Estimation of a Stochastic Volatility Model Using Pricing and Hedging Information

Estimation of a Stochastic Volatility Model Using Pricing and Hedging Information
Author: Jason Fink
Publisher:
Total Pages: 23
Release: 2005
Genre:
ISBN:

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Estimation of option pricing models in which the underlying asset exhibits stochastic volatility presents complicated econometric questions. One such question, thus far unstudied, is whether the inclusion of information derived from hedging relationships implied by an option pricing model may be used in conjunction with pricing information to provide more reliable parameter estimates than the use of pricing information alone. This paper estimates, using a simple least-squares procedure, the stochastic volatility model of Heston (1993), and includes hedging information in the objective function. This hedging information enters the objective function through a weighting parameter that is chosen optimally within the model. With the weight appropriately chosen, we find that incorporating the hedging information reduces both the out-of-sample hedging and pricing errors associated with the Heston model.

Estimating a Stochastic Volatility Model for DAX-Index Options

Estimating a Stochastic Volatility Model for DAX-Index Options
Author:
Publisher:
Total Pages:
Release: 2003
Genre:
ISBN:

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The paper examines alternative strategies for pricing and hedging options on German DAX-index. To this purpose an affine stochastic volatility model is estimated directly on objective probability system through a three step approach. Errors obtained by the implementation of the stochastic volatility model and Black and Scholes with different historical and implied volatility measures are compared and the performance is evaluated in terms of out-of-sample pricing and hedging. The results for DAX-index options market support the estimation on the affine stochastic volatility model in pricing as well as in hedging procedures.

Stochastic Volatility in Financial Markets

Stochastic Volatility in Financial Markets
Author: Antonio Mele
Publisher: Springer Science & Business Media
Total Pages: 156
Release: 2012-12-06
Genre: Business & Economics
ISBN: 1461545331

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Stochastic Volatility in Financial Markets presents advanced topics in financial econometrics and theoretical finance, and is divided into three main parts. The first part aims at documenting an empirical regularity of financial price changes: the occurrence of sudden and persistent changes of financial markets volatility. This phenomenon, technically termed `stochastic volatility', or `conditional heteroskedasticity', has been well known for at least 20 years; in this part, further, useful theoretical properties of conditionally heteroskedastic models are uncovered. The second part goes beyond the statistical aspects of stochastic volatility models: it constructs and uses new fully articulated, theoretically-sounded financial asset pricing models that allow for the presence of conditional heteroskedasticity. The third part shows how the inclusion of the statistical aspects of stochastic volatility in a rigorous economic scheme can be faced from an empirical standpoint.

Stochastic Volatility Modeling

Stochastic Volatility Modeling
Author: Lorenzo Bergomi
Publisher: CRC Press
Total Pages: 520
Release: 2015-12-16
Genre: Business & Economics
ISBN: 1482244071

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Packed with insights, Lorenzo Bergomi's Stochastic Volatility Modeling explains how stochastic volatility is used to address issues arising in the modeling of derivatives, including:Which trading issues do we tackle with stochastic volatility? How do we design models and assess their relevance? How do we tell which models are usable and when does c

Stochastic Volatility

Stochastic Volatility
Author: Torben G. Andersen
Publisher:
Total Pages:
Release: 2010
Genre:
ISBN:

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Complex Systems in Finance and Econometrics

Complex Systems in Finance and Econometrics
Author: Robert A. Meyers
Publisher: Springer Science & Business Media
Total Pages: 919
Release: 2010-11-03
Genre: Business & Economics
ISBN: 1441977007

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Finance, Econometrics and System Dynamics presents an overview of the concepts and tools for analyzing complex systems in a wide range of fields. The text integrates complexity with deterministic equations and concepts from real world examples, and appeals to a broad audience.

A Preliminary View of Calculating Call Option Prices Utilizing Stochastic Volatility Models

A Preliminary View of Calculating Call Option Prices Utilizing Stochastic Volatility Models
Author: Karl Shen
Publisher:
Total Pages: 138
Release: 2009
Genre:
ISBN:

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Abstract: We will begin with a review of key financial topics and outline many of the crucial ideas utilized in the latter half of the paper. Formal notation for important variables will also be established. Then, a derivation of the Black-Scholes equation will lead to a discussion of its shortcomings, and the introduction of stochastic volatility models. Chapter 2 will focus on a variation of the CIR Model using stock price in the volatility driving process, and its behavior to a greater degree. The key area of discussion will be to approximate a hedging function for European call option prices by Taylor Expansion. We will apply this estimation to real data, and analyze the behavior of the price correction. Then make conclusions about whether stock price has any positive effects on the model.

Derivatives in Financial Markets with Stochastic Volatility

Derivatives in Financial Markets with Stochastic Volatility
Author: Jean-Pierre Fouque
Publisher: Cambridge University Press
Total Pages: 222
Release: 2000-07-03
Genre: Business & Economics
ISBN: 9780521791632

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This book, first published in 2000, addresses pricing and hedging derivative securities in uncertain and changing market volatility.