Numerical Engines in Quantitative Finance : Computational Methods for Pricing, Risk, Calibration, and Simulation
Language: English
Published by Independently Published Mai 2026, 2026
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
£ 65.49
Quantity: 2 available
Add to basketItem description from seller
Neuware - Reactive PublishingNumerical Engines in Quantitative Finance is a practical guide to the computational methods used to build pricing, risk, calibration, and simulation workflows in modern quantitative finance.Designed for readers who already understand the foundations of financial modeling, this book focuses on the numerical machinery behind quantitative systems. It explains how models are translated into reliable computational processes, how numerical choices affect accuracy and stability, and how pricing and risk engines can be structured for real-world analytical use.Inside, readers will explore core techniques used across derivatives pricing, portfolio risk, model calibration, Monte Carlo simulation, finite difference methods, optimization, curve construction, and scenario analysis. The emphasis is on building a clear understanding of how numerical methods behave, where they fail, and how they can be tested, validated, and improved.Topics include: - Numerical foundations for quantitative finance- Pricing engine architecture and model implementation- Risk measurement and sensitivity calculation- Calibration methods for financial models- Monte Carlo simulation and variance reduction- Finite difference approaches for pricing problems- Curve construction, interpolation, and bootstrapping- Stability, convergence, validation, and error analysis- Practical design patterns for computational finance systemsRather than presenting quantitative finance as a collection of isolated formulas, this book treats it as an engineering discipline. Readers will learn how numerical components connect, how model assumptions flow through computational systems, and how to design engines that are more transparent, testable, and robust.Numerical Engines in Quantitative Finance is suited for quantitative analysts, financial engineers, advanced finance students, and technically oriented traders who want a deeper understanding of the computational infrastructure behind pricing and risk systems.…
Seller Inventory # 9798196310355
- Title
- Numerical Engines in Quantitative Finance : Computational Methods for Pricing, Risk, Calibration, and Simulation
- Author
- Johann Strauss
- Publisher
- Independently Published Mai 2026
- Publication year
- 2026
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 13
- 9798196310355
- Item weight
- 518 grams
- Dimensions
- 229x152x27 mm
Numerical Engines in Quantitative Finance is a practical guide to the computational methods used to build pricing, risk, calibration, and simulation workflows in modern quantitative finance.
Designed for readers who already understand the foundations of financial modeling, this book focuses on the numerical machinery behind quantitative systems. It explains how models are translated into reliable computational processes, how numerical choices affect accuracy and stability, and how pricing and risk engines can be structured for real-world analytical use.
Inside, readers will explore core techniques used across derivatives pricing, portfolio risk, model calibration, Monte Carlo simulation, finite difference methods, optimization, curve construction, and scenario analysis. The emphasis is on building a clear understanding of how numerical methods behave, where they fail, and how they can be tested, validated, and improved.
Topics include:
- Numerical foundations for quantitative finance
- Pricing engine architecture and model implementation
- Risk measurement and sensitivity calculation
- Calibration methods for financial models
- Monte Carlo simulation and variance reduction
- Finite difference approaches for pricing problems
- Curve construction, interpolation, and bootstrapping
- Stability, convergence, validation, and error analysis
- Practical design patterns for computational finance systems
Rather than presenting quantitative finance as a collection of isolated formulas, this book treats it as an engineering discipline. Readers will learn how numerical components connect, how model assumptions flow through computational systems, and how to design engines that are more transparent, testable, and robust.
Numerical Engines in Quantitative Finance is suited for quantitative analysts, financial engineers, advanced finance students, and technically oriented traders who want a deeper understanding of the computational infrastructure behind pricing and risk systems.
"Synopsis" may belong to another edition of this title.
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