Derivatives Analytics with Python: Data Analysis, Models, Simulation, Calibration and Hedging (Hardcover)

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.

使用Python的強大功能，加強期權分析和對沖。《Python衍生品分析》向您展示如何使用先進的金融模型、高效的數值技術和Python編程語言的強大功能，實施市場一致的估值和對沖方法。這本獨特的指南詳細解釋了所有理論、方法和過程，為您提供了評估股票指數期權所需的背景和工具。您將找到並使用獨立的Python腳本和模塊，並學習如何將Python應用於高級數據和衍生品分析，同時受益於提供的5000多行代碼，以幫助您重現所呈現的結果和圖形。內容包括市場數據分析、風險中性估值、蒙特卡羅模擬、模型校準、估值和動態對沖，其中模型展示了隨機波動、跳躍組件、隨機短期利率等。配套網站提供所有代碼和IPython筆記本，可立即執行和自動化。Python在衍生品分析領域越來越受到重視，使機構能夠快速高效地提供投資組合、交易和風險管理結果。本書是金融專業人士利用Python進行高效和高性能衍生品分析的指南。 * 自己重現股票和期權市場的主要特徵 * 應用傅立葉變換技術和高級蒙特卡羅定價 * 將高級期權定價模型校準到市場數據 * 整合高級模型和數值方法以動態對沖期權 Python生態系統的最新發展使分析師能夠實現與C或C++一樣高效的分析任務，但只需使用大約十分之一甚至更少的代碼。《Python衍生品分析：數據分析、模型、模擬、校準和對沖》向您展示了如何加強您的衍生品和風險分析工作。