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Superfícies de volatilidade

Authors: Sousa, André Filipe Figueira de;

Superfícies de volatilidade

Abstract

O presente trabalho tem como objectivo debruçar-se sobre a construção de superfícies de volatilidade implícita. Toma-se, como ponto de partida, a literatura existente que nos diz que o modelo de Black-Merton-Scholes (BMS) apresenta várias limitações, sendo que a principal, para muitos, é considerar a volatilidade determinística. Neste trabalho, como forma de eliminar este problema, iremos apresentar a metodologia desenvolvida por Peter Carr e Liuren Wu (2011), de forma a construir uma superfície de volatilidade não determinística, que não seja tão difícil de obter como nos modelos de volatilidade estocástica e que seja mais rápida de estimar. Esta metodologia especifica o preço do activo subjacente e a dinâmica da volatilidade implícita, enquanto deixa a dinâmica da taxa da volatilidade instantânea variar livremente. Por sua vez, o domínio dos valores admissíveis para a superfície de volatilidade implícita inicial deriva de uma base com argumentos de não arbitragem. Com o objectivo de modelar a volatilidade implícita para os dois modelos apresentados no trabalho de Peter Carr e Liuren Wu (2011), o square-root variance model e o lognormal variance model, usamos uma variante do square-root process. Nessa construção, é usado o unscented Kalman FIlter e um algoritmo de minimização de erros, como forma de determinar os parâmetros que necessitamos para resolver a equação do modelo. Este trabalho é composto por duas vertentes, uma vertente teórica e uma vertente prática. A vertente teórica, incide sobre a metodologia apresentada por Peter Carr e Liuren Wu (2011), enquanto que a vertente prática, inclina-se sobre a construção do unscented Kalman FIlter e do algoritmo de minimização, como forma de determinar os parâmetros que necessitamos para a dinâmica da volatilidade do preço do activo subjacente.

The objective of this thesis is to construct an implied volatility surface to price options. We start from the existing literature that says Black-Merton-Scholes (BMS) has many drawbacks, being the most important one assuming deterministic volatility. In this thesis, we will present Peter Carr and Liuren Wu (2011) methodology for constructing a volatility surface that is not assumed to be deterministic, is not so complicated to determine like in stochastic volatility models and is faster to estimate. This thesis proposes a new approach, which specifies the security price and the implied volatility dynamics while leaving the instantaneous variance rate dynamics unspecified. The allowable shape for the initial implied volatility surface is then derived based on dynamic no-arbitrage arguments. This thesis presents two models for constructing volatility surfaces using a variant of the square-root process for the volatility process. This paper has two parts, one theoretical and another practical. In the theoretical part we demonstrate the paper of Peter Carr and Liuren Wu (2011) to construct volatility surfaces, while in the practical part we construct an unscented Kalman filter with a minimization algorithm to determine the parameters that we need to construct the real dynamics of the implied volatility surface of the underlying.

Tese de mestrado em Matemática Financeira, apresentada à Universidade de Lisboa, através da Faculdade de Ciências, 2013

Country
Portugal
Related Organizations
Keywords

Vega-gamma-vanna-volga, Calibração dinâmica, Square-root variance model, Unscented Kalman filter, Lognormal variance model, Teses de mestrado - 2013, Superfície de volatilidade implícita

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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