Fifteen years have elapsed after the second edition of Practical Bifurcation and Stability Analysis was published. During that time period the ?eld of computational bifurcation has become mature. Today, bifurcation mec- nisms are widely accepted as decisive phenomena for explaining and - derstanding stability and structural change. Along with the high level of sophistication that bifurcation analysis has reached, the research on basic computational bifurcation algorithms is essentially completed, at least in - dinary di?erential equations. The focus has been shifting from mathematical foundations towards applications. The evolution from equilibrium to chaos has become commonplace and is no longer at the cutting edge of innovation. But the corresponding methods of practical bifurcation and stability analysis remain indispensable instruments in all applications of mathematics. This constant need for practical bifur- tion and stability analysis has stimulated an e?ort to maintain this book on a present-day level. The author’s endeavor has resulted in this third edition. It is based on more than three decades of practical experience with the subject, and on many courses given at several universities.

Fifteen years have elapsed after the second edition of Practical Bifurcation and Stability Analysis was published. During that time period the ?eld of computational bifurcation has become mature. Today, bifurcation mec- nisms are widely accepted as decisive phenomena for explaining and - derstanding stability and structural change. Along with the high level of sophistication that bifurcation analysis has reached, the research on basic computational bifurcation algorithms is essentially completed, at least in - dinary di?erential equations. The focus has been shifting from mathematical foundations towards applications. The evolution from equilibrium to chaos has become commonplace and is no longer at the cutting edge of innovation. But the corresponding methods of practical bifurcation and stability analysis remain indispensable instruments in all applications of mathematics. This constant need for practical bifur- tion and stability analysis has stimulated an e?ort to maintain this book on a present-day level. The author’s endeavor has resulted in this third edition. It is based on more than three decades of practical experience with the subject, and on many courses given at several universities.

The disciplines of financial engineering and numerical computation differ greatly, however computational methods are used in a number of ways across the field of finance. It is the aim of this book to explain how such methods work in financial engineering; specifically the use of numerical methods as tools for computational finance. By concentrating on the field of option pricing, a core task of financial engineering and risk analysis, this book explores a wide range of computational tools in a coherent and focused manner and will be of use to the entire field of computational finance. Starting with an introductory chapter that presents the financial and stochastic background, the remainder of the book goes on to detail computational methods using both stochastic and deterministic approaches.

Now in its fifth edition, Tools for Computational Finance has been significantly revised and contains:

A new chapter on incomplete markets which links to new appendices on Viscosity solutions and the Dupire equation;Several new parts throughout the book such as that on the calculation of sensitivities (Sect. 3.7) and the introduction of penalty methods and their application to a two-factor model (Sect. 6.7)Additional material in the field of analytical methods including Kim’s integral representation and its computationGuidelines for comparing algorithms and judging their efficiencyAn extended chapter on finite elements that now includes a discussion of two-asset optionsAdditional exercises, figures and references

Written from the perspective of an applied mathematician, methods are introduced as tools within the book for immediate and straightforward application. A ‘learning by calculating’ approach is adopted throughout this book enabling readers to explore several areas of the financial world.

Interdisciplinary in nature, this book will appeal to advanced undergraduate students inmathematics, engineering and other scientific disciplines as well as professionals in financial engineering.

Computational and numerical methods are used in a number of ways across the field of finance. It is the aim of this book to explain how such methods work in financial engineering. By concentrating on the field of option pricing, a core task of financial engineering and risk analysis, this book explores a wide range of computational tools in a coherent and focused manner and will be of use to anyone working in computational finance. Starting with an introductory chapter that presents the financial and stochastic background, the book goes on to detail computational methods using both stochastic and deterministic approaches.Now in its sixth edition, Tools for Computational Finance has been significantly revised and contains:   Several new parts such as a section on extended applications of tree methods, including multidimensional trees, trinomial trees, and the handling of dividends;Additional material in the field of generating normal variates with acceptance-rejection methods, and on Monte Carlo methods;115 exercises, and more than 100 figures, many in color.Written from the perspective of an applied mathematician, all methods are introduced for immediate and straightforward application. A ‘learning by calculating’ approach is adopted throughout this book, enabling readers to explore several areas of the financial world.Interdisciplinary in nature, this book will appeal to advanced undergraduate and graduate students in mathematics, engineering, and other scientific disciplines as well as professionals in financial engineering.

Computational and numerical methods are used in a number of ways across the field of finance. It is the aim of this book to explain how such methods work in financial engineering. By concentrating on the field of option pricing, a core task of financial engineering and risk analysis, this book explores a wide range of computational tools in a coherent and focused manner and will be of use to anyone working in computational finance. Starting with an introductory chapter that presents the financial and stochastic background, the book goes on to detail computational methods using both stochastic and deterministic approaches.

Now in its sixth edition, Tools for Computational Finance has been significantly revised and contains:   

Several new parts such as a section on extended applications of tree methods, including multidimensional trees, trinomial trees, and the handling of dividends;Additional material in the field of generating normal variates with acceptance-rejection methods, and on Monte Carlo methods;115 exercises, and more than 100 figures, many in color.

Written from the perspective of an applied mathematician, all methods are introduced for immediate and straightforward application. A ‘learning by calculating’ approach is adopted throughout this book, enabling readers to explore several areas of the financial world.

Interdisciplinary in nature, this book will appeal to advanced undergraduate and graduate students in mathematics, engineering, and other scientific disciplines as well as professionals in financial engineering.

Fifteen years have elapsed after the second edition of Practical Bifurcation and Stability Analysis was published. During that time period the ?eld of computational bifurcation has become mature. Today, bifurcation mec- nisms are widely accepted as decisive phenomena for explaining and - derstanding stability and structural change. Along with the high level of sophistication that bifurcation analysis has reached, the research on basic computational bifurcation algorithms is essentially completed, at least in - dinary di?erential equations. The focus has been shifting from mathematical foundations towards applications. The evolution from equilibrium to chaos has become commonplace and is no longer at the cutting edge of innovation. But the corresponding methods of practical bifurcation and stability analysis remain indispensable instruments in all applications of mathematics. This constant need for practical bifur- tion and stability analysis has stimulated an e?ort to maintain this book on a present-day level. The author’s endeavor has resulted in this third edition. It is based on more than three decades of practical experience with the subject, and on many courses given at several universities.

Basic principles underlying the transactions of ?nancial markets are tied to probability and statistics. Accordingly it is natural that books devoted to mathematical ?nance are dominated by stochastic methods. Only in recent years, spurred by the enormous economical success of ?nancial derivatives, a need for sophisticated computational technology has developed. For - ample, to price an American put, quantitative analysts have asked for the numerical solution of a free-boundary partial di?erential equation. Fast and accurate numerical algorithms have become essential tools to price ?nancial derivatives and to manage portfolio risks. The required methods aggregate to the new ?eld of Computational Finance. This discipline still has an aura of mysteriousness; the ?rst specialists were sometimes called rocket scientists. So far, the emerging ?eld of computational ?nance has hardly been discussed in the mathematical ?nance literature. This book attempts to ?ll the gap. Basic principles of computational ?nance are introduced in a monograph with textbook character. The book is divided into four parts, arranged in six chapters and seven appendices. The general organization is Part I (Chapter 1): Financial and Stochastic Background Part II (Chapters 2, 3): Tools for Simulation Part III (Chapters 4, 5, 6): Partial Di?erential Equations for Options PartIV(AppendicesA1...A7):FurtherRequisitsandAdditionalMaterial.

Basic principles underlying the transactions of ?nancial markets are tied to probability and statistics. Accordingly it is natural that books devoted to mathematical ?nance are dominated by stochastic methods. Only in recent years, spurred by the enormous economical success of ?nancial derivatives, a need for sophisticated computational technology has developed. For - ample, to price an American put, quantitative analysts have asked for the numerical solution of a free-boundary partial di?erential equation. Fast and accurate numerical algorithms have become essential tools to price ?nancial derivatives and to manage portfolio risks. The required methods aggregate to the new ?eld of Computational Finance. This discipline still has an aura of mysteriousness; the ?rst specialists were sometimes called rocket scientists. So far, the emerging ?eld of computational ?nance has hardly been discussed in the mathematical ?nance literature. This book attempts to ?ll the gap. Basic principles of computational ?nance are introduced in a monograph with textbook character. The book is divided into four parts, arranged in six chapters and seven appendices. The general organization is Part I (Chapter 1): Financial and Stochastic Background Part II (Chapters 2, 3): Tools for Simulation Part III (Chapters 4, 5, 6): Partial Di?erential Equations for Options PartIV(AppendicesA1...A7):FurtherRequisitsandAdditionalMaterial.

In jüngster Zeit haben Finanz-Derivate eine starke Verbreitung erfahren. Das vorliegende Lehrbuch bietet eine elementare Einführung in diejenigen Methoden der Numerik und des Wissenschaftichen Rechnens, die insbesondere für die Berechung von Optionspreisen grundlegend sind. Nach einer kurzen Beschreibung der Modellierung von Standard-Optionen folgt als erster Hauptteil die numerische Simulation der Stochastik mit der Berechnung von Zufallszahlen, der Integration von stochastischen Differentialgleichungen und dem Einsatz von Monte-Carlo-Verfahren. Der zweite Hauptteil konzentriert sich auf die Numerik zu den Black-Scholes Ansätzen mit partiellen Differential-Gleichungen und -Ungleichungen. Dabei werden Lösungsalgorithmen von Differenzenverfahren und von Finite-Element-Verfahren erklärt. Übungsaufgaben, instruktive Abbildungen sowie themenbezogene Anhänge runden das Buch ab. Lösungshinweise zu ausgewählten Aufgaben werden unter http://www.mi.uni-koeln.de/numerik/compfin/ bereitgestellt.

Basic principles underlying the transactions of financial markets are tied to probability and statistics. Accordingly it is natural that books devoted to mathematical finance are dominated by stochastic methods. Only in recent years, spurred by the enormous economical success of financial derivatives, a need for sophisticated computational technology has developed. For ex­ ample, to price an American put, quantitative analysts have asked for the numerical solution of a free-boundary partial differential equation. Fast and accurate numerical algorithms have become essential tools to price financial derivatives and to manage portfolio risks. The required methods aggregate to the new field of Computational Finance. This discipline still has an aura of mysteriousness; the first specialists were sometimes called rocket scientists. So far, the emerging field of computational finance has hardly been discussed in the mathematical finance literature. This book attempts to fill the gap. Basic principles of computational finance are introduced in a monograph with textbook character. The book is divided into four parts, arranged in six chapters and seven appendices. The general organization is Part I (Chapter 1): Financial and Stochastic Background Part II (Chapters 2, 3): Tools for Simulation Part III (Chapters 4, 5, 6): Partial Differential Equations for Options Part IV (Appendices A1 ... A7): Further Requisits and Additional Material.

Fifteen years have elapsed after the second edition of Practical Bifurcation and Stability Analysis was published. During that time period the ?eld of computational bifurcation has become mature. Today, bifurcation mec- nisms are widely accepted as decisive phenomena for explaining and - derstanding stability and structural change. Along with the high level of sophistication that bifurcation analysis has reached, the research on basic computational bifurcation algorithms is essentially completed, at least in - dinary di?erential equations. The focus has been shifting from mathematical foundations towards applications. The evolution from equilibrium to chaos has become commonplace and is no longer at the cutting edge of innovation. But the corresponding methods of practical bifurcation and stability analysis remain indispensable instruments in all applications of mathematics. This constant need for practical bifur- tion and stability analysis has stimulated an e?ort to maintain this book on a present-day level. The author’s endeavor has resulted in this third edition. It is based on more than three decades of practical experience with the subject, and on many courses given at several universities.

Fifteen years have elapsed after the second edition of Practical Bifurcation and Stability Analysis was published. During that time period the ?eld of computational bifurcation has become mature. Today, bifurcation mec- nisms are widely accepted as decisive phenomena for explaining and - derstanding stability and structural change. Along with the high level of sophistication that bifurcation analysis has reached, the research on basic computational bifurcation algorithms is essentially completed, at least in - dinary di?erential equations. The focus has been shifting from mathematical foundations towards applications. The evolution from equilibrium to chaos has become commonplace and is no longer at the cutting edge of innovation. But the corresponding methods of practical bifurcation and stability analysis remain indispensable instruments in all applications of mathematics. This constant need for practical bifur- tion and stability analysis has stimulated an e?ort to maintain this book on a present-day level. The author’s endeavor has resulted in this third edition. It is based on more than three decades of practical experience with the subject, and on many courses given at several universities.

The disciplines of financial engineering and numerical computation differ greatly, however computational methods are used in a number of ways across the field of finance. It is the aim of this book to explain how such methods work in financial engineering; specifically the use of numerical methods as tools for computational finance. By concentrating on the field of option pricing, a core task of financial engineering and risk analysis, this book explores a wide range of computational tools in a coherent and focused manner and will be of use to the entire field of computational finance. Starting with an introductory chapter that presents the financial and stochastic background, the remainder of the book goes on to detail computational methods using both stochastic and deterministic approaches.

Now in its fifth edition, Tools for Computational Finance has been significantly revised and contains:

A new chapter on incomplete markets which links to new appendices on Viscosity solutions and the Dupire equation;Several new parts throughout the book such as that on the calculation of sensitivities (Sect. 3.7) and the introduction of penalty methods and their application to a two-factor model (Sect. 6.7)Additional material in the field of analytical methods including Kim’s integral representation and its computationGuidelines for comparing algorithms and judging their efficiencyAn extended chapter on finite elements that now includes a discussion of two-asset optionsAdditional exercises, figures and references

Written from the perspective of an applied mathematician, methods are introduced as tools within the book for immediate and straightforward application. A ‘learning by calculating’ approach is adopted throughout this book enabling readers to explore several areas of the financial world.

Interdisciplinary in nature, this book will appeal to advanced undergraduate students inmathematics, engineering and other scientific disciplines as well as professionals in financial engineering.

Computational and numerical methods are used in a number of ways across the field of finance. It is the aim of this book to explain how such methods work in financial engineering. By concentrating on the field of option pricing, a core task of financial engineering and risk analysis, this book explores a wide range of computational tools in a coherent and focused manner and will be of use to anyone working in computational finance. Starting with an introductory chapter that presents the financial and stochastic background, the book goes on to detail computational methods using both stochastic and deterministic approaches.Now in its sixth edition, Tools for Computational Finance has been significantly revised and contains:   Several new parts such as a section on extended applications of tree methods, including multidimensional trees, trinomial trees, and the handling of dividends;Additional material in the field of generating normal variates with acceptance-rejection methods, and on Monte Carlo methods;115 exercises, and more than 100 figures, many in color.Written from the perspective of an applied mathematician, all methods are introduced for immediate and straightforward application. A ‘learning by calculating’ approach is adopted throughout this book, enabling readers to explore several areas of the financial world.Interdisciplinary in nature, this book will appeal to advanced undergraduate and graduate students in mathematics, engineering, and other scientific disciplines as well as professionals in financial engineering.

Computational and numerical methods are used in a number of ways across the field of finance. It is the aim of this book to explain how such methods work in financial engineering. By concentrating on the field of option pricing, a core task of financial engineering and risk analysis, this book explores a wide range of computational tools in a coherent and focused manner and will be of use to anyone working in computational finance. Starting with an introductory chapter that presents the financial and stochastic background, the book goes on to detail computational methods using both stochastic and deterministic approaches.

Now in its sixth edition, Tools for Computational Finance has been significantly revised and contains:   

Several new parts such as a section on extended applications of tree methods, including multidimensional trees, trinomial trees, and the handling of dividends;Additional material in the field of generating normal variates with acceptance-rejection methods, and on Monte Carlo methods;115 exercises, and more than 100 figures, many in color.

Written from the perspective of an applied mathematician, all methods are introduced for immediate and straightforward application. A ‘learning by calculating’ approach is adopted throughout this book, enabling readers to explore several areas of the financial world.

Interdisciplinary in nature, this book will appeal to advanced undergraduate and graduate students in mathematics, engineering, and other scientific disciplines as well as professionals in financial engineering.

Fifteen years have elapsed after the second edition of Practical Bifurcation and Stability Analysis was published. During that time period the ?eld of computational bifurcation has become mature. Today, bifurcation mec- nisms are widely accepted as decisive phenomena for explaining and - derstanding stability and structural change. Along with the high level of sophistication that bifurcation analysis has reached, the research on basic computational bifurcation algorithms is essentially completed, at least in - dinary di?erential equations. The focus has been shifting from mathematical foundations towards applications. The evolution from equilibrium to chaos has become commonplace and is no longer at the cutting edge of innovation. But the corresponding methods of practical bifurcation and stability analysis remain indispensable instruments in all applications of mathematics. This constant need for practical bifur- tion and stability analysis has stimulated an e?ort to maintain this book on a present-day level. The author’s endeavor has resulted in this third edition. It is based on more than three decades of practical experience with the subject, and on many courses given at several universities.

Basic principles underlying the transactions of ?nancial markets are tied to probability and statistics. Accordingly it is natural that books devoted to mathematical ?nance are dominated by stochastic methods. Only in recent years, spurred by the enormous economical success of ?nancial derivatives, a need for sophisticated computational technology has developed. For - ample, to price an American put, quantitative analysts have asked for the numerical solution of a free-boundary partial di?erential equation. Fast and accurate numerical algorithms have become essential tools to price ?nancial derivatives and to manage portfolio risks. The required methods aggregate to the new ?eld of Computational Finance. This discipline still has an aura of mysteriousness; the ?rst specialists were sometimes called rocket scientists. So far, the emerging ?eld of computational ?nance has hardly been discussed in the mathematical ?nance literature. This book attempts to ?ll the gap. Basic principles of computational ?nance are introduced in a monograph with textbook character. The book is divided into four parts, arranged in six chapters and seven appendices. The general organization is Part I (Chapter 1): Financial and Stochastic Background Part II (Chapters 2, 3): Tools for Simulation Part III (Chapters 4, 5, 6): Partial Di?erential Equations for Options PartIV(AppendicesA1...A7):FurtherRequisitsandAdditionalMaterial.

Basic principles underlying the transactions of ?nancial markets are tied to probability and statistics. Accordingly it is natural that books devoted to mathematical ?nance are dominated by stochastic methods. Only in recent years, spurred by the enormous economical success of ?nancial derivatives, a need for sophisticated computational technology has developed. For - ample, to price an American put, quantitative analysts have asked for the numerical solution of a free-boundary partial di?erential equation. Fast and accurate numerical algorithms have become essential tools to price ?nancial derivatives and to manage portfolio risks. The required methods aggregate to the new ?eld of Computational Finance. This discipline still has an aura of mysteriousness; the ?rst specialists were sometimes called rocket scientists. So far, the emerging ?eld of computational ?nance has hardly been discussed in the mathematical ?nance literature. This book attempts to ?ll the gap. Basic principles of computational ?nance are introduced in a monograph with textbook character. The book is divided into four parts, arranged in six chapters and seven appendices. The general organization is Part I (Chapter 1): Financial and Stochastic Background Part II (Chapters 2, 3): Tools for Simulation Part III (Chapters 4, 5, 6): Partial Di?erential Equations for Options PartIV(AppendicesA1...A7):FurtherRequisitsandAdditionalMaterial.

In jüngster Zeit haben Finanz-Derivate eine starke Verbreitung erfahren. Das vorliegende Lehrbuch bietet eine elementare Einführung in diejenigen Methoden der Numerik und des Wissenschaftichen Rechnens, die insbesondere für die Berechung von Optionspreisen grundlegend sind. Nach einer kurzen Beschreibung der Modellierung von Standard-Optionen folgt als erster Hauptteil die numerische Simulation der Stochastik mit der Berechnung von Zufallszahlen, der Integration von stochastischen Differentialgleichungen und dem Einsatz von Monte-Carlo-Verfahren. Der zweite Hauptteil konzentriert sich auf die Numerik zu den Black-Scholes Ansätzen mit partiellen Differential-Gleichungen und -Ungleichungen. Dabei werden Lösungsalgorithmen von Differenzenverfahren und von Finite-Element-Verfahren erklärt. Übungsaufgaben, instruktive Abbildungen sowie themenbezogene Anhänge runden das Buch ab. Lösungshinweise zu ausgewählten Aufgaben werden unter http://www.mi.uni-koeln.de/numerik/compfin/ bereitgestellt.

Basic principles underlying the transactions of financial markets are tied to probability and statistics. Accordingly it is natural that books devoted to mathematical finance are dominated by stochastic methods. Only in recent years, spurred by the enormous economical success of financial derivatives, a need for sophisticated computational technology has developed. For ex­ ample, to price an American put, quantitative analysts have asked for the numerical solution of a free-boundary partial differential equation. Fast and accurate numerical algorithms have become essential tools to price financial derivatives and to manage portfolio risks. The required methods aggregate to the new field of Computational Finance. This discipline still has an aura of mysteriousness; the first specialists were sometimes called rocket scientists. So far, the emerging field of computational finance has hardly been discussed in the mathematical finance literature. This book attempts to fill the gap. Basic principles of computational finance are introduced in a monograph with textbook character. The book is divided into four parts, arranged in six chapters and seven appendices. The general organization is Part I (Chapter 1): Financial and Stochastic Background Part II (Chapters 2, 3): Tools for Simulation Part III (Chapters 4, 5, 6): Partial Differential Equations for Options Part IV (Appendices A1 ... A7): Further Requisits and Additional Material.