Implied volatility asymptotics under affine stochastic volatility models

This thesis is concerned with the calibration of affine stochastic volatility models with jumps. This class of models encompasses most models used in practice and captures some of the common features of market data such as jumps and heavy tail distributions of returns. Two questions arise when one wants to calibrate such a model: (a) How to check its theoretical consistency with the relevant market characteristics? (b) How to calibrate it rigorously to market data, in particular to the so-called implied volatility, which is a normalised measure of option prices? These two questions form the backbone of this thesis, since they led to the following idea: instead of calibrating a model using a computer-intensive global optimisation algorithm, it should be more efficient to use a less robust—hence faster—algorithm, but with an accurate starting point. Henceforth deriving closed-form approximation formulae for the implied-volatility should provide a way to obtain such accurate initial points, thus ensuring a faster calibration. In this thesis we propose such a calibration approach based on the time-asymptotics of affine stochastic volatility models with jumps. Mathematically since this class of models is defined via its Laplace transform, the tools we naturally use are large deviations theory as well as complex saddle-point methods. Large deviations enable us to obtain the limiting behaviour (in small or large time) of the implied volatility, and saddle-point methods are needed to obtain more accurate results on the speed of convergence. We also provide numerical evidence in order to highlight the accuracy of the closed-form approximations thus obtained, and compare them to standard pricing methods based on real calibrated data

Convergence of Heston to SVI

In this short note, we prove by an appropriate change of variables that the SVI implied volatility parameterization presented in Gatheral's book and the large-time asymptotic of the Heston implied volatility agree algebraically, thus confirming a conjecture from Gatheral as well as providing a simpler expression for the asymptotic implied volatility in the Heston model. We show how this result can help in interpreting SVI parameters.Comment: 5 page

From characteristic functions to implied volatility expansions

For any strictly positive martingale $S = \exp(X)$ for which $X$ has a characteristic function, we provide an expansion for the implied volatility. This expansion is explicit in the sense that it involves no integrals, but only polynomials in the log strike. We illustrate the versatility of our expansion by computing the approximate implied volatility smile in three well-known martingale models: one finite activity exponential L\'evy model (Merton), one infinite activity exponential L\'evy model (Variance Gamma), and one stochastic volatility model (Heston). Finally, we illustrate how our expansion can be used to perform a model-free calibration of the empirically observed implied volatility surface.Comment: 21 pages, 4 figure

Asymptotics of forward implied volatility

We prove here a general closed-form expansion formula for forward-start options and the forward implied volatility smile in a large class of models, including the Heston stochastic volatility and time-changed exponential L\'evy models. This expansion applies to both small and large maturities and is based solely on the properties of the forward characteristic function of the underlying process. The method is based on sharp large deviations techniques, and allows us to recover (in particular) many results for the spot implied volatility smile. In passing we (i) show that the forward-start date has to be rescaled in order to obtain non-trivial small-maturity asymptotics, (ii) prove that the forward-start date may influence the large-maturity behaviour of the forward smile, and (iii) provide some examples of models with finite quadratic variation where the small-maturity forward smile does not explode.Comment: 37 pages, 13 figure

Asymptotic arbitrage in the Heston model

In the context of the Heston model, we establish a precise link between the set of equivalent martingale measures, the ergodicity of the underlying variance process and the concept of asymptotic arbitrage proposed in Kabanov-Kramkov and in Follmer-Schachermayer.Comment: 13 pages. New definition of partial asymptotic arbitrage introduced. Main theorems revise

Asymptotic formulae for implied volatility in the Heston model

In this paper we prove an approximate formula expressed in terms of elementary functions for the implied volatility in the Heston model. The formula consists of the constant and first order terms in the large maturity expansion of the implied volatility function. The proof is based on saddlepoint methods and classical properties of holomorphic functions.Comment: Presentation in Section 2 has been improved. Theorem 3.1 has been slightly generalised. Figures 2 and 3 now include the at-the-money point