9798259178557 - quantitative risk management with python: value at risk, expected shortfall, and portfolio stress testing de preston, james; bisette, vincent (4 resultados)

- Tapa blanda
Librería: PBShop.store UK, Fairford, GLOS, Reino UnidoPBShop.store UK
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 34,72
Envío por EUR 5,89Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

- Tapa blanda
Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 48,58
Envío por EUR 62,57Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Taschenbuch. Condición: Neu. Neuware.

- Tapa blanda
- Impresión bajo demanda
Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books
Contactar con el vendedorVendedor de 4 estrellasCondición: Nuevo
EUR 34,28
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: New. Print on Demand.

- Tapa blanda
- Impresión bajo demanda
Librería: CitiRetail, Stevenage, Reino UnidoCitiRetail
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 38,67
Envío por EUR 43,43Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Paperback. Condición: new. Paperback. Reactive PublishingQuantitative Risk Management with Python is a practical guide to measuring, modeling, and analyzing financial risk using modern Python workflows.Designed for analysts, traders, students, and quantitative finance practitioners, this book explains how core risk measures are…built, interpreted, and applied across real-world portfolios. Readers will learn how to calculate Value at Risk, estimate Expected Shortfall, run portfolio stress tests, analyze return distributions, and evaluate risk under changing market conditions.The book emphasizes clear implementation, practical interpretation, and reusable Python techniques. Instead of treating risk metrics as isolated formulas, it shows how they fit into a broader risk management workflow involving data preparation, volatility estimation, scenario analysis, backtesting, and portfolio-level reporting.Inside, readers will explore: Value at Risk using historical, parametric, and simulation-based methodsExpected Shortfall and downside risk measurementStress testing and scenario analysis for portfolio exposuresVolatility, correlation, and distributional assumptionsBacktesting risk models and interpreting model limitationsPython workflows for repeatable financial risk analysisThis book is written for readers who want a structured, applied approach to quantitative risk management without unnecessary theory or promotional trading claims. It provides the tools and context needed to understand risk models, implement them in Python, and use them responsibly in financial analysis. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.