Calibration and Pricing Under a Stochastic Volatility Jump Diffusion Model with Time-dependent Parameters

Calibration and Pricing Under a Stochastic Volatility Jump Diffusion Model with Time-dependent Parameters PDF Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 63

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Implied Calibration and Moments Asymptotics in Stochastic Volatility Jump Diffusion Models

Implied Calibration and Moments Asymptotics in Stochastic Volatility Jump Diffusion Models PDF Author: Stefano Galluccio
Publisher:
ISBN:
Category :
Languages : en
Pages : 32

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Book Description
In the context of arbitrage-free modelling of financial derivatives, we introduce a novel calibration technique for models in the affine-quadratic class for the purpose of over-the-counter option pricing and risk-management. In particular, we aim at calibrating a stochastic volatility jump diffusion model to the whole market implied volatility surface at any given time. We study the asymptotic behaviour of the moments of the underlying distribution and use this information to introduce and implement our calibration algorithm. We numerically show that the proposed approach is both statistically stable and accurate.

Approximation and Calibration of Short-Term Implied Volatilities Under Jump-Diffusion Stochastic Volatility

Approximation and Calibration of Short-Term Implied Volatilities Under Jump-Diffusion Stochastic Volatility PDF Author: Alexey Medvedev
Publisher:
ISBN:
Category :
Languages : en
Pages :

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We derive an asymptotic expansion formula for option implied volatility under a two-factor jump-diffusion stochastic volatility model when time-to-maturity is small. We further propose a simple calibration procedure of an arbitrary parametric model to short-term near-the-money implied volatilities. An important advantage of our approximation is that it is free of the unobserved spot volatility. Therefore, the model can be calibrated on option data pooled across different calendar dates to extract information from the dynamics of the implied volatility smile. An example of calibration to a sample of Samp;P 500 option prices is provided. (JEL G12).

Numerical Analysis Of Stochastic Volatility Jump Diffusion Models

Numerical Analysis Of Stochastic Volatility Jump Diffusion Models PDF Author: Abdelilah Jraifi
Publisher: LAP Lambert Academic Publishing
ISBN: 9783659564895
Category :
Languages : en
Pages : 104

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Book Description
In the modern economic world, the options contracts are used because they allow to hedge against the vagaries and risks refers to fluctuations in the prices of the underlying assets. The determination of the price of these contracts is of great importance for investors.We are interested in problems of options pricing, actually the European and Quanto options on a financial asset. The price of that asset is modeled by a multi-dimentional jump diffusion with stochastic volatility. Otherwise, the first model considers the volatility as a continuous process and the second model considers it as a jump process. Finally in the 3rd model, the underlying asset is without jump and volatility follows a model CEV without jump. This model allow better to take into account some phenomena observed in the markets. We develop numerical methods that determine the values of prices for these options. We first write the model as an integro-differential stochastic equations system "EIDS," of which we study existence and unicity of solutions. Then we relate the resolution of PIDE to the computation of the option value.

Financial Modelling with Jump Processes

Financial Modelling with Jump Processes PDF Author: Peter Tankov
Publisher: CRC Press
ISBN: 1135437947
Category : Business & Economics
Languages : en
Pages : 552

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Book Description
WINNER of a Riskbook.com Best of 2004 Book Award! During the last decade, financial models based on jump processes have acquired increasing popularity in risk management and option pricing. Much has been published on the subject, but the technical nature of most papers makes them difficult for nonspecialists to understand, and the mathematic

A Simple Calibration Procedure of Stochastic Volatility Models with Jumps by Short Term Asymptotics

A Simple Calibration Procedure of Stochastic Volatility Models with Jumps by Short Term Asymptotics PDF Author: Alexey Medvedev
Publisher:
ISBN:
Category :
Languages : en
Pages : 56

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Book Description
In this paper we develop approximating formulas for European options prices based on short term asymptotics, i.e. when time-to-maturity tends to zero. The analysis is performed in a general setting where stochastic volatility and jumps drive the dynamics of stock returns. In a numerical study we show that the closed form approximation is accurate for a broad range of option parameters typically encountered in practice. An empirical application illustrates its use in calibrating observed smiles of Samp;P 500 index options, and in getting new insight into the dependence of the volatility of volatility and jump size distribution on the spot volatility. We test the consistency of the calibration by showing that the shape of the volatility of volatility inferred from option prices agrees with its estimate from the time series of spot volatilities inferred from the same observed option prices.

Numerical Analysis of Multiscale Computations

Numerical Analysis of Multiscale Computations PDF Author: Björn Engquist
Publisher: Springer Science & Business Media
ISBN: 3642219438
Category : Computers
Languages : en
Pages : 432

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Book Description
This book is a snapshot of current research in multiscale modeling, computations and applications. It covers fundamental mathematical theory, numerical algorithms as well as practical computational advice for analysing single and multiphysics models containing a variety of scales in time and space. Complex fluids, porous media flow and oscillatory dynamical systems are treated in some extra depth, as well as tools like analytical and numerical homogenization, and fast multipole method.

Jump-Diffusion Processes

Jump-Diffusion Processes PDF Author: Leif B. G. Andersen
Publisher:
ISBN:
Category :
Languages : en
Pages : 45

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Book Description
The standard approach (e.g. Dupire (1994) and Rubinstein (1994)) to fitting stock processes to observed option prices models the underlying stock price as a one-factor diffusion process with state- and time-dependent volatility. While this approach is attractive in the sense that market completeness is maintained, the resulting model is often highly non-stationary, difficult to fit to steep volatility smiles, and generally is not well supported by empirical evidence. In this paper, we attempt to overcome some of these problems by overlaying the diffusion dynamics with a jump-process, effectively assuming that a large part of the observed volatility smiles can be explained by fear of sudden large market movements (quot;crash-o-phobiaquot;). The first part of this paper derives a forward PIDE (Partial Integro-Differential Equation) satisfied by European call option prices and demonstrates how the resulting equation can be used to fit the model to the observed volatility smile/skew. In the second part of the paper, we discuss efficient methods of applying the calibrated model to the pricing of contingent claims. In particular, we develop an ADI (Alternating Directions Implicit) finite difference method that is shown to be unconditionally stable and, if combined with FFT (Fast Fourier Transform) methods, computationally efficient. The paper also discusses the usage of Monte Carlo methods, and contains several detailed examples from the Samp;P500 market. We compare pricing results obtained by the jump-diffusion approach with those of pure diffusion, and find significant differences for a range of popular contracts.

A Hull and White Formula for a General Stochastic Volatility Jump-diffusion Model with Applications to the Study of the Short-time Behavior of the Implied Volatility

A Hull and White Formula for a General Stochastic Volatility Jump-diffusion Model with Applications to the Study of the Short-time Behavior of the Implied Volatility PDF Author: Elisa Alós
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Financial Modelling

Financial Modelling PDF Author: Joerg Kienitz
Publisher: John Wiley & Sons
ISBN: 0470744898
Category : Business & Economics
Languages : en
Pages : 736

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Book Description
Financial modelling Theory, Implementation and Practice with MATLAB Source Jörg Kienitz and Daniel Wetterau Financial Modelling - Theory, Implementation and Practice with MATLAB Source is a unique combination of quantitative techniques, the application to financial problems and programming using Matlab. The book enables the reader to model, design and implement a wide range of financial models for derivatives pricing and asset allocation, providing practitioners with complete financial modelling workflow, from model choice, deriving prices and Greeks using (semi-) analytic and simulation techniques, and calibration even for exotic options. The book is split into three parts. The first part considers financial markets in general and looks at the complex models needed to handle observed structures, reviewing models based on diffusions including stochastic-local volatility models and (pure) jump processes. It shows the possible risk-neutral densities, implied volatility surfaces, option pricing and typical paths for a variety of models including SABR, Heston, Bates, Bates-Hull-White, Displaced-Heston, or stochastic volatility versions of Variance Gamma, respectively Normal Inverse Gaussian models and finally, multi-dimensional models. The stochastic-local-volatility Libor market model with time-dependent parameters is considered and as an application how to price and risk-manage CMS spread products is demonstrated. The second part of the book deals with numerical methods which enables the reader to use the models of the first part for pricing and risk management, covering methods based on direct integration and Fourier transforms, and detailing the implementation of the COS, CONV, Carr-Madan method or Fourier-Space-Time Stepping. This is applied to pricing of European, Bermudan and exotic options as well as the calculation of the Greeks. The Monte Carlo simulation technique is outlined and bridge sampling is discussed in a Gaussian setting and for Lévy processes. Computation of Greeks is covered using likelihood ratio methods and adjoint techniques. A chapter on state-of-the-art optimization algorithms rounds up the toolkit for applying advanced mathematical models to financial problems and the last chapter in this section of the book also serves as an introduction to model risk. The third part is devoted to the usage of Matlab, introducing the software package by describing the basic functions applied for financial engineering. The programming is approached from an object-oriented perspective with examples to propose a framework for calibration, hedging and the adjoint method for calculating Greeks in a Libor market model. Source code used for producing the results and analysing the models is provided on the author's dedicated website, http://www.mathworks.de/matlabcentral/fileexchange/authors/246981.