Reactive Publishing
Financial markets are driven by complex mathematical models, and Fourier and Laplace transforms are powerful tools used in option pricing, risk-neutral valuation, and algorithmic trading. These mathematical techniques enable fast and efficient solutions to problems that would otherwise require time-consuming numerical methods.
This comprehensive guide bridges the gap between theory and real-world financial applications, equipping you with the tools needed to model derivatives, manage risk, and enhance trading strategies.
What You’ll Learn:Fourier Transform Applications in Finance – Efficient computation of option prices using the Characteristic Function Approach
Laplace Transforms in Risk Management – Solving stochastic differential equations (SDEs) for derivative pricing
Option Pricing with the Fast Fourier Transform (FFT) – Accelerate pricing computations for European and exotic options
Risk-Neutral Valuation & Martingales – Use transform methods to simplify pricing under the risk-neutral measure
Stochastic Processes & Jump Diffusions – Apply Fourier methods to price models like Merton’s Jump-Diffusion and Heston’s Stochastic Volatility Model
Practical Python Implementations – Step-by-step coding examples for real-world quant applications
Quantitative Traders & Hedge Funds – Optimize trading strategies with advanced transform methods
Financial Engineers & Risk Managers – Improve risk modeling and derivative pricing accuracy
Students & Researchers in Quant Finance – Build a strong mathematical foundation in transform methods
With clear explanations, real-world case studies, and Python implementations, this book transforms complex mathematical concepts into practical tools for finance professionals.
Master the mathematics of modern finance—get your copy today!
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Paperback. Condición: new. Paperback. Reactive PublishingMaster Fourier and Laplace Transforms for Advanced Quantitative FinanceFinancial markets are driven by complex mathematical models, and Fourier and Laplace transforms are powerful tools used in option pricing, risk-neutral valuation, and algorithmic trading. These mathematical techniques enable fast and efficient solutions to problems that would otherwise require time-consuming numerical methods.This comprehensive guide bridges the gap between theory and real-world financial applications, equipping you with the tools needed to model derivatives, manage risk, and enhance trading strategies.What You'll Learn: Fourier Transform Applications in Finance - Efficient computation of option prices using the Characteristic Function ApproachLaplace Transforms in Risk Management - Solving stochastic differential equations (SDEs) for derivative pricingOption Pricing with the Fast Fourier Transform (FFT) - Accelerate pricing computations for European and exotic optionsRisk-Neutral Valuation & Martingales - Use transform methods to simplify pricing under the risk-neutral measureStochastic Processes & Jump Diffusions - Apply Fourier methods to price models like Merton's Jump-Diffusion and Heston's Stochastic Volatility ModelPractical Python Implementations - Step-by-step coding examples for real-world quant applicationsWho This Book is For: Quantitative Traders & Hedge Funds - Optimize trading strategies with advanced transform methodsFinancial Engineers & Risk Managers - Improve risk modeling and derivative pricing accuracyStudents & Researchers in Quant Finance - Build a strong mathematical foundation in transform methodsWith clear explanations, real-world case studies, and Python implementations, this book transforms complex mathematical concepts into practical tools for finance professionals.Master the mathematics of modern finance-get your copy today! This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9798312120929
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Paperback. Condición: new. Paperback. Reactive PublishingMaster Fourier and Laplace Transforms for Advanced Quantitative FinanceFinancial markets are driven by complex mathematical models, and Fourier and Laplace transforms are powerful tools used in option pricing, risk-neutral valuation, and algorithmic trading. These mathematical techniques enable fast and efficient solutions to problems that would otherwise require time-consuming numerical methods.This comprehensive guide bridges the gap between theory and real-world financial applications, equipping you with the tools needed to model derivatives, manage risk, and enhance trading strategies.What You'll Learn: Fourier Transform Applications in Finance - Efficient computation of option prices using the Characteristic Function ApproachLaplace Transforms in Risk Management - Solving stochastic differential equations (SDEs) for derivative pricingOption Pricing with the Fast Fourier Transform (FFT) - Accelerate pricing computations for European and exotic optionsRisk-Neutral Valuation & Martingales - Use transform methods to simplify pricing under the risk-neutral measureStochastic Processes & Jump Diffusions - Apply Fourier methods to price models like Merton's Jump-Diffusion and Heston's Stochastic Volatility ModelPractical Python Implementations - Step-by-step coding examples for real-world quant applicationsWho This Book is For: Quantitative Traders & Hedge Funds - Optimize trading strategies with advanced transform methodsFinancial Engineers & Risk Managers - Improve risk modeling and derivative pricing accuracyStudents & Researchers in Quant Finance - Build a strong mathematical foundation in transform methodsWith clear explanations, real-world case studies, and Python implementations, this book transforms complex mathematical concepts into practical tools for finance professionals.Master the mathematics of modern finance-get your copy today! This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9798312120929
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