This book offers an up-to-date introductory treatment of computational techniques applied to problems in finance, placing issues such as numerical stability, convergence and error analysis in both deterministic and stochastic settings at its core.
The first part provides a welcoming but nonetheless rigorous introduction to the fundamental theory of option pricing, including European, American, and exotic options along with their hedge parameters, and combines a clear treatment of the mathematical framework with practical worked examples in Python. The second part explores the main computational methods for valuing options within the Black-Scholes framework: lattice, Monte Carlo, and finite difference methods. The third and final part covers advanced topics for the simulation of financial processes beyond the standard Black-Scholes setting. Techniques for the analysis and simulation of multidimensional financial data, including copulas, are covered and will be of interest to those studying machine learning for finance. There is also an in-depth treatment of exact and approximate sampling methods for stochastic differential equation models of interest rates and volatilities.
Written for advanced undergraduate and masters-level courses, the book assumes some exposure to core mathematical topics such as linear algebra, ordinary differential equations, multivariate calculus, probability, and statistics at an undergraduate level. While familiarity with Python is not required, readers should be comfortable with basic programming constructs such as variables, loops, and conditional statements.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Cónall Kelly is a Senior Lecturer in Financial Mathematics and Director of the MSc Financial and Computational Mathematics at the School of Mathematical Sciences, University College Cork, Ireland. He teaches core modules on derivatives pricing and computational finance to undergraduate and postgraduate students. He is an active researcher in the field of computational stochastics and, since 2018, he has contributed to the graduate programme at the African Institute for Mathematical Sciences in Senegal.
This book offers an up-to-date introductory treatment of computational techniques applied to problems in finance, placing issues such as numerical stability, convergence and error analysis in both deterministic and stochastic settings at its core.
The first part provides a welcoming but nonetheless rigorous introduction to the fundamental theory of option pricing, including European, American, and exotic options along with their hedge parameters, and combines a clear treatment of the mathematical framework with practical worked examples in Python. The second part explores the main computational methods for valuing options within the Black-Scholes framework: lattice, Monte Carlo, and finite difference methods. The third and final part covers advanced topics for the simulation of financial processes beyond the standard Black-Scholes setting. Techniques for the analysis and simulation of multidimensional financial data, including copulas, are covered and will be of interest to those studying machine learning for finance. There is also an in-depth treatment of exact and approximate sampling methods for stochastic differential equation models of interest rates and volatilities.
Written for advanced undergraduate and masters-level courses, the book assumes some exposure to core mathematical topics such as linear algebra, ordinary differential equations, multivariate calculus, probability, and statistics at an undergraduate level. While familiarity with Python is not required, readers should be comfortable with basic programming constructs such as variables, loops, and conditional statements.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: New. Codice articolo 47820003-n
Quantità: Più di 20 disponibili
Da: PBShop.store US, Wood Dale, IL, U.S.A.
HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000. Codice articolo GB-9783031605741
Quantità: 3 disponibili
Da: PBShop.store UK, Fairford, GLOS, Regno Unito
HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000. Codice articolo GB-9783031605741
Quantità: 3 disponibili
Da: Books Puddle, New York, NY, U.S.A.
Condizione: New. 2024th edition NO-PA16APR2015-KAP. Codice articolo 26402091717
Quantità: 1 disponibili
Da: Speedyhen LLC, Hialeah, FL, U.S.A.
Condizione: NEW. Codice articolo NWUS9783031605741
Quantità: 6 disponibili
Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: As New. Unread book in perfect condition. Codice articolo 47820003
Quantità: Più di 20 disponibili
Da: Majestic Books, Hounslow, Regno Unito
Condizione: New. Codice articolo 394318106
Quantità: 1 disponibili
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
Hardcover. Condizione: new. Hardcover. This book offers an up-to-date introductory treatment of computational techniques applied to problems in finance, placing issues such as numerical stability, convergence and error analysis in both deterministic and stochastic settings at its core.The first part provides a welcoming but nonetheless rigorous introduction to the fundamental theory of option pricing, including European, American, and exotic options along with their hedge parameters, and combines a clear treatment of the mathematical framework with practical worked examples in Python. The second part explores the main computational methods for valuing options within the Black-Scholes framework: lattice, Monte Carlo, and finite difference methods. The third and final part covers advanced topics for the simulation of financial processes beyond the standard Black-Scholes setting. Techniques for the analysis and simulation of multidimensional financial data, including copulas, are covered and will be of interest to those studying machine learning for finance. There is also an in-depth treatment of exact and approximate sampling methods for stochastic differential equation models of interest rates and volatilities.Written for advanced undergraduate and masters-level courses, the book assumes some exposure to core mathematical topics such as linear algebra, ordinary differential equations, multivariate calculus, probability, and statistics at an undergraduate level. While familiarity with Python is not required, readers should be comfortable with basic programming constructs such as variables, loops, and conditional statements. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9783031605741
Quantità: 1 disponibili
Da: Biblios, Frankfurt am main, HESSE, Germania
Condizione: New. Codice articolo 18402091727
Quantità: 1 disponibili
Da: Brook Bookstore On Demand, Napoli, NA, Italia
Condizione: new. Codice articolo BA5PIVLQIQ
Quantità: 3 disponibili