Author: Mark S. Joshi
Publisher: Cambridge University Press
ISBN: 0521514088
Category : Business & Economics
Languages : en
Pages : 0
Book Description
The second edition of a successful text providing the working knowledge needed to become a good quantitative analyst. An ideal introduction to mathematical finance, readers will gain a clear understanding of the intuition behind derivatives pricing, how models are implemented, and how they are used and adapted in practice.
The Concepts and Practice of Mathematical Finance
Author: Mark S. Joshi
Publisher: Cambridge University Press
ISBN: 0521514088
Category : Business & Economics
Languages : en
Pages : 0
Book Description
The second edition of a successful text providing the working knowledge needed to become a good quantitative analyst. An ideal introduction to mathematical finance, readers will gain a clear understanding of the intuition behind derivatives pricing, how models are implemented, and how they are used and adapted in practice.
Publisher: Cambridge University Press
ISBN: 0521514088
Category : Business & Economics
Languages : en
Pages : 0
Book Description
The second edition of a successful text providing the working knowledge needed to become a good quantitative analyst. An ideal introduction to mathematical finance, readers will gain a clear understanding of the intuition behind derivatives pricing, how models are implemented, and how they are used and adapted in practice.
More Mathematical Finance
Author: Mark Suresh Joshi
Publisher:
ISBN: 9780987122803
Category : Business & Economics
Languages : en
Pages : 484
Book Description
The long-awaited sequel to the "Concepts and Practice of Mathematical Finance" has now arrived. Taking up where the first volume left off, a range of topics is covered in depth. Extensive sections include portfolio credit derivatives, quasi-Monte Carlo, the calibration and implementation of the LIBOR market model, the acceleration of binomial trees, the Fourier transform in option pricing and much more. Throughout Mark Joshi brings his unique blend of theory, lucidity, practicality and experience to bear on issues relevant to the working quantitative analyst. "More Mathematical Finance" is Mark Joshi's fourth book. His previous books including "C++ Design Patterns and Derivatives Pricing" and "Quant Job Interview Questions and Answers" have proven to be indispensable for individuals seeking to become quantitative analysts. His new book continues this trend with a clear exposition of a range of models and techniques in the field of derivatives pricing. Each chapter is accompanied by a set of exercises. These are of a variety of types including simple proofs, complicated derivations and computer projects. Chapter 1. Optionality, convexity and volatility 1 Chapter 2. Where does the money go? 9 Chapter 3. The Bachelier model 23 Chapter 4. Deriving the Delta 29 Chapter 5. Volatility derivatives and model-free dynamic replication 33 Chapter 6. Credit derivatives 41 Chapter 7. The Monte Carlo pricing of portfolio credit derivatives 53 Chapter 8. Quasi-analytic methods for pricing portfolio credit derivatives 71 Chapter 9. Implied correlation for portfolio credit derivatives 81 Chapter 10. Alternate models for portfolio credit derivatives 93 Chapter 11. The non-commutativity of discretization 113 Chapter 12. What is a factor? 129 Chapter 13. Early exercise and Monte Carlo Simulation 151 Chapter 14. The Brownian bridge 175 Chapter 15. Quasi Monte Carlo Simulation 185 Chapter 16. Pricing continuous barrier options using a jump-diffusion model 207 Chapter 17. The Fourier-Laplace transform and option pricing 219 Chapter 18. The cos method 253 Chapter 19. What are market models? 265 Chapter 20. Discounting in market models 281 Chapter 21. Drifts again 293 Chapter 22. Adjoint and automatic Greeks 307 Chapter 23. Estimating correlation for the LIBOR market model 327 Chapter 24. Swap-rate market models 341 Chapter 25. Calibrating market models 363 Chapter 26. Cross-currency market models 389 Chapter 27. Mixture models 401 Chapter 28. The convergence of binomial trees 407 Chapter 29. Asymmetry in option pricing 433 Chapter 30. A perfect model? 443 Chapter 31. The fundamental theorem of asset pricing. 449 Appendix A. The discrete Fourier transform 457 Praise for the Concepts and Practice of Mathematical Finance: "overshadows many other books available on the same subject" -- ZentralBlatt Math "Mark Joshi succeeds admirably - an excellent starting point for a numerate person in the field of mathematical finance." -- Risk Magazine "Very few books provide a balance between financial theory and practice. This book is one of the few books that strikes that balance." -- SIAM Review
Publisher:
ISBN: 9780987122803
Category : Business & Economics
Languages : en
Pages : 484
Book Description
The long-awaited sequel to the "Concepts and Practice of Mathematical Finance" has now arrived. Taking up where the first volume left off, a range of topics is covered in depth. Extensive sections include portfolio credit derivatives, quasi-Monte Carlo, the calibration and implementation of the LIBOR market model, the acceleration of binomial trees, the Fourier transform in option pricing and much more. Throughout Mark Joshi brings his unique blend of theory, lucidity, practicality and experience to bear on issues relevant to the working quantitative analyst. "More Mathematical Finance" is Mark Joshi's fourth book. His previous books including "C++ Design Patterns and Derivatives Pricing" and "Quant Job Interview Questions and Answers" have proven to be indispensable for individuals seeking to become quantitative analysts. His new book continues this trend with a clear exposition of a range of models and techniques in the field of derivatives pricing. Each chapter is accompanied by a set of exercises. These are of a variety of types including simple proofs, complicated derivations and computer projects. Chapter 1. Optionality, convexity and volatility 1 Chapter 2. Where does the money go? 9 Chapter 3. The Bachelier model 23 Chapter 4. Deriving the Delta 29 Chapter 5. Volatility derivatives and model-free dynamic replication 33 Chapter 6. Credit derivatives 41 Chapter 7. The Monte Carlo pricing of portfolio credit derivatives 53 Chapter 8. Quasi-analytic methods for pricing portfolio credit derivatives 71 Chapter 9. Implied correlation for portfolio credit derivatives 81 Chapter 10. Alternate models for portfolio credit derivatives 93 Chapter 11. The non-commutativity of discretization 113 Chapter 12. What is a factor? 129 Chapter 13. Early exercise and Monte Carlo Simulation 151 Chapter 14. The Brownian bridge 175 Chapter 15. Quasi Monte Carlo Simulation 185 Chapter 16. Pricing continuous barrier options using a jump-diffusion model 207 Chapter 17. The Fourier-Laplace transform and option pricing 219 Chapter 18. The cos method 253 Chapter 19. What are market models? 265 Chapter 20. Discounting in market models 281 Chapter 21. Drifts again 293 Chapter 22. Adjoint and automatic Greeks 307 Chapter 23. Estimating correlation for the LIBOR market model 327 Chapter 24. Swap-rate market models 341 Chapter 25. Calibrating market models 363 Chapter 26. Cross-currency market models 389 Chapter 27. Mixture models 401 Chapter 28. The convergence of binomial trees 407 Chapter 29. Asymmetry in option pricing 433 Chapter 30. A perfect model? 443 Chapter 31. The fundamental theorem of asset pricing. 449 Appendix A. The discrete Fourier transform 457 Praise for the Concepts and Practice of Mathematical Finance: "overshadows many other books available on the same subject" -- ZentralBlatt Math "Mark Joshi succeeds admirably - an excellent starting point for a numerate person in the field of mathematical finance." -- Risk Magazine "Very few books provide a balance between financial theory and practice. This book is one of the few books that strikes that balance." -- SIAM Review
Advances in Mathematical Finance
Author: Michael C. Fu
Publisher: Springer Science & Business Media
ISBN: 0817645454
Category : Business & Economics
Languages : en
Pages : 345
Book Description
This self-contained volume brings together a collection of chapters by some of the most distinguished researchers and practitioners in the field of mathematical finance and financial engineering. Presenting state-of-the-art developments in theory and practice, the book has real-world applications to fixed income models, credit risk models, CDO pricing, tax rebates, tax arbitrage, and tax equilibrium. It is a valuable resource for graduate students, researchers, and practitioners in mathematical finance and financial engineering.
Publisher: Springer Science & Business Media
ISBN: 0817645454
Category : Business & Economics
Languages : en
Pages : 345
Book Description
This self-contained volume brings together a collection of chapters by some of the most distinguished researchers and practitioners in the field of mathematical finance and financial engineering. Presenting state-of-the-art developments in theory and practice, the book has real-world applications to fixed income models, credit risk models, CDO pricing, tax rebates, tax arbitrage, and tax equilibrium. It is a valuable resource for graduate students, researchers, and practitioners in mathematical finance and financial engineering.
Mathematical Finance
Author: Christian Fries
Publisher: John Wiley & Sons
ISBN: 9780470179772
Category : Mathematics
Languages : en
Pages : 512
Book Description
A balanced introduction to the theoretical foundations and real-world applications of mathematical finance The ever-growing use of derivative products makes it essential for financial industry practitioners to have a solid understanding of derivative pricing. To cope with the growing complexity, narrowing margins, and shortening life-cycle of the individual derivative product, an efficient, yet modular, implementation of the pricing algorithms is necessary. Mathematical Finance is the first book to harmonize the theory, modeling, and implementation of today's most prevalent pricing models under one convenient cover. Building a bridge from academia to practice, this self-contained text applies theoretical concepts to real-world examples and introduces state-of-the-art, object-oriented programming techniques that equip the reader with the conceptual and illustrative tools needed to understand and develop successful derivative pricing models. Utilizing almost twenty years of academic and industry experience, the author discusses the mathematical concepts that are the foundation of commonly used derivative pricing models, and insightful Motivation and Interpretation sections for each concept are presented to further illustrate the relationship between theory and practice. In-depth coverage of the common characteristics found amongst successful pricing models are provided in addition to key techniques and tips for the construction of these models. The opportunity to interactively explore the book's principal ideas and methodologies is made possible via a related Web site that features interactive Java experiments and exercises. While a high standard of mathematical precision is retained, Mathematical Finance emphasizes practical motivations, interpretations, and results and is an excellent textbook for students in mathematical finance, computational finance, and derivative pricing courses at the upper undergraduate or beginning graduate level. It also serves as a valuable reference for professionals in the banking, insurance, and asset management industries.
Publisher: John Wiley & Sons
ISBN: 9780470179772
Category : Mathematics
Languages : en
Pages : 512
Book Description
A balanced introduction to the theoretical foundations and real-world applications of mathematical finance The ever-growing use of derivative products makes it essential for financial industry practitioners to have a solid understanding of derivative pricing. To cope with the growing complexity, narrowing margins, and shortening life-cycle of the individual derivative product, an efficient, yet modular, implementation of the pricing algorithms is necessary. Mathematical Finance is the first book to harmonize the theory, modeling, and implementation of today's most prevalent pricing models under one convenient cover. Building a bridge from academia to practice, this self-contained text applies theoretical concepts to real-world examples and introduces state-of-the-art, object-oriented programming techniques that equip the reader with the conceptual and illustrative tools needed to understand and develop successful derivative pricing models. Utilizing almost twenty years of academic and industry experience, the author discusses the mathematical concepts that are the foundation of commonly used derivative pricing models, and insightful Motivation and Interpretation sections for each concept are presented to further illustrate the relationship between theory and practice. In-depth coverage of the common characteristics found amongst successful pricing models are provided in addition to key techniques and tips for the construction of these models. The opportunity to interactively explore the book's principal ideas and methodologies is made possible via a related Web site that features interactive Java experiments and exercises. While a high standard of mathematical precision is retained, Mathematical Finance emphasizes practical motivations, interpretations, and results and is an excellent textbook for students in mathematical finance, computational finance, and derivative pricing courses at the upper undergraduate or beginning graduate level. It also serves as a valuable reference for professionals in the banking, insurance, and asset management industries.
Financial Statistics and Mathematical Finance
Author: Ansgar Steland
Publisher: John Wiley & Sons
ISBN: 1118316568
Category : Business & Economics
Languages : en
Pages : 355
Book Description
Mathematical finance has grown into a huge area of research which requires a lot of care and a large number of sophisticated mathematical tools. Mathematically rigorous and yet accessible to advanced level practitioners and mathematicians alike, it considers various aspects of the application of statistical methods in finance and illustrates some of the many ways that statistical tools are used in financial applications. Financial Statistics and Mathematical Finance: Provides an introduction to the basics of financial statistics and mathematical finance. Explains the use and importance of statistical methods in econometrics and financial engineering. Illustrates the importance of derivatives and calculus to aid understanding in methods and results. Looks at advanced topics such as martingale theory, stochastic processes and stochastic integration. Features examples throughout to illustrate applications in mathematical and statistical finance. Is supported by an accompanying website featuring R code and data sets. Financial Statistics and Mathematical Finance introduces the financial methodology and the relevant mathematical tools in a style that is both mathematically rigorous and yet accessible to advanced level practitioners and mathematicians alike, both graduate students and researchers in statistics, finance, econometrics and business administration will benefit from this book.
Publisher: John Wiley & Sons
ISBN: 1118316568
Category : Business & Economics
Languages : en
Pages : 355
Book Description
Mathematical finance has grown into a huge area of research which requires a lot of care and a large number of sophisticated mathematical tools. Mathematically rigorous and yet accessible to advanced level practitioners and mathematicians alike, it considers various aspects of the application of statistical methods in finance and illustrates some of the many ways that statistical tools are used in financial applications. Financial Statistics and Mathematical Finance: Provides an introduction to the basics of financial statistics and mathematical finance. Explains the use and importance of statistical methods in econometrics and financial engineering. Illustrates the importance of derivatives and calculus to aid understanding in methods and results. Looks at advanced topics such as martingale theory, stochastic processes and stochastic integration. Features examples throughout to illustrate applications in mathematical and statistical finance. Is supported by an accompanying website featuring R code and data sets. Financial Statistics and Mathematical Finance introduces the financial methodology and the relevant mathematical tools in a style that is both mathematically rigorous and yet accessible to advanced level practitioners and mathematicians alike, both graduate students and researchers in statistics, finance, econometrics and business administration will benefit from this book.
Methods of Mathematical Finance
Author: Ioannis Karatzas
Publisher: Springer Science & Business Media
ISBN: 0387948392
Category : Business & Economics
Languages : en
Pages : 427
Book Description
This monograph is a sequel to Brownian Motion and Stochastic Calculus by the same authors. Within the context of Brownian-motion- driven asset prices, it develops contingent claim pricing and optimal consumption/investment in both complete and incomplete markets. The latter topic is extended to a study of equilibrium, providing conditions for the existence and uniqueness of market prices which support trading by several heterogeneous agents. Although much of the incomplete-market material is available in research papers, these topics are treated for the first time in a unified manner. The book contains an extensive set of references and notes describing the field, including topics not treated in the text. This monograph should be of interest to researchers wishing to see advanced mathematics applied to finance. The material on optimal consumption and investment, leading to equilibrium, is addressed to the theoretical finance community. The chapters on contingent claim valuation present techniques of practical importance, especially for pricing exotic options. Also available by Ioannis Karatzas and Steven E. Shreve, Brownian Motion and Stochastic Calculus, Second Edition, Springer-Verlag New York, Inc., 1991, 470 pp., ISBN 0-387- 97655-8.
Publisher: Springer Science & Business Media
ISBN: 0387948392
Category : Business & Economics
Languages : en
Pages : 427
Book Description
This monograph is a sequel to Brownian Motion and Stochastic Calculus by the same authors. Within the context of Brownian-motion- driven asset prices, it develops contingent claim pricing and optimal consumption/investment in both complete and incomplete markets. The latter topic is extended to a study of equilibrium, providing conditions for the existence and uniqueness of market prices which support trading by several heterogeneous agents. Although much of the incomplete-market material is available in research papers, these topics are treated for the first time in a unified manner. The book contains an extensive set of references and notes describing the field, including topics not treated in the text. This monograph should be of interest to researchers wishing to see advanced mathematics applied to finance. The material on optimal consumption and investment, leading to equilibrium, is addressed to the theoretical finance community. The chapters on contingent claim valuation present techniques of practical importance, especially for pricing exotic options. Also available by Ioannis Karatzas and Steven E. Shreve, Brownian Motion and Stochastic Calculus, Second Edition, Springer-Verlag New York, Inc., 1991, 470 pp., ISBN 0-387- 97655-8.
Mathematics for Finance
Author: Marek Capinski
Publisher: Springer
ISBN: 1852338466
Category : Business & Economics
Languages : en
Pages : 317
Book Description
This textbook contains the fundamentals for an undergraduate course in mathematical finance aimed primarily at students of mathematics. Assuming only a basic knowledge of probability and calculus, the material is presented in a mathematically rigorous and complete way. The book covers the time value of money, including the time structure of interest rates, bonds and stock valuation; derivative securities (futures, options), modelling in discrete time, pricing and hedging, and many other core topics. With numerous examples, problems and exercises, this book is ideally suited for independent study.
Publisher: Springer
ISBN: 1852338466
Category : Business & Economics
Languages : en
Pages : 317
Book Description
This textbook contains the fundamentals for an undergraduate course in mathematical finance aimed primarily at students of mathematics. Assuming only a basic knowledge of probability and calculus, the material is presented in a mathematically rigorous and complete way. The book covers the time value of money, including the time structure of interest rates, bonds and stock valuation; derivative securities (futures, options), modelling in discrete time, pricing and hedging, and many other core topics. With numerous examples, problems and exercises, this book is ideally suited for independent study.
Mathematical Finance and Probability
Author: Pablo Koch Medina
Publisher: Birkhäuser
ISBN: 3034880413
Category : Mathematics
Languages : en
Pages : 326
Book Description
This self-contained book presents the theory underlying the valuation of derivative financial instruments, which is becoming a standard part of the professional toolbox in the financial industry. It provides great insight into the underlying economic ideas in a very readable form, putting the reader in an excellent position to proceed to the more general continuous-time theory.
Publisher: Birkhäuser
ISBN: 3034880413
Category : Mathematics
Languages : en
Pages : 326
Book Description
This self-contained book presents the theory underlying the valuation of derivative financial instruments, which is becoming a standard part of the professional toolbox in the financial industry. It provides great insight into the underlying economic ideas in a very readable form, putting the reader in an excellent position to proceed to the more general continuous-time theory.
Mathematical Modeling And Computation In Finance: With Exercises And Python And Matlab Computer Codes
Author: Cornelis W Oosterlee
Publisher: World Scientific
ISBN: 1786347962
Category : Business & Economics
Languages : en
Pages : 1310
Book Description
This book discusses the interplay of stochastics (applied probability theory) and numerical analysis in the field of quantitative finance. The stochastic models, numerical valuation techniques, computational aspects, financial products, and risk management applications presented will enable readers to progress in the challenging field of computational finance.When the behavior of financial market participants changes, the corresponding stochastic mathematical models describing the prices may also change. Financial regulation may play a role in such changes too. The book thus presents several models for stock prices, interest rates as well as foreign-exchange rates, with increasing complexity across the chapters. As is said in the industry, 'do not fall in love with your favorite model.' The book covers equity models before moving to short-rate and other interest rate models. We cast these models for interest rate into the Heath-Jarrow-Morton framework, show relations between the different models, and explain a few interest rate products and their pricing.The chapters are accompanied by exercises. Students can access solutions to selected exercises, while complete solutions are made available to instructors. The MATLAB and Python computer codes used for most tables and figures in the book are made available for both print and e-book users. This book will be useful for people working in the financial industry, for those aiming to work there one day, and for anyone interested in quantitative finance. The topics that are discussed are relevant for MSc and PhD students, academic researchers, and for quants in the financial industry.
Publisher: World Scientific
ISBN: 1786347962
Category : Business & Economics
Languages : en
Pages : 1310
Book Description
This book discusses the interplay of stochastics (applied probability theory) and numerical analysis in the field of quantitative finance. The stochastic models, numerical valuation techniques, computational aspects, financial products, and risk management applications presented will enable readers to progress in the challenging field of computational finance.When the behavior of financial market participants changes, the corresponding stochastic mathematical models describing the prices may also change. Financial regulation may play a role in such changes too. The book thus presents several models for stock prices, interest rates as well as foreign-exchange rates, with increasing complexity across the chapters. As is said in the industry, 'do not fall in love with your favorite model.' The book covers equity models before moving to short-rate and other interest rate models. We cast these models for interest rate into the Heath-Jarrow-Morton framework, show relations between the different models, and explain a few interest rate products and their pricing.The chapters are accompanied by exercises. Students can access solutions to selected exercises, while complete solutions are made available to instructors. The MATLAB and Python computer codes used for most tables and figures in the book are made available for both print and e-book users. This book will be useful for people working in the financial industry, for those aiming to work there one day, and for anyone interested in quantitative finance. The topics that are discussed are relevant for MSc and PhD students, academic researchers, and for quants in the financial industry.
An Introduction to Mathematical Finance with Applications
Author: Arlie O. Petters
Publisher: Springer
ISBN: 1493937839
Category : Mathematics
Languages : en
Pages : 499
Book Description
This textbook aims to fill the gap between those that offer a theoretical treatment without many applications and those that present and apply formulas without appropriately deriving them. The balance achieved will give readers a fundamental understanding of key financial ideas and tools that form the basis for building realistic models, including those that may become proprietary. Numerous carefully chosen examples and exercises reinforce the student’s conceptual understanding and facility with applications. The exercises are divided into conceptual, application-based, and theoretical problems, which probe the material deeper. The book is aimed toward advanced undergraduates and first-year graduate students who are new to finance or want a more rigorous treatment of the mathematical models used within. While no background in finance is assumed, prerequisite math courses include multivariable calculus, probability, and linear algebra. The authors introduce additional mathematical tools as needed. The entire textbook is appropriate for a single year-long course on introductory mathematical finance. The self-contained design of the text allows for instructor flexibility in topics courses and those focusing on financial derivatives. Moreover, the text is useful for mathematicians, physicists, and engineers who want to learn finance via an approach that builds their financial intuition and is explicit about model building, as well as business school students who want a treatment of finance that is deeper but not overly theoretical.
Publisher: Springer
ISBN: 1493937839
Category : Mathematics
Languages : en
Pages : 499
Book Description
This textbook aims to fill the gap between those that offer a theoretical treatment without many applications and those that present and apply formulas without appropriately deriving them. The balance achieved will give readers a fundamental understanding of key financial ideas and tools that form the basis for building realistic models, including those that may become proprietary. Numerous carefully chosen examples and exercises reinforce the student’s conceptual understanding and facility with applications. The exercises are divided into conceptual, application-based, and theoretical problems, which probe the material deeper. The book is aimed toward advanced undergraduates and first-year graduate students who are new to finance or want a more rigorous treatment of the mathematical models used within. While no background in finance is assumed, prerequisite math courses include multivariable calculus, probability, and linear algebra. The authors introduce additional mathematical tools as needed. The entire textbook is appropriate for a single year-long course on introductory mathematical finance. The self-contained design of the text allows for instructor flexibility in topics courses and those focusing on financial derivatives. Moreover, the text is useful for mathematicians, physicists, and engineers who want to learn finance via an approach that builds their financial intuition and is explicit about model building, as well as business school students who want a treatment of finance that is deeper but not overly theoretical.