Volatility clustering, long-range dependence, non-Gaussianity and anomalous scaling are all well-known stylized facts of financial assets return dynamics. These elements have a relevant impact on the aptness of models for the pricing of options written on financial assets. We make us of a model...

In this paper we propose the optimum weighting scheme for pricing American options under a local volatility model. American options are priced under the constant elasticity of variance volatility model using Monte Carlo simulation. The residuals obtained from regression were heteroscedastic. For...

We present a computationally tractable method for simulating arbitrage free implied volatility surfaces. We illustrate how our method may be combined with a factor model for the implied volatility surface to generate dynamic scenarios for arbitrage-free implied volatility surfaces. Our approach...

Volatility implied from observed option contracts systematically varies with the contracts' strike price and time to expiration, giving rise to an instantaneously non-flat implied volatility surface (IVS) that exhibits substantial time variation. We identify a number of latent factors that drive...

Recent general equilibrium models prescribe predictable dynamics in the volatility surfaces that are implied by observed option prices. In this paper we investigate the predictability of surfaces, using extensive time series of implied volatilities from over-the-counter options on eight...

We examine whether the dynamics of the implied volatility surface of individual equity options contains exploitable predictability patterns. Predictability in implied volatilities is expected due to the learning behavior of agents in option markets. In particular, we explore the possibility that...

Recent empirical studies report predictable dynamics in the volatility surfaces implied by observed index option prices, as prescribed by general equilibrium models. Using an extensive data set from the over-the-counter options market, we document similar predictability in the factors that...

Option pricing models are tools for pricing and hedging derivatives. Good models are complex and the econometrician faces many design decisions when bringing them to the data. I show that strategically constructed low-dimensional filter designs outperform those that try to use all the available...

This article proposes a simple and intuitive framework to combine a discrete volatility forecast series produced by a GARCH model with the binomial tree methodology to price path-dependent options. The framework exploits the premise of the path integral methodology of combining the terminal...

Daily returns of financial assets are frequently found to exhibit positive autocorrelation at lag 1. When specifying a linear AR(l) conditional mean, one may ask how this predictability affects option prices. We investigate the dependence of option prices on autoregressive dynamics under...