CRAI - Universidad del Rosario Koha › Detalles de: Derivatives analytics with Python

Derivatives analytics with Python

por Hilpisch, Yves J.

Series: The wiley finance series Publicado por : Wiley (Nueva Delhi (India)) Detalles físicos: xvii, 356 páginas ISBN:9781119037996.

Tema(s): Python (Lenguaje de programación para computadores) | Programas informáticos | Métodos de simulación | Análisis de datos

Año : 2015

Existencias ( 2 )
Notas de título ( 1 )

Tipo de ítem	Ubicación actual	Colección	Signatura	Copia número	Estado	Fecha de vencimiento	Código de barras	Reserva de ítems
Libro	Claustro 2do piso	Libro	005.133 H655da (Navegar estantería)	Ej.1	Disponible		100154154
Libro	Claustro 2do piso	Libro	005.133 H655da (Navegar estantería)	Ej.2	Disponible		100154155

Total de reservas: 0

"Supercharge options analytics and hedging using the power of Python Derivatives Analytics with Python shows you how to implement market-consistent valuation and hedging approaches using advanced financial models, efficient numerical techniques, and the powerful capabilities of the Python programming language. This unique guide offers detailed explanations of all theory, methods, and processes, giving you the background and tools necessary to value stock index options from a sound foundation. You'll find and use self-contained Python scripts and modules and learn how to apply Python to advanced data and derivatives analytics as you benefit from the 5,000+ lines of code that are provided to help you reproduce the results and graphics presented. Coverage includes market data analysis, risk-neutral valuation, Monte Carlo simulation, model calibration, valuation, and dynamic hedging, with models that exhibit stochastic volatility, jump components, stochastic short rates, and more. The companion website features all code and IPython Notebooks for immediate execution and automation. Python is gaining ground in the derivatives analytics space, allowing institutions to quickly and efficiently deliver portfolio, trading, and risk management results. This book is the finance professional's guide to exploiting Python's capabilities for efficient and performing derivatives analytics. Reproduce major stylized facts of equity and options markets yourself Apply Fourier transform techniques and advanced Monte Carlo pricing Calibrate advanced option pricing models to market data Integrate advanced models and numeric methods to dynamically hedge options Recent developments in the Python ecosystem enable analysts to implement analytics tasks as performing as with C or C++, but using only about one-tenth of the code or even less. Derivatives Analytics with Python -- Data Analysis, Models, Simulation, Calibration and Hedging shows you what you need to know to supercharge your derivatives and risk analytics efforts"--