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Paperback. Condición: As New. No Jacket. Pages are clean and are not marred by notes or folds of any kind. ~ ThriftBooks: Read More, Spend Less.

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Paperback. Condición: Brand New. 107 pages. 8.50x8.50x0.26 inches. In Stock.

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PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

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Condición: Nuevo. Rocafort, Juan Antonio; Archivo SM,; Alonso Rivero, Daniel; Illa Gómez, Aarón; García Ayerbe, Alberto; Mark, Alya; Martí De La Ahumada, Blanca; Gutiérrez, Eliana; Moreno Arrastio, Félix; García Ingelmo, Gema; Vitali, Giselle; Delgado, Jesús; Infante Toro, Juan Jesús; Navarro Falcón, Lourdes; Fernández Méndez, Luján; Pérez De Muti, Marcelo; Rodrigo Miranda, Mercedes; Albesa Valdés, Núria; Hernández Pintor, Nuria; Thinkstock, Ilustrador. Natural Science. 2 Primary. Revuela. Principado de Asturias editado por Sm.

Condición: Nuevo. Rocafort, Juan Antonio; Archivo SM,; Alonso Rivero, Daniel; Illa Gómez, Aarón; García Ayerbe, Alberto; Mark, Alya; Martí De La Ahumada, Blanca; Gutiérrez, Eliana; Moreno Arrastio, Félix; García Ingelmo, Gema; Vitali, Giselle; Delgado, Jesús; Infante Toro, Juan Jesús; Navarro Falcón, Lourdes; Fernández Méndez, Luján; Pérez De Muti, Marcelo; Rodrigo Miranda, Mercedes; Albesa Valdés, Núria; Hernández Pintor, Nuria; Thinkstock, Ilustrador. Natural Science. 2 Primary. Revuela. Galicia editado por Sm.

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PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

Condición: As New. Unread book in perfect condition.

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

Condición: New.

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Paperback. Condición: New.

Condición: As New. Unread book in perfect condition.

Taschenbuch. Condición: Neu. Neuware -From the elegance of the BlackScholes equation to the complexity of multi-factor interest rate models and hybrid derivatives, this book is your comprehensive guide to quantitative finance, complete with 15+ advanced C++ projects using QuantLib and Boost.You'll move seamlessly from mathematical foundations to real-world implementation, building a professional-grade toolkit for pricing, risk analysis, and calibration. Inside, you will learn core option pricing methods, master single-and multi-factor interest rate models, and construct and calibrate trees and lattices for advanced derivatives. You will also explore cutting edge products: exotic multi-asset options, hybrid derivatives, credit instruments, and cross-currency swaps.Packed with practical source code, step-by-step calibrations, and performance-tuned Boost integration, this book bridges the gap between academic finance and production-grade quant development. Whether you're a quant developer, financial engineer, or an advanced student, you'll gain the skills to design, implement, and deploy derivatives pricing models ready for the trading floor.What You Will LearnUnderstand the mathematics behind BlackScholes, Vasicek, HullWhite, CIR, BDT, BlackKarasinski, and other core models.Apply finite difference schemes, trinomial trees, and Monte Carlo simulations for derivative pricing.Build and value swaps, swaptions, FRAs, bonds, callable/convertible debt, and multi-curve term structures.Implement barrier, multi-asset, hybrid, and structured products in C++.Model credit default swaps, cross-currency swaps, and total return structures.Use QuantLib and Boost to create production-grade pricing engines and calibration tools.Employ Gaussian models, market models, and global optimizers for fitting market data.Integrate code into professional workflows, ensuring speed, accuracy, and maintainability.Who This Book is for:Quantitative developers, financial engineers, traders, analysts, and graduates students using C++, QuantLib, Boost, and robust tools to price, hedge, and manage risk for complex financial instrumentsand for software engineers aiming to bridge theory and industry practice in quantitative finance.Optional prerequisite: Mastering Quantitative Finance with Modern C++: Foundations, Derivatives, and Computational Methods, for readers who want to build a solid foundation before tackling the advanced models and projects in this book.

Taschenbuch. Condición: Neu. Neuware -Learn to build robust, scalable financial models to position yourself as an expert in computational finance. At a time when the financial industry demands an increasingly complex and accurate mode, this book ensures you stay ahead of the curve by leveraging the latest advancements in programming to develop faster, more reliable, and maintainable financial software.To begin, you'll explore key features of C++23, object-oriented programming, and template-based design patterns critical for building reusable financial components. From there, dive into a range of numerical methods, including Monte Carlo simulations, binomial and trinomial trees, and finite difference schemes. Special attention is given to practical implementation details. Every chapter is designed to guide you step by step in transforming mathematical models into efficient, production-level C++ code. You will also learn to handle exotic derivatives, stochastic volatility, and jump-diffusion models, bridging the gap between theory and practice.In the end, you'll be equipped with the technical foundation and practical tools needed to design, implement, and analyze complex financial products. You will also be well-prepared to tackle the advanced interest rate and credit derivatives covered in further depth in De La Rosa's Advanced Quantitative Finance with Modern C++.What You Will Learn:Master modern C++23 syntax and features, including object-oriented and generic programming.Design flexible option payoff hierarchies for code reuse.Apply advanced numerical techniques such as Monte Carlo, binomial/trinomial trees, and finite difference methods.Calculate and interpret option sensitivities (Greeks).Model and price exotic options, including stochastic volatility and jump-diffusion models.Integrate mathematical finance concepts into production-quality C++ code.Who This Book is for:Quantitative analysts, financial engineers, researchers, and advanced developers who seek to deepen their knowledge of derivative pricing and computational finance using modern C++. Also suited for graduate students in quantitative finance or applied mathematics who want to complement their theoretical studies with robust coding skills.

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Taschenbuch. Condición: Neu. Advanced Quantitative Finance with Modern C++ | Interest Rate Modeling and Advanced Derivatives | Aaron de La Rosa | Taschenbuch | xx | Englisch | 2026 | Apress | EAN 9798868820588 | Verantwortliche Person für die EU: APress in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Taschenbuch. Condición: Neu. Mastering Quantitative Finance with Modern C++ | Foundations, Derivatives, and Computational Methods | Aaron de la Rosa | Taschenbuch | xxxviii | Englisch | 2026 | Apress | EAN 9798868817922 | Verantwortliche Person für die EU: APress in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Taschenbuch. Condición: Neu. Neuware - Learn to build robust, scalable financial models to position yourself as an expert in computational finance. At a time when the financial industry demands an increasingly complex and accurate mode, this book ensures you stay ahead of the curve by leveraging the latest advancements in programming to develop faster, more reliable, and maintainable financial software.To begin, you ll explore key features of C++23, object-oriented programming, and template-based design patterns critical for building reusable financial components. From there, dive into a range of numerical methods, including Monte Carlo simulations, binomial and trinomial trees, and finite difference schemes. Special attention is given to practical implementation details. Every chapter is designed to guide you step by step in transforming mathematical models into efficient, production-level C++ code. You will also learn to handle exotic derivatives, stochastic volatility, and jump-diffusion models, bridging the gap between theory and practice.In the end, you ll be equipped with the technical foundation and practical tools needed to design, implement, and analyze complex financial products. You will also be well-prepared to tackle the advanced interest rate and credit derivatives covered in further depth in De La Rosa s Advanced Quantitative Finance with Modern C++.What You Will Learn:Master modern C++23 syntax and features, including object-oriented and generic programming.Design flexible option payoff hierarchies for code reuse.Apply advanced numerical techniques such as Monte Carlo, binomial/trinomial trees, and finite difference methods.Calculate and interpret option sensitivities (Greeks).Model and price exotic options, including stochastic volatility and jump-diffusion models.Integrate mathematical finance concepts into production-quality C++ code.Who This Book is for:Quantitative analysts, financial engineers, researchers, and advanced developers who seek to deepen their knowledge of derivative pricing and computational finance using modern C++. Also suited for graduate students in quantitative finance or applied mathematics who want to complement their theoretical studies with robust coding skills.

Taschenbuch. Condición: Neu. Neuware - From the elegance of the Black Scholes equation to the complexity of multi-factor interest rate models and hybrid derivatives, this book is your comprehensive guide to quantitative finance, complete with 15+ advanced C++ projects using QuantLib and Boost.You ll move seamlessly from mathematical foundations to real-world implementation, building a professional-grade toolkit for pricing, risk analysis, and calibration. Inside, you will learn core option pricing methods, master single-and multi-factor interest rate models, and construct and calibrate trees and lattices for advanced derivatives. You will also explore cutting edge products: exotic multi-asset options, hybrid derivatives, credit instruments, and cross-currency swaps.Packed with practical source code, step-by-step calibrations, and performance-tuned Boost integration, this book bridges the gap between academic finance and production-grade quant development. Whether you re a quant developer, financial engineer, or an advanced student, you ll gain the skills to design, implement, and deploy derivatives pricing models ready for the trading floor.What You Will LearnUnderstand the mathematics behind Black Scholes, Vasicek, Hull White, CIR, BDT, Black Karasinski, and other core models.Apply finite difference schemes, trinomial trees, and Monte Carlo simulations for derivative pricing.Build and value swaps, swaptions, FRAs, bonds, callable/convertible debt, and multi-curve term structures.Implement barrier, multi-asset, hybrid, and structured products in C++.Model credit default swaps, cross-currency swaps, and total return structures.Use QuantLib and Boost to create production-grade pricing engines and calibration tools.Employ Gaussian models, market models, and global optimizers for fitting market data.Integrate code into professional workflows, ensuring speed, accuracy, and maintainability.Who This Book is for:Quantitative developers, financial engineers, traders, analysts, and graduates students using C++, QuantLib, Boost, and robust tools to price, hedge, and manage risk for complex financial instruments and for software engineers aiming to bridge theory and industry practice in quantitative finance.Optional prerequisite: Mastering Quantitative Finance with Modern C++: Foundations, Derivatives, and Computational Methods, for readers who want to build a solid foundation before tackling the advanced models and projects in this book.

Paperback. Condición: New.

Taschenbuch. Condición: Neu. Neuware -From the elegance of the BlackScholes equation to the complexity of multi-factor interest rate models and hybrid derivatives, this book is your comprehensive guide to quantitative finance, complete with 15+ advanced C++ projects using QuantLib and Boost.You'll move seamlessly from mathematical foundations to real-world implementation, building a professional-grade toolkit for pricing, risk analysis, and calibration. Inside, you will learn core option pricing methods, master single-and multi-factor interest rate models, and construct and calibrate trees and lattices for advanced derivatives. You will also explore cutting edge products: exotic multi-asset options, hybrid derivatives, credit instruments, and cross-currency swaps.Packed with practical source code, step-by-step calibrations, and performance-tuned Boost integration, this book bridges the gap between academic finance and production-grade quant development. Whether you're a quant developer, financial engineer, or an advanced student, you'll gain the skills to design, implement, and deploy derivatives pricing models ready for the trading floor.What You Will LearnUnderstand the mathematics behind BlackScholes, Vasicek, HullWhite, CIR, BDT, BlackKarasinski, and other core models.Apply finite difference schemes, trinomial trees, and Monte Carlo simulations for derivative pricing.Build and value swaps, swaptions, FRAs, bonds, callable/convertible debt, and multi-curve term structures.Implement barrier, multi-asset, hybrid, and structured products in C++.Model credit default swaps, cross-currency swaps, and total return structures.Use QuantLib and Boost to create production-grade pricing engines and calibration tools.Employ Gaussian models, market models, and global optimizers for fitting market data.Integrate code into professional workflows, ensuring speed, accuracy, and maintainability.Who This Book is for:Quantitative developers, financial engineers, traders, analysts, and graduates students using C++, QuantLib, Boost, and robust tools to price, hedge, and manage risk for complex financial instrumentsand for software engineers aiming to bridge theory and industry practice in quantitative finance.Optional prerequisite: Mastering Quantitative Finance with Modern C++: Foundations, Derivatives, and Computational Methods, for readers who want to build a solid foundation before tackling the advanced models and projects in this book. 1100 pp. Englisch.

Taschenbuch. Condición: Neu. Neuware -Learn to build robust, scalable financial models to position yourself as an expert in computational finance. At a time when the financial industry demands an increasingly complex and accurate mode, this book ensures you stay ahead of the curve by leveraging the latest advancements in programming to develop faster, more reliable, and maintainable financial software.To begin, you'll explore key features of C++23, object-oriented programming, and template-based design patterns critical for building reusable financial components. From there, dive into a range of numerical methods, including Monte Carlo simulations, binomial and trinomial trees, and finite difference schemes. Special attention is given to practical implementation details. Every chapter is designed to guide you step by step in transforming mathematical models into efficient, production-level C++ code. You will also learn to handle exotic derivatives, stochastic volatility, and jump-diffusion models, bridging the gap between theory and practice.In the end, you'll be equipped with the technical foundation and practical tools needed to design, implement, and analyze complex financial products. You will also be well-prepared to tackle the advanced interest rate and credit derivatives covered in further depth in De La Rosa's Advanced Quantitative Finance with Modern C++.What You Will Learn: Master modern C++23 syntax and features, including object-oriented and generic programming.Design flexible option payoff hierarchies for code reuse.Apply advanced numerical techniques such as Monte Carlo, binomial/trinomial trees, and finite difference methods.Calculate and interpret option sensitivities (Greeks).Model and price exotic options, including stochastic volatility and jump-diffusion models.Integrate mathematical finance concepts into production-quality C++ code.Who This Book is for:Quantitative analysts, financial engineers, researchers, and advanced developers who seek to deepen their knowledge of derivative pricing and computational finance using modern C++. Also suited for graduate students in quantitative finance or applied mathematics who want to complement their theoretical studies with robust coding skills. 916 pp. Englisch.

Paperback. Condición: new. Paperback. Learn to build robust, scalable financial models to position yourself as an expert in computational finance. At a time when the financial industry demands an increasingly complex and accurate mode, this book ensures you stay ahead of the curve by leveraging the latest advancements in programming to develop faster, more reliable, and maintainable financial software.To begin, youll explore key features of C++23, object-oriented programming, and template-based design patterns critical for building reusable financial components. From there, dive into a range of numerical methods, including Monte Carlo simulations, binomial and trinomial trees, and finite difference schemes. Special attention is given to practical implementation details. Every chapter is designed to guide you step by step in transforming mathematical models into efficient, production-level C++ code. You will also learn to handle exotic derivatives, stochastic volatility, and jump-diffusion models, bridging the gap between theory and practice.In the end, youll be equipped with the technical foundation and practical tools needed to design, implement, and analyze complex financial products. You will also be well-prepared to tackle the advanced interest rate and credit derivatives covered in further depth in De La Rosas Advanced Quantitative Finance with Modern C++.What You Will Learn: Master modern C++23 syntax and features, including object-oriented and generic programming.Design flexible option payoff hierarchies for code reuse.Apply advanced numerical techniques such as Monte Carlo, binomial/trinomial trees, and finite difference methods.Calculate and interpret option sensitivities (Greeks).Model and price exotic options, including stochastic volatility and jump-diffusion models.Integrate mathematical finance concepts into production-quality C++ code.Who This Book is for:Quantitative analysts, financial engineers, researchers, and advanced developers who seek to deepen their knowledge of derivative pricing and computational finance using modern C++. Also suited for graduate students in quantitative finance or applied mathematics who want to complement their theoretical studies with robust coding skills. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.