Appendices / 33.8：
An introduction to integral and partial integro-differential equations / A1：
An introduction to the finite element method / A2：
Bibliography
Index
Goals of this Book and Global Overview / 0：
What is this book? / 0.1：
Why has this book been written? / 0.2：
5.

図書
図書
5. Monte Carlo frameworks : building customisable high-performance C++ applications (: hbk)
Daniel J. Duffy, Jörg Kienitz
出版情報: Chichester, U.K. : Wiley, 2009  xxv, 750 p. ; 26 cm.
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目次情報: 続きを見る
Preface
My First Monte Carlo Application One-Factor Problems / Chapter 0：
Mathematical Preparations for the Monte Carlo Method / Chapter 1：
The Mathematics of Stochastic Differential Equations (SDE) / Chapter 2：
Alternative SDEs and Toolkit Functionality / Chapter 3：
An Introduction to the Finite Difference Method for SDE / Chapter 4：
Design and Implementation of Finite Difference Schemes in Computational Finance / Chapter 5：
Advanced Finance Models and Numerical Methods / Chapter 6：
Architectures and Frameworks for Monte Carlo Methods: Overview / Chapter 8：
System Decomposition and System Patterns / Chapter 9：
Detailed Design using the GOF Patterns / Chapter 10：
Combining Object-Oriented and Generic Programming Models / Chapter 11：
Data Structures and their Application to the Monte Carlo Method / Chapter 12：
The Boost Library: An Introduction / Chapter 13：
C++ Application Optimisation and Performance Improvement / Chapter 21：
An Introduction to Multi-threaded and Parallel Programming / Chapter 24：
An Introduction to OpenMP and its Applications to the Monte Carlo Method / Chapter 25：
Excel, C++ and Monte Carlo Integration / Chapter 27：
Preface
My First Monte Carlo Application One-Factor Problems / Chapter 0：
Mathematical Preparations for the Monte Carlo Method / Chapter 1：
6.

電子ブック
ＥＢ
6. Introduction to C++ for financial engineers : an object-oriented approach (: electronic bk)
Daniel J. Duffy
出版情報: [Hoboken, N.J.] : Wiley Online Library, 2013  1 online resource (xiii, 424 p.)
シリーズ名: Wiley finance series ;
所蔵情報: loading…
目次情報: 続きを見る
Goals of this Book and Global Overview / 0：
C++ Essential Skills / Part I：
Introduction to C++ and Quantitative Finance / 1：
The Mechanics of C++: from Source Code to a Running Program / 2：
C++ Fundamentals and My First Option Class / 3：
Creating Robust Classes / 4：
Operator Overloading in C++ / 5：
Memory Management in C++ / 6：
Functions, Namespaces and Introduction to Inheritance / 7：
Advanced Inheritance and Payoff Class Hierarchies / 8：
Run-Time Behaviour in C++ / 9：
An Introduction to C++ Templates / 10：
Data Structures, Templates and Patterns / Part II：
Introduction to Generic Data Structures and Standard Template Library (STL) / 11：
Creating Simpler Interfaces to STL for QF Applications / 12：
Data Structures for Financial Engineering Applications / 13：
An Introduction to Design Patterns / 14：
QF Applications / Part III：
Programming the Binomial Method in C++ / 15：
Implementing One-Factor Black Scholes in C++ / 16：
Two-Factor Option Pricing: Basket and Other multi-Asset Options / 17：
Useful C++ Classes for Numerical Analysis Applications in Finance / 18：
Other Numerical Methods in Quantitative Finance / 19：
The Monte Carlo Method Theory and C++ Frameworks / 20：
Skills Development: from White Belt to Black Belt / 21：
Background Information / Part IV：
Basic C Survival Guide / 22：
Advanced C Syntax / 23：
Datasim Visualisation Package in Excel: Drivers and Mechanisms / 24：
Motivating COM and Emulation in C++ / 25：
COM Fundamentals / 26：
References
Index
Goals of this Book and Global Overview / 0：
C++ Essential Skills / Part I：
Introduction to C++ and Quantitative Finance / 1：
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