9798198515994 - stochastic calculus for modern quantitative finance and algorithmic trading: python implementations, models, and real-world applications di van der post, hayden; preston, james (6 risultati)
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Da: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 30,54
Spedizione gratuitaSpedito in U.S.A.Quantità: Più di 20 disponibili
PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
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Da: PBShop.store UK, Fairford, GLOS, Regno UnitoPBShop.store UK
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 28,07
EUR 4,86 spedizioneSpedito da Regno Unito a U.S.A.Quantità: Più di 20 disponibili
PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 40,81
EUR 62,31 spedizioneSpedito da Germania a U.S.A.Quantità: 2 disponibili
Taschenbuch. Condizione: Neu. Neuware - Reactive PublishingStochastic Calculus for Modern Quantitative Finance and Algorithmic Trading offers a clear, practical, and rigorous introduction to stochastic calculus tailored specifically for quantitative finance professionals and algorithmic traders.This book bridges the gap between…theoretical stochastic processes and real-world implementation in modern financial markets. Readers will learn how to apply core concepts, such as Itô's lemma, stochastic differential equations, martingales, and Brownian motion, directly to quantitative modeling and trading strategy development.What You'll Find Inside: - Python Implementation: Complete, ready-to-use code examples using Python (NumPy, SciPy, pandas, and QuantLib) that demonstrate how to simulate stochastic processes, price derivatives, and build trading models.- Modern Models: In-depth coverage of key models used in today's quantitative finance, including the Black-Scholes framework extensions, local volatility, stochastic volatility (Heston), jump-diffusion, and more.- Real-World Applications: Practical case studies on algorithmic trading strategies, risk management, option pricing, portfolio optimization, and Monte Carlo methods applied to live market data.Written with both clarity and technical depth, this book is designed for readers who want to move beyond abstract theory and develop production-grade skills in quantitative finance and algorithmic trading.Whether you are a quantitative analyst, aspiring quant developer, algorithmic trader, or finance graduate student looking to strengthen your technical toolkit, this book provides the mathematical foundation and practical coding guidance needed to succeed in today's data-driven financial markets.No prior stochastic calculus experience is assumed, but familiarity with basic probability, calculus, and Python programming is recommended.
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- Print on Demand
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 29,96
Spedizione gratuitaSpedito in U.S.A.Quantità: 1 disponibili
Paperback. Condizione: new. Paperback. Reactive PublishingStochastic Calculus for Modern Quantitative Finance and Algorithmic Trading offers a clear, practical, and rigorous introduction to stochastic calculus tailored specifically for quantitative finance professionals and algorithmic traders.This book bridges the gap between t…heoretical stochastic processes and real-world implementation in modern financial markets. Readers will learn how to apply core concepts, such as Ito's lemma, stochastic differential equations, martingales, and Brownian motion, directly to quantitative modeling and trading strategy development.What You'll Find Inside: Python Implementation: Complete, ready-to-use code examples using Python (NumPy, SciPy, pandas, and QuantLib) that demonstrate how to simulate stochastic processes, price derivatives, and build trading models.Modern Models: In-depth coverage of key models used in today's quantitative finance, including the Black-Scholes framework extensions, local volatility, stochastic volatility (Heston), jump-diffusion, and more.Real-World Applications: Practical case studies on algorithmic trading strategies, risk management, option pricing, portfolio optimization, and Monte Carlo methods applied to live market data.Written with both clarity and technical depth, this book is designed for readers who want to move beyond abstract theory and develop production-grade skills in quantitative finance and algorithmic trading.Whether you are a quantitative analyst, aspiring quant developer, algorithmic trader, or finance graduate student looking to strengthen your technical toolkit, this book provides the mathematical foundation and practical coding guidance needed to succeed in today's data-driven financial markets.No prior stochastic calculus experience is assumed, but familiarity with basic probability, calculus, and Python programming is recommended. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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- Print on Demand
Da: California Books, Miami, FL, U.S.A.California Books
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 29,97
Spedizione gratuitaSpedito in U.S.A.Quantità: Più di 20 disponibili
Condizione: New. Print on Demand.
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- Print on Demand
Da: CitiRetail, Stevenage, Regno UnitoCitiRetail
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 31,84
EUR 43,19 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 1 disponibili
Paperback. Condizione: new. Paperback. Reactive PublishingStochastic Calculus for Modern Quantitative Finance and Algorithmic Trading offers a clear, practical, and rigorous introduction to stochastic calculus tailored specifically for quantitative finance professionals and algorithmic traders.This book bridges the gap between t…heoretical stochastic processes and real-world implementation in modern financial markets. Readers will learn how to apply core concepts, such as Ito's lemma, stochastic differential equations, martingales, and Brownian motion, directly to quantitative modeling and trading strategy development.What You'll Find Inside: Python Implementation: Complete, ready-to-use code examples using Python (NumPy, SciPy, pandas, and QuantLib) that demonstrate how to simulate stochastic processes, price derivatives, and build trading models.Modern Models: In-depth coverage of key models used in today's quantitative finance, including the Black-Scholes framework extensions, local volatility, stochastic volatility (Heston), jump-diffusion, and more.Real-World Applications: Practical case studies on algorithmic trading strategies, risk management, option pricing, portfolio optimization, and Monte Carlo methods applied to live market data.Written with both clarity and technical depth, this book is designed for readers who want to move beyond abstract theory and develop production-grade skills in quantitative finance and algorithmic trading.Whether you are a quantitative analyst, aspiring quant developer, algorithmic trader, or finance graduate student looking to strengthen your technical toolkit, this book provides the mathematical foundation and practical coding guidance needed to succeed in today's data-driven financial markets.No prior stochastic calculus experience is assumed, but familiarity with basic probability, calculus, and Python programming is recommended. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
