Option Valuation Under Stochastic Volatility II

Option Valuation Under Stochastic Volatility II

Author: Alan L. Lewis

Publisher:

Published: 2016-05-12

Total Pages: 748

ISBN-13: 9780967637211

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This book is a sequel to the author's well-received "Option Valuation under Stochastic Volatility." It extends that work to jump-diffusions and many related topics in quantitative finance. Topics include spectral theory for jump-diffusions, boundary behavior for short-term interest rate models, modelling VIX options, inference theory, discrete dividends, and more. It provides approximately 750 pages of original research in 26 chapters, with 165 illustrations, Mathematica, and some C/C++ codes. The first 12 chapters (550 pages) are completely new. Also included are reprints of selected previous publications of the author for convenient reference. The book should interest both researchers and quantitatively-oriented investors and traders. First 12 chapters: Slow Reflection, Jump-Returns, & Short-term Interest Rates Spectral Theory for Jump-diffusions Joint Time Series Modelling of SPX and VIX Modelling VIX Options (and Futures) under Stochastic Volatility Stochastic Volatility as a Hidden Markov Model Continuous-time Inference: Mathematical Methods and Worked Examples A Closer Look at the Square-root and 3/2-model A Closer Look at the SABR Model Back to Basics: An Update on the Discrete Dividend Problem PDE Numerics without the Pain Exact Solution to Double Barrier Problems under a Class of Processes Advanced Smile Asymptotics: Geometry, Geodesics, and All That


American Option Pricing Under Stochastic Volatility

American Option Pricing Under Stochastic Volatility

Author: Manisha Goswami

Publisher:

Published: 2008

Total Pages:

ISBN-13:

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The approximate method to price American options makes use of the fact that accurate pricing of these options does not require exact determination of the early exercise boundary. Thus, the procedure mixes the two models of constant and stochastic volatility. The idea is to obtain early exercise boundary through constant volatility model using the approximation methods of AitSahlia and Lai or Ju and then utilize this boundary to price the options under stochastic volatility models. The data on S & P 100 Index American options is used to analyze the pricing performance of the mixing of the two models. The performance is studied with respect to percentage pricing error and absolute pricing errors for each money-ness maturity group.


American Options Under Stochastic Volatility

American Options Under Stochastic Volatility

Author: Arun Chockalingam

Publisher:

Published: 2012

Total Pages: 30

ISBN-13:

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The problem of pricing an American option written on an underlying asset with constant price volatility has been studied extensively in literature. Real-world data, however, demonstrates that volatility is not constant and stochastic volatility models are used to account for dynamic volatility changes. Option pricing methods that have been developed in literature for pricing under stochastic volatility focus mostly on European options. We consider the problem of pricing American options under stochastic volatility which has relatively had much less attention from literature. First, we develop an exercise-policy improvement procedure to compute the optimal exercise policy and option price. We show that the scheme monotonically converges for various popular stochastic volatility models in literature. Second, using this computational tool, we explore a variety of questions that seek insights into the dependence of option prices, exercise policies and implied volatilities on the market price of volatility risk and correlation between the asset and stochastic volatility.


Multiscale Stochastic Volatility for Equity, Interest Rate, and Credit Derivatives

Multiscale Stochastic Volatility for Equity, Interest Rate, and Credit Derivatives

Author: Jean-Pierre Fouque

Publisher: Cambridge University Press

Published: 2011-09-29

Total Pages: 456

ISBN-13: 113950245X

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Building upon the ideas introduced in their previous book, Derivatives in Financial Markets with Stochastic Volatility, the authors study the pricing and hedging of financial derivatives under stochastic volatility in equity, interest-rate, and credit markets. They present and analyze multiscale stochastic volatility models and asymptotic approximations. These can be used in equity markets, for instance, to link the prices of path-dependent exotic instruments to market implied volatilities. The methods are also used for interest rate and credit derivatives. Other applications considered include variance-reduction techniques, portfolio optimization, forward-looking estimation of CAPM 'beta', and the Heston model and generalizations of it. 'Off-the-shelf' formulas and calibration tools are provided to ease the transition for practitioners who adopt this new method. The attention to detail and explicit presentation make this also an excellent text for a graduate course in financial and applied mathematics.