{"product_id":"derivatives-analytics-with-python-data-analysis-models-simulation-calibration-and-hedging-hardcover","title":"Derivatives Analytics with Python: Data Analysis, Models, Simulation, Calibration and Hedging - Hardcover","description":"\u003cp\u003eby \u003cb\u003eYves Hilpisch\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003cb\u003eSupercharge options analytics and hedging using the power of Python\u003c\/b\u003e \u003c\/p\u003e\u003cp\u003e\u003ci\u003eDerivatives Analytics with Python\u003c\/i\u003e 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.\u003c\/p\u003e \u003cp\u003ePython 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.\u003c\/p\u003e \u003cul\u003e \u003cli\u003eReproduce major stylized facts of equity and options markets yourself\u003c\/li\u003e \u003cli\u003eApply Fourier transform techniques and advanced Monte Carlo pricing\u003c\/li\u003e \u003cli\u003eCalibrate advanced option pricing models to market data\u003c\/li\u003e \u003cli\u003eIntegrate advanced models and numeric methods to dynamically hedge options\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eRecent 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. \u003ci\u003eDerivatives Analytics with Python -- Data Analysis, Models, Simulation, Calibration and Hedging\u003c\/i\u003e shows you what you need to know to supercharge your derivatives and risk analytics efforts.\u003c\/p\u003e\u003ch3\u003eFront Jacket\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eMarket-based valuation of stock index options is an essential task for every buy-side and sell-side decision maker in the derivatives analytics domain. In \u003ci\u003eDerivatives Analytics with Python\u003c\/i\u003e, you'll discover why Python has established itself in the financial industry and how to leverage this powerful programming language so you can implement market-consistent valuation and hedging approaches. \u003c\/p\u003e\u003cp\u003eWritten for Quant developers, traders, risk managers, compliance officers, and model validators, this reliable resource skillfully covers the four areas necessary to effectively value options: market-based valuation as a process; sound market model; numerical techniques; and technology. Presented in three parts, Part One looks at the risks affecting the value of equity index options and empirical facts regarding stocks and interest rates. Part Two covers arbitrage pricing theory, risk-neutral valuation in discrete time, continuous time, and introduces the two popular methods of Carr-Madan and Lewis for Fourier-based option pricing. Finally, Part Three considers the whole process of a market-based valuation effort and the Monte Carlo simulation as the method of choice for the valuation of exotic and complex index options and derivatives. \u003c\/p\u003e\u003cp\u003ePractical and informative, with self-contained Python scripts and modules and 5,000+ lines of code provided to help you reproduce the results and graphics presented. In addition, the companion website (http: \/\/wiley. quant-platform.com) features all code and IPython Notebooks for immediate execution and automation. \u003c\/p\u003e\u003cp\u003eAuthor Yves Hilpisch explores market-based valuation as a process, as well as empirical findings about market realities. By reading this book, you'll be equipped to develop much-needed tools during a market-based valuation with balanced coverage of: \u003c\/p\u003e\u003cul\u003e \u003cli\u003eMarket-based valuation\u003c\/li\u003e \u003cli\u003eRisk-neutral valuation\u003c\/li\u003e \u003cli\u003eDiscrete market models\u003c\/li\u003e \u003cli\u003eBlack-Scholes-Merton Model\u003c\/li\u003e \u003cli\u003eFourier-based option pricing\u003c\/li\u003e \u003cli\u003eValuation of American options\u003c\/li\u003e \u003cli\u003eStochastic volatility and jump-diffusion models\u003c\/li\u003e \u003cli\u003eModel calibration\u003c\/li\u003e \u003cli\u003eSimulation and valuation\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003ePython is gaining ground in the derivatives analytics space, allowing institutions to quickly and efficiently deliver pricing, trading, and risk management results. Learn to implement market-consistent valuation and hedging approaches for European and American options with the solid guidance found in \u003ci\u003eDerivatives Analytics with Python\u003c\/i\u003e.\u003c\/p\u003e\u003ch3\u003eBack Jacket\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eMarket-based valuation of stock index options is an essential task for every buy-side and sell-side decision maker in the derivatives analytics domain. In \u003ci\u003eDerivatives Analytics with Python\u003c\/i\u003e, you'll discover why Python has established itself in the financial industry and how to leverage this powerful programming language so you can implement market-consistent valuation and hedging approaches. \u003c\/p\u003e\u003cp\u003eWritten for Quant developers, traders, risk managers, compliance officers, and model validators, this reliable resource skillfully covers the four areas necessary to effectively value options: market-based valuation as a process; sound market model; numerical techniques; and technology. Presented in three parts, Part One looks at the risks affecting the value of equity index options and empirical facts regarding stocks and interest rates. Part Two covers arbitrage pricing theory, risk-neutral valuation in discrete time, continuous time, and introduces the two popular methods of Carr-Madan and Lewis for Fourier-based option pricing. Finally, Part Three considers the whole process of a market-based valuation effort and the Monte Carlo simulation as the method of choice for the valuation of exotic and complex index options and derivatives. \u003c\/p\u003e\u003cp\u003ePractical and informative, with self-contained Python scripts and modules and 5,000+ lines of code provided to help you reproduce the results and graphics presented. In addition, the companion website (http: \/\/wiley.quant-platform.com) features all code and IPython Notebooks for immediate execution and automation. \u003c\/p\u003e\u003cp\u003eAuthor Yves Hilpisch explores market-based valuation as a process, as well as empirical findings about market realities. By reading this book, you'll be equipped to develop much-needed tools during a market-based valuation with balanced coverage of: \u003c\/p\u003e\u003cul\u003e \u003cli\u003eMarket-based valuation\u003c\/li\u003e \u003cli\u003eRisk-neutral valuation\u003c\/li\u003e \u003cli\u003eDiscrete market models\u003c\/li\u003e \u003cli\u003eBlack-Scholes-Merton Model\u003c\/li\u003e \u003cli\u003eFourier-based option pricing\u003c\/li\u003e \u003cli\u003eValuation of American options\u003c\/li\u003e \u003cli\u003eStochastic volatility and jump-diffusion models\u003c\/li\u003e \u003cli\u003eModel calibration\u003c\/li\u003e \u003cli\u003eSimulation and valuation\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003ePython is gaining ground in the derivatives analytics space, allowing institutions to quickly and efficiently deliver pricing, trading, and risk management results. Learn to implement market-consistent valuation and hedging approaches for European and American options with the solid guidance found in \u003ci\u003eDerivatives Analytics with Python\u003c\/i\u003e.\u003c\/p\u003e\u003ch3\u003eAuthor Biography\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eYVES HILPISCH\u003c\/b\u003e is founder and Managing Partner of The Python Quants, a group that focuses on Python \u0026amp; Open Source Software for Quantitative Finance. Yves is also a Computational Finance Lecturer on the CQF Program. He works with clients in the financial industry around the globe and has ten years of experience with Python. Yves is the organizer of Python and Open Source for Quant Finance conferences and meetup groups in Frankfurt, London and New York City.\u003c\/p\u003e\n        \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 384\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 1.1 x 9.7 x 6.6 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e August 03, 2015\u003c\/div\u003e\n            ","brand":"Books by splitShops","offers":[{"title":"Default Title","offer_id":42744782291007,"sku":"9781119037996","price":181.44,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0105\/8226\/1823\/files\/b4e3f2ea2daacc798e1564627ebdfc22.webp?v=1765169459","url":"https:\/\/dhlswag.com\/products\/derivatives-analytics-with-python-data-analysis-models-simulation-calibration-and-hedging-hardcover","provider":"BBB","version":"1.0","type":"link"}