Listed Volatility and Variance Derivatives

A Python-based Guide

Author: Yves Hilpisch

Publisher: John Wiley & Sons

ISBN: 1119167914

Category: Business & Economics

Page: 368

View: 1645

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"Listed Volatility and Variance Derivatives comprehensively covers all aspects related to these now so popular financial products. It is the first to cover European products provided by Eurex and to provide Python codes for implementing all quantitative aspects related to them. Benefits of Reading the Book: - Data Analysis: Learn how to use Python for data and financial analysis. Reproduce major stylized facts of volatility and variance markets by yourself. - Models: Learn the fundamental techniques of modelling volatility (indices) and variance and the model-free replication of variance. - Trading: Learn the micro structure elements of the markets for listed volatility and variance derivatives. - Python: All results, graphics, etc. presented are in general reproducible with the IPython Notebooks and Python codes accompanying the book"--
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Derivatives Analytics with Python - Data Analytics, Models, Simulation, Calibration and Hedging + WS

Author: Yves Hilpisch

Publisher: John Wiley & Sons

ISBN: 1119037999

Category: Business & Economics

Page: 352

View: 4567

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Derivatives Analytics with Python: Data Analysis, Models, Simulation, Calibration and Hedging provides the necessary background information, theoretical foundations and numerical tools to implement a market-based valuation of stock index options. Topics are, amongst others, stylized facts of equity and options markets, risk-neutral valuation, Fourier transform methods, Monte Carlo simulation, model calibration, valuation and dynamic hedging. The financial models introduced in this book exhibit features like stochastic volatility, jump components and stochastic short rates. The approach is a practical one in that all important aspects are illustrated by a set of self-contained Python scripts. Benefits of Reading the Book: Data Analysis: Learn how to use Python for data and financial analysis. Reproduce major stylized facts of equity and options markets by yourself. Models: Learn risk-neutral pricing techniques from ground up, apply Fourier transform techniques to European options and advanced Monte Carlo pricing to American options. Simulation: Monte Carlo simulation is the most powerful and flexible numerical method for derivatives analytics. Simulate models with jumps, stochastic volatility and stochastic short rates. Calibration: Use global and local optimization techniques (incl. penalties) to calibrate advanced option pricing models to market quotes for options with different strikes and maturities. Hedging: Learn how to use advanced option pricing models in combination with advanced numerical methods to dynamically hedge American options. Python: All results, graphics, etc. presented are in general reproducible with the Python scripts accompanying the book. Benefit from more than 5,500 lines of code.
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